System

Abstract

To provide a system.SOLUTION: A system comprises: means for constructing a platform capable of reproducing history; means for collecting historical data from the past to the present and storing it in a database; means for generating a virtual space along a temporal axis on the basis of the collected historical data; means for generating AI with individual thoughts equivalent to the cumulative global population and arranging it in the virtual space to make them autonomously act; means for customizing and displaying the virtual space on the basis of a request of the user; means for allowing the user to interact with an AI agent in the virtual space and acquire information; means for inheriting specific thoughts and behaviors of influential persons and converting them into AI to enable dialog; and means for realistically verifying and visualizing hypotheses to make use of them for future predictions.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, there are no concrete methods for recreating history or predicting the future. There is also a lack of methods for inheriting and utilizing the thoughts and actions of influential people. A new system is needed to solve these problems. [Means for solving the problem]

[0005] This invention builds a platform that enables the re-creation of history, generates AI with individual thoughts equivalent to the total world population, places them in a virtual space, and allows them to act independently. Furthermore, it inherits the specific thoughts and actions of influential people, turning them into AI and enabling dialogue. Various hypotheses can then be realistically verified and visualized to aid in future predictions. This makes it possible to recreate history, predict the future, and inherit and utilize the thoughts and actions of influential people. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] As an embodiment of the present invention, we will build a platform that enables the reproduction of history. This platform will generate a virtual space along a timeline based on historical data from the past to the present. In this virtual space, AIs equivalent to the total world population will be placed. These AIs will have their own individual thoughts and will act independently.

[0029] "Example 2"

[0030] Furthermore, the specific thoughts and actions of influential people can be inherited and turned into AI. Specifically, the AI ​​learns the thought patterns and behaviors of business leaders and historical figures and imitates them. This makes it possible to inherit the knowledge and management decisions of business leaders even after they retire. It is also possible to obtain new management hints through dialogue with historical figures.

[0031] "Example 3"

[0032] Furthermore, various hypotheses can be realistically verified and visualized to aid in future predictions. Specifically, scenarios based on specific hypotheses are set in a virtual space where AI acts autonomously, and the results are observed. This makes it possible to obtain information that is useful for formulating business strategies and making future predictions.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: Collect historical data from the past to the present. This data includes information about people's behavior, events, technological advances, and other time-based information.

[0036] Step 2: Based on the collected historical data, a virtual space along a timeline is generated. This virtual space will become a platform that enables historical reconstruction.

[0037] Step 3: Create a number of AIs equivalent to the total population of the world. These AIs will have their own thoughts and behave independently.

[0038] Step 4: Place the generated AI in a virtual space, creating an environment in which the AI ​​can act autonomously to recreate history.

[0039] "Example 2"

[0040] Step 1: Learn the thought and behavior patterns of influential people. Specifically, extract the thought and behavior patterns from the statements and actions of business leaders and historical figures. Step 2: Generate AI that imitates the extracted thought and behavior patterns.

[0041] Step 3: The generated AI is placed in a virtual space, allowing interaction with the AI ​​that inherits the thoughts and actions of influential people.

[0042] "Example 3"

[0043] Step 1: Create a scenario based on a specific hypothesis. This scenario will serve as a guide for the AI ​​to act autonomously in a virtual space.

[0044] Step 2: The AI ​​acts independently based on the set scenario.

[0045] Step 3: Observe the results of AI actions and analyze the results, which will enable us to obtain information that will be useful for formulating business strategies and making future predictions.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] With current technology, it is difficult to realistically recreate past history and allow users to experience and learn from it. It is also difficult to inherit the thoughts and actions of influential historical figures and interact with them in a virtual space. Furthermore, there is a lack of means to verify hypotheses and make realistic predictions about the future, making it difficult to use for formulating business strategies or predicting the future.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes means for building a platform that enables historical reproduction, means for collecting historical data from the past to the present and storing it in a database, means for generating a virtual space along a timeline based on the collected data, means for generating AIs with individual thoughts equivalent to the total world population and placing them in the virtual space and making them act autonomously, means for customizing and displaying the virtual space based on user requests, means for users to interact with AI agents in the virtual space and obtain information, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help predict the future.This allows users to realistically experience and learn about past history, interact with influential historical figures, and further verify hypotheses and make realistic predictions about the future.

[0051] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience and learn within it.

[0052] "Historical data" refers to information about history, such as past events, demographics, cultural background, and geographic information.

[0053] A "database" is a collection of information that stores collected historical data and is indexed for rapid access through queries.

[0054] "Virtual space" is a three-dimensional digital space generated along a timeline based on collected historical data.

[0055] An "AI agent" is an artificial intelligence that uses a generative AI model to have individual thoughts and act independently.

[0056] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to communicate with users and other AI agents.

[0057] A "User Request" is a request submitted by a User to the Platform specifying a particular historical period or location.

[0058] "Customization" means adjusting the virtual space based on the user's requests and generating detailed scenes relating to specific times and places.

[0059] An "influential person" is someone who has had a major impact in a particular field, such as someone who played an important role in history or a business leader.

[0060] "Hypothesis testing" involves trying out various scenarios in a virtual space and observing the results.

[0061] "Future prediction" is the prediction of future events or situations based on the results of hypothesis verification.

[0062] MODE FOR CARRYING OUT THE INVENTION

[0063] The present invention aims to build a platform that enables historical reproduction, allowing users to realistically experience and learn about past history. A specific embodiment of this system will be described below.

[0064] Generating a Program

[0065] The server generates a platform program that enables historical reproduction. This program has the function of generating a virtual space along a timeline based on historical data from the past to the present.

[0066] Program processing

[0067] The server first collects historical data and stores it in a database, which includes past events, demographics, cultural background, geographic information, etc. The collected data is stored in a database such as MongoDB or MySQL (registered trademark).

[0068] The server then uses this data to generate a virtual space. This virtual space is built using a game engine such as Unity or Unreal Engine. For example, to recreate 19th century Paris, the server places buildings, cityscapes, and scenery from that era into the virtual space. This is done using assets created in 3D modeling tools such as Blender.

[0069] AI agents equivalent in number to the total world population are placed in the virtual space. These AI agents are configured to have individual thoughts and act autonomously using a generative AI model (e.g., GPT-4 (registered trademark) from OpenAI (registered trademark)). The AI ​​agents communicate with the user and other AI agents using natural language processing (NLP) technology.

[0070] Specific examples

[0071] When a user accesses the platform using a device, the server generates a virtual space in response to the user's request and displays it on the device. For example, if a user requests a recreation of 19th century Paris, the server generates a virtual space based on data about 19th century Paris and displays it on the device.

[0072] As a concrete example, a user inputs the following prompt sentence into a generative AI model:

[0073] "Recreate life in 19th century Paris. I'd especially like to learn more about the construction of the Eiffel Tower."

[0074] The server receives this prompt and generates a virtual space based on data about 19th-century Paris, recreating the construction process of the Eiffel Tower in detail. The AI ​​agents act autonomously as workers and citizens of the time, providing real-time information to the user.

[0075] In this way, users can experience past history in a realistic way and interact with influential historical figures. They can also verify hypotheses and make realistic predictions about the future, which can be useful for formulating business strategies and forecasting the future.

[0076] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0077] Step 1:

[0078] The server collects historical data and stores it in a database.

[0079] Input: reliable data sources on the internet (e.g., historical databases and literature)

[0080] How it works: The server uses scraping technology to collect data such as historical events, demographics, cultural background, and geographic information. The collected data is then stored in a database such as MongoDB or MySQL.

[0081] Output: Archived historical data

[0082] Step 2:

[0083] The server generates a virtual space based on the collected data.

[0084] Input: Stored historical data

[0085] How it works: The server uses game engines such as Unity or Unreal Engine to generate 3D models based on the collected data. For example, to recreate 19th century Paris, it places 3D models of buildings and roads from that time. This uses assets created in 3D modeling tools such as Blender.

[0086] Output: Generated virtual space

[0087] Step 3:

[0088] The server places and configures AI agents within the virtual space.

[0089] Input: Generated virtual space, generative AI model

[0090] Specific operation: The server uses a generative AI model (e.g., GPT-4) to set an individual profile for each AI agent. For example, one AI agent is set as a worker in 19th century Paris, while others are set as citizens or merchants. This allows each AI agent to have different behavioral patterns.

[0091] Output: The configured AI agent

[0092] Step 4:

[0093] A user accesses the platform using a terminal and requests a particular historical period or location.

[0094] Input: User request (e.g., "I want a 19th century Paris re-created")

[0095] Specific operation: A user accesses the platform through a browser on their device and requests a specific time and location.

[0096] Output: User request data

[0097] Step 5:

[0098] The server customizes and displays the virtual space based on the user's request.

[0099] Input: User request data, generated virtual space

[0100] How it works: The server customizes the virtual space based on the user's request. For example, if a user requests 19th-century Paris, the server generates a detailed scene, including the construction of the Eiffel Tower, and streams it to the device in real time.

[0101] Output: Customized virtual space

[0102] Step 6:

[0103] Users explore the virtual space through their devices and interact with AI agents.

[0104] Input: A customized virtual space, a user prompt (e.g., "Tell me about the construction of the Eiffel Tower").

[0105] Specific operation: The user moves freely through the virtual space via the terminal and interacts with the AI ​​agent, which uses the generative AI model to respond and provide information in real time based on the user's prompts.

[0106] Output: Response from the AI ​​agent, user experience information

[0107] (Application example 1)

[0108] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0109] Conventional historical reenactment systems simply visually reproduce past events, making it difficult for users to interact with people from that era or move freely around and experience them. Furthermore, interactions within the virtual space are limited, making it impossible to generate real-time responses based on user input. Furthermore, the visual experience using a head-mounted display is insufficient, resulting in a lack of immersion.

[0110] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0111] In this invention, the server includes means for building a platform that enables the reproduction of history, means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to allow them to act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for enabling users to move freely within the virtual space and interact with AI characters, means for visually experiencing the virtual space using a head-mounted display, and means for generating responses from AI characters based on user input and displaying them in the virtual space, thereby enabling users to experience past historical events and eras in the virtual space and interact with AI characters.

[0112] The "platform that enables historical reenactment" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience historical events within it.

[0113] "AI with individual thoughts" is artificial intelligence that has its own unique thought patterns and acts independently.

[0114] A "virtual space" is a three-dimensional digital space generated by a computer, in which users can move freely and interact.

[0115] An "influential person" is someone who has played an important role in history or in the present day, and whose thoughts and actions have a great influence on others.

[0116] "Means enabling dialogue" refers to a function that allows users to have natural conversations with AI characters.

[0117] "A means to realistically verify and visualize hypotheses to help predict the future" is a function that simulates various scenarios in a virtual space and visually displays the results, helping to predict the future and formulate strategies.

[0118] "Means that allow users to move freely and interact with AI characters" refers to a function that allows users to move freely within the virtual space and interact with placed AI characters.

[0119] A "head-mounted display" is a display device that the user wears on their head, allowing them to visually experience a virtual space.

[0120] "Means for generating responses from an AI character based on user input and displaying them in a virtual space" refers to a function that receives input from a user, generates responses from an AI character in real time in response to the input, and displays them in a virtual space.

[0121] The system for implementing this invention uses the following hardware and software: a head-mounted display (e.g., Oculus Rift, HTC Vive) as hardware, and a VR engine (e.g., Unity, Unreal Engine), OpenAI API, and a history database as software.

[0122] The server first builds a platform that enables historical reproduction. Specifically, it generates a virtual space along a timeline based on historical data from the past to the present. In this virtual space, it generates and places AIs with individual thoughts, in numbers equivalent to the total world population. These AIs act autonomously and are able to interact with users.

[0123] By wearing a head-mounted display, users can move freely within the virtual space and interact with AI characters. Based on the user's input, the server uses the OpenAI API to generate responses from the AI ​​characters and display them in the virtual space. This allows users to realistically experience past historical events and eras.

[0124] For example, if a user says, "I want to meet Napoleon," the server will generate an AI character of Napoleon in the virtual space and have it interact with the user. The following is an example of a prompt sentence:

[0125] User: I want to meet Napoleon

[0126] AI: Hello, I'm Napoleon Bonaparte. What question do you have?

[0127] In this way, users can interact with historical figures and experience past events. Hypothesis verification and visualization can also be used to predict the future and formulate strategies.

[0128] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0129] Step 1:

[0130] The server loads historical data from the past to the present from the historical database. The input is the historical database, and the output is the loaded historical data. Specifically, the server executes a database query to obtain the required data.

[0131] Step 2:

[0132] The server generates a virtual space along a timeline based on the loaded historical data. The input is the loaded historical data, and the output is the generated virtual space. Specifically, the server uses a VR engine to construct a three-dimensional virtual space.

[0133] Step 3:

[0134] The server generates AIs with individual thoughts, in numbers equivalent to the total world population, and places them in a virtual space. The input is historical data and a generative AI model, and the output is an AI character placed in the virtual space. Specifically, the server uses the OpenAI API to generate AI characters and place them in the virtual space.

[0135] Step 4:

[0136] The user wears a head-mounted display and accesses the virtual space. The input is the user's visual information, and the output is the visual experience of the virtual space. Specifically, the user wears the head-mounted display and moves freely within the virtual space.

[0137] Step 5:

[0138] The user provides input to interact with the AI ​​character in the virtual space. The input is the user's voice or text, and the output is the user's input data. Specifically, the user speaks to the AI ​​character using voice recognition or text input.

[0139] Step 6:

[0140] The server generates responses for the AI ​​character based on the user's input. The input is the user's input data and the generative AI model, and the output is the AI ​​character's response. Specifically, the server uses the OpenAI API to generate appropriate responses to the user's input.

[0141] Step 7:

[0142] The server displays the generated AI character's response in the virtual space. The input is the AI ​​character's response, and the output is the response displayed in the virtual space. Specifically, the server uses the VR engine to visually display the response.

[0143] Step 8:

[0144] The user checks the response of the AI ​​character displayed in the virtual space and performs the next interaction. The input is the response displayed in the virtual space, and the output is the user's next input. In concrete terms, the user checks the displayed response and asks the next question or gives the next instruction.

[0145] Example 2

[0146] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] There is a need to inherit the knowledge and management decisions of influential figures and utilize that knowledge even after retirement. It is also important to obtain new management hints through dialogue with historical figures. However, there is a lack of concrete methods to effectively inherit this knowledge and decisions and utilize them in actual management. Furthermore, a system is needed to verify hypotheses and make realistic predictions about the future.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0149] In this invention, the server includes means for collecting data on influential people, means for preprocessing the collected data, means for training a machine learning model based on the preprocessed data, means for evaluating the trained model, means for providing an interface for users to interact with the AI, means for the AI ​​to generate answers based on user input, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help with future predictions. This makes it possible to effectively inherit the knowledge and management decisions of influential people and use them in actual management. Furthermore, dialogue with historical figures can provide new management insights, allowing for realistic hypothesis verification and future predictions.

[0150] An "influential person" is someone who plays an important role in society or an organization and whose thoughts and actions have a significant impact on others.

[0151] "Data collection" refers to the process of obtaining information needed for a specific purpose from sources such as the internet or databases.

[0152] "Preprocessing" refers to a series of operations performed on collected data to transform it into a form suitable for analysis and model training, including data cleaning, tokenization, and normalization.

[0153] A "machine learning model" refers to an algorithm or mathematical model that automatically learns specific tasks based on data and makes predictions or classifications.

[0154] "Model training" refers to the process of using collected data to train a machine learning model and improve its performance.

[0155] "Model evaluation" refers to the process of evaluating the performance of a trained machine learning model using test data to confirm its accuracy and effectiveness.

[0156] "User interface" refers to the software and hardware components that provide a means for a user to interact with a system, including chatbots and voice recognition.

[0157] A "prompt" refers to the text of a question or instruction that a user enters into an AI.

[0158] "Hypothesis verification" refers to the process of verifying whether a particular hypothesis is correct using actual data or simulations.

[0159] "Future forecasting" refers to the process of predicting future events or conditions based on current data and trends.

[0160] This invention is a system for inheriting the knowledge and management decisions of influential people and utilizing that knowledge even after they retire. A specific embodiment of this system will be described below.

[0161] The server first collects data on influencers, including their past statements, behavioral history, and decision-making processes, using web scraping tools (e.g., BeautifulSoup, Scrapy) or APIs.

[0162] The server then preprocesses the collected data, which includes cleaning the text data (denoising, normalising), tokenising, removing stop words, etc. This is done using natural language processing libraries such as Python's NLTK or spaCy.

[0163] The server trains a machine learning model based on the preprocessed data. This model is designed to learn the thought and behavior patterns of influential people. Training is performed using deep learning frameworks such as TENSORFLOW (registered trademark) and PyTorch, and is run on a server equipped with high-performance GPUs.

[0164] The trained model is evaluated by the server. The evaluation involves checking the accuracy of the model using test data and adjusting hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc.

[0165] The device provides an interface for users to interact with the AI, including chatbot-style interfaces and voice-activated applications, using web frameworks such as Flask and Django.

[0166] The user poses a question to the AI ​​through their device. For example, the user might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the device's chat box. For example, a response might read, "When entering a new market, it is important to first conduct thorough market research. To minimize risk, it is necessary to work with local partners and understand differences in laws, regulations, and culture."

[0167] In this way, the knowledge and management decisions of influential figures can be effectively passed on and put to use in actual management. Furthermore, through dialogue with historical figures, new management hints can be obtained, and hypotheses can be verified and future predictions can be made in real time.

[0168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0169] Step 1:

[0170] The server collects data on influential people. Specifically, it uses web scraping tools (e.g., BeautifulSoup, Scrapy) and APIs to retrieve data such as executives' past statements, behavioral history, and decision-making processes from the internet and corporate databases. The input is the website URL or API endpoint, and the output is the collected text data.

[0171] Step 2:

[0172] The server preprocesses the collected data. Specifically, it uses Python's NLTK and spaCy to clean the text data (remove noise, normalize), tokenize, and remove stop words. The input is the collected text data, and the output is the preprocessed, clean text data.

[0173] Step 3:

[0174] The server trains a machine learning model based on the preprocessed data. Specifically, it uses TensorFlow and PyTorch to build a deep learning model that learns the thought patterns and behavior patterns of influential people. The input is the preprocessed text data, and the output is the trained machine learning model.

[0175] Step 4:

[0176] The server evaluates the trained model. Specifically, it checks the model's accuracy using test data and adjusts hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc. The input is the trained machine learning model and test data, and the output is the evaluation results and the adjusted model.

[0177] Step 5:

[0178] The terminal provides an interface for users to interact with the AI. Specifically, Flask and Django are used to build an application with a chatbot-style interface and speech recognition functionality. The input is the user's questions and instructions (prompts), and the output is the AI's response.

[0179] Step 6:

[0180] The user poses a question to the AI ​​through the terminal. For example, they might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the terminal's chat box. The input is the user's prompt, and the output is the answer from the AI.

[0181] (Application example 2)

[0182] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0183] In today's business environment, there is a need to inherit and utilize in real time the knowledge and management decisions of influential business leaders and historical figures. However, existing technologies have limited the means to effectively utilize this knowledge, making it difficult to optimize customer service, product placement, and promotions, especially in physical stores.

[0184] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0185] In this invention, the server includes a means for building a platform that enables the reproduction of history, a means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, a means for providing the knowledge and management decisions of influential people in real time using smart devices, and a means for verifying and visualizing various hypotheses in real time to help predict the future. This will enable the optimization of customer service, product placement, and promotions even in physical stores.

[0186] A "platform that enables historical reenactment" is a system that recreates past events and the actions of people in a virtual space, allowing users to experience them.

[0187] "AI with individual thoughts" is artificial intelligence that learns the thought patterns of a specific person or character and acts independently based on that.

[0188] "Inheriting the specific thoughts and actions of influential people and turning them into AI" means creating an AI that learns the thinking and behavior patterns of famous historical figures and modern business leaders and imitates them.

[0189] "Interaction-enabling means" refers to interfaces and technologies that allow users to have natural conversations with artificial intelligence.

[0190] A "smart device" is an electronic device that can connect to the Internet and run various applications. Examples include smartphones and smart glasses.

[0191] "A means of providing insights and business decisions from influential people in real time" is a technology that allows users to instantly receive insights and business decisions from influential people based on their current situation.

[0192] "A means of realistically verifying and visualizing hypotheses to aid in future predictions" is a technology that simulates hypotheses and visually displays the results to aid in future predictions and strategy formulation.

[0193] To implement the present invention, the following system configuration and program are required.

[0194] First, the server builds a platform that enables historical reenactment. This platform recreates past events and the actions of people in a virtual space, allowing users to experience them. Next, the server generates AI with individual thoughts, in numbers equivalent to the world's total population, places them in the virtual space, and lets them act independently. This AI learns the thought patterns of specific people and characters and acts independently based on those patterns.

[0195] Furthermore, the server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. This AI learns and imitates the thinking and behavior patterns of famous historical figures and modern business leaders. Users can have natural conversations with this AI.

[0196] Next, we will implement a method to provide influential people's insights and business decisions in real time using smart devices such as smartphones and smart glasses. This allows users to instantly receive insights and business decisions from influential people based on their current situation.

[0197] Specifically, an application installed on the smart glasses analyzes customer behavior through the camera and sends the data to a server. The server uses the data to generate appropriate prompts and provides advice using a generative AI model. For example, if a customer picks up a specific product, the server generates a prompt such as, "Please tell us what to do if a customer picks up the product," and the AI ​​provides real-time advice such as, "Provide a detailed description of the product and share related promotional information."

[0198] The hardware used includes smart glasses (with a camera) and smartphones, and the software uses OpenAI API and OpenCV (image processing library), enabling optimization of customer service, product placement, and promotions in physical stores.

[0199] Examples of prompts include:

[0200] "What should I do if a customer picks up my product?"

[0201] In this way, store staff can tap into the knowledge of renowned business leaders and marketing experts from history to optimize customer interactions.

[0202] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0203] Step 1:

[0204] The user puts on the smart glasses and launches the application.

[0205] Input: Smart glasses camera image

[0206] Output: Real-time video data

[0207] Specific operation: The camera in the smart glasses captures video in real time, and the application acquires the video data.

[0208] Step 2:

[0209] The device analyzes camera footage and detects customer behavior.

[0210] Input: Real-time video data

[0211] Output: Customer behavior data (e.g., product pick-up behavior)

[0212] Specific operation: The device uses OpenCV to analyze video data and detect specific actions, such as a customer picking up a product.

[0213] Step 3:

[0214] The device transmits the detected behavior data to the server.

[0215] Input: Customer behavior data

[0216] Output: Send data to the server

[0217] Specific operation: The device generates an API request to send the detected customer behavior data to the server and sends it to the server.

[0218] Step 4:

[0219] The server generates a prompt sentence based on the behavioral data received.

[0220] Input: Customer behavior data

[0221] Output: Prompt statement (e.g., "What should I do if the customer picks up the item?")

[0222] Specific behavior: The server analyzes the received behavioral data and executes logic to generate appropriate prompt sentences.

[0223] Step 5:

[0224] The prompt sentence generated by the server is input into the generative AI model to obtain advice.

[0225] Input: prompt statement

[0226] Output: AI advice (e.g., "Provide a detailed description of the product and share relevant promotional information.")

[0227] Specific operation: The server uses the OpenAI API to input prompt sentences into the generative AI model and obtain advice from the AI.

[0228] Step 6:

[0229] The server transmits the obtained advice to the terminal.

[0230] Input: AI advice

[0231] Output: Sending data to the terminal

[0232] Specific operation: The server generates an API request to send the obtained advice to the terminal and sends it to the terminal.

[0233] Step 7:

[0234] The terminal displays the received advice to the user.

[0235] Input: AI advice

[0236] Output: Advice displayed on the smart glasses display

[0237] Specific operation: The terminal displays the received advice on the display of the smart glasses so that the user can check it.

[0238] In this way, users can receive real-time insights and business decisions from influential people and optimize customer service, product placement, and promotions.

[0239] Example 3

[0240] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0241] Hypothesis verification and scenario simulation are important in modern business strategies and future predictions, but experiments and verifications in the real world require a great deal of time and cost. It is also difficult to inherit the knowledge and management decisions of influential people and use them in simulations in virtual space. Furthermore, there is a lack of systems that can convert user-defined hypotheses into concrete scenarios and observe and analyze the results in real time.

[0242] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0243] In this invention, the server includes means for building a platform that enables historical reproduction, means for generating artificial intelligences with individual thoughts equivalent to the total world population, placing them in a virtual space, and making them act independently, means for inheriting the specific thoughts and actions of influential people and turning them into artificial intelligences that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for a user to set hypotheses and generate prompt statements, means for analyzing the generated prompt statements and generating specific instructions to be executed in the virtual space, means for constructing a virtual space, placing artificial intelligence agents, and executing scenarios, means for observing results, collecting data, analyzing them, and generating reports, and means for displaying the results to the user. This enables a user to set hypotheses, execute specific scenarios in the virtual space, and observe and analyze the results in real time.

[0244] The "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and observe that environment.

[0245] "Artificial intelligence" is a computer program that mimics human thought and behavior and has the ability to learn, judge, and act independently.

[0246] A "virtual space" is a computer-generated, three-dimensional digital environment, a simulated environment in which users and artificial intelligence can interact.

[0247] An "influential person" is someone whose actions and decisions have a widespread impact, such as a historical figure or a modern business leader.

[0248] "Inheriting thoughts and actions to create artificial intelligence" means collecting data on the thought patterns and actions of influential people and building artificial intelligence based on that data.

[0249] A "hypothesis" is a prediction or assumption about a certain phenomenon or event, and is a prerequisite for confirming its validity through verification and experimentation.

[0250] A "prompt sentence" is an input sentence for converting a hypothesis set by the user into a specific scenario.

[0251] A "generative AI model" is an artificial intelligence model that analyzes prompt statements and generates specific instructions to be executed in a virtual space.

[0252] A "scenario" is a hypothetical sequence of events or situations that is carried out in a virtual space.

[0253] "Means of observing results, collecting data, analyzing, and generating reports" refers to the process of observing the results of scenarios executed in virtual space in real time, collecting and analyzing that data, and creating reports to provide to users.

[0254] "Means for displaying results to the user" refers to an interface that visually displays the collected and analyzed data and allows the user to review and evaluate the results.

[0255] This invention is a system that uses artificial intelligence in a virtual space to verify hypotheses and is useful for future predictions and the formulation of business strategies. Specific embodiments of this system will be described below.

[0256] First, the user sets a hypothesis through an interface on a web browser. For example, the user inputs a hypothesis such as "Sales fluctuations when new product A is launched on the market." The terminal generates a prompt based on the hypothesis entered by the user. Specifically, the prompt generated is "Please simulate how sales will fluctuate over the next six months when new product A is launched on the market."

[0257] The server then sends the generated prompt to a generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual world. This generative AI model is built using a machine learning framework such as TensorFlow or PyTorch.

[0258] The server uses software such as Unity to create a virtual world, which is designed based on a scenario set by the user and includes stores, consumers, competitors, and more.

[0259] The server deploys artificial intelligence agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The artificial intelligence agents are controlled by machine learning models written in Python, which allows the server to simulate consumer behavior and observe fluctuations in sales.

[0260] The results of the scenario execution are observed in real time by the server, which collects sales data and consumer behavior data. This data is stored in a database. The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of a report. The report includes graphs showing sales trends and statistical information on consumer purchasing behavior.

[0261] Finally, the terminal displays the report received from the server to the user, who can then use the dashboard to view sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions.

[0262] As a concrete example, consider a simulation of the impact of a new product launch on sales. The user inputs the following prompt into the generative AI model:

[0263] "If we launch new product A into the market, please simulate how sales will fluctuate over the next six months."

[0264] The server receives this prompt and sets up a market launch scenario for new product A in the virtual space. The artificial intelligence agent simulates consumer behavior and observes fluctuations in sales. The observation results are provided to the user in the form of graphs and reports, which can be used to formulate business strategies and make future predictions. The flow of the specific processing in Example 3 will be explained using FIG. 15.

[0265] Step 1:

[0266] The user sets the hypothesis

[0267] The user opens the interface on a web browser and inputs a hypothesis. For example, they input a hypothesis such as "Sales fluctuations when new product A is released to the market." The input data is the text information of the hypothesis. The output is that the hypothesis is registered in the system.

[0268] Step 2:

[0269] The terminal generates a prompt

[0270] The terminal generates a prompt based on the hypothesis entered by the user. Specifically, it generates the prompt, "Please simulate how sales will fluctuate over the next six months if new product A is released to the market." The input data is the hypothesis set by the user, and the output is the generated prompt.

[0271] Step 3:

[0272] The server sends a prompt to the generative AI model

[0273] The server sends the prompt received from the device to the generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual space. The input data is the generated prompt, and the output is specific scenario instructions.

[0274] Step 4:

[0275] The server creates the virtual space

[0276] The server uses software such as Unity to build a virtual space. This virtual space is designed based on a scenario set by the user. The input data are specific scenario instructions, and the output is the constructed virtual space.

[0277] Step 5:

[0278] The server deploys AI agents and executes scenarios.

[0279] The server deploys AI agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The AI ​​agents are controlled by machine learning models written in Python. The input data are specific scenario instructions, and the output is the results of the executed scenario.

[0280] Step 6:

[0281] The server observes the results and collects the data.

[0282] The server observes the results of the scenario execution in real time and collects sales data and consumer behavior data. These data are stored in a database. The input data are the results of the executed scenario, and the output is the collected data.

[0283] Step 7:

[0284] The server analyzes the results and generates a report

[0285] The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of reports. The reports include graphs showing sales trends and statistical information on consumer purchasing behavior. The input data is the collected data, and the output is the generated report.

[0286] Step 8:

[0287] The device displays the results to the user

[0288] The terminal displays the report received from the server to the user. Through the dashboard, the user can check sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions. The input data is the generated report, and the output is the result displayed to the user.

[0289] (Application example 3)

[0290] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0291] Optimizing work efficiency is an important issue in modern logistics centers. However, trying out new layouts and work flows in a real environment is not easy due to the costs and risks involved. It is also difficult to verify hypotheses when formulating business strategies or making future predictions. To solve these issues, a means is needed to utilize simulations in virtual space to find optimal strategies that are efficient, low-risk, and efficient.

[0292] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for building a platform that enables historical reproduction, a means for generating AIs with individual thoughts equivalent to the total world population and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can interact, a means for simulating scenarios in a virtual space to optimize work efficiency within a logistics center, and a means for visualizing the simulation results and proposing optimal strategies. This makes it possible to evaluate the effects of new layouts and work flows in logistics centers with low risk and to formulate optimal strategies.

[0293] A "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and learn within it.

[0294] "AI with individual thinking" is artificial intelligence that imitates the thought patterns and behavior of a specific individual and makes decisions and takes action independently.

[0295] A "virtual space" is a digital environment generated by computer simulation, an area in which users can interact.

[0296] "Means for autonomous action" refers to technologies and algorithms that allow AI to make decisions and take action on its own without external instructions.

[0297] An "influential person" is an individual who has had a significant impact on society or an organization, either historically or in the present day.

[0298] "Means to inherit specific thoughts and actions, turn them into AI, and enable dialogue" refers to technology that incorporates the thoughts and behavioral patterns of influential people into AI, allowing users to interact with that AI.

[0299] "A means to realistically verify and visualize hypotheses to help predict the future" is a technology that executes scenarios set up in virtual space and visually displays the results, helping to predict the future and formulate strategies.

[0300] "A means of simulating scenarios in a virtual space to optimize work efficiency within a logistics center" is a technology that tests the layout and work flow of a logistics center in a virtual space and evaluates their effectiveness.

[0301] "Means for visualizing simulation results and proposing optimal strategies" refers to technology that visually displays the results of simulations in graphs, charts, etc., and suggests optimal actions and strategies to users.

[0302] The following system configuration will be described as an embodiment of the present invention.

[0303] System Configuration

[0304] The server includes the following means:

[0305] 1. A means of building a platform that allows historical re-enactment

[0306] 2. A method to generate AI with individual thoughts equivalent to the total population of the world, place them in a virtual space, and make them act independently.

[0307] 3. A means to inherit the specific thoughts and actions of influential people and turn them into AI, enabling dialogue

[0308] 4. A means of simulating scenarios in virtual space to optimize work efficiency within a logistics center

[0309] 5. A means to visualize simulation results and propose optimal strategies

[0310] Hardware and software used

[0311] Hardware: Servers, smartphones, computers

[0312] Software: Python, NumPy, Matplotlib, Scikit-learn

[0313] Data processing and calculation

[0314] The server will first build a platform that enables historical reenactment. This platform is a system that recreates past events and situations in a virtual space, allowing users to experience and learn from them.

[0315] The server then generates a number of AIs with individual thoughts equivalent to the total population of the world and places them in a virtual space, allowing the AIs to act autonomously and test hypotheses based on specific scenarios.

[0316] Furthermore, the specific thoughts and actions of influential people will be inherited and turned into AI, enabling dialogue, allowing users to interact with historical figures and business leaders and gain insights.

[0317] This also includes a means of simulating scenarios in a virtual space to optimize work efficiency within a logistics center, in which layouts and work flows of the logistics center are tested in a virtual space and their effectiveness is evaluated.

[0318] Finally, we use a method to visualize the simulation results and propose optimal strategies. This allows us to visually display the simulation results in graphs and charts, and to propose optimal actions and strategies to users.

[0319] Specific examples

[0320] For example, it is possible to simulate how work efficiency changes when the layout of a logistics center is changed, and it is also possible to evaluate the effects of introducing a new work flow.

[0321] Prompt Sentence Examples

[0322] "Perform simulations to optimize your distribution center layout and maximize operational efficiency. Set up scenarios involving new layouts and workflow changes and visualize the results."

[0323] In this way, simulation applications can be developed to help optimize logistics centers and then tested in real environments with low risk.

[0324] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0325] Step 1:

[0326] The server builds a platform that enables historical reconstruction. As input, it receives data on past events and situations and generates a virtual space based on this data. As output, it provides a virtual space where users can experience and learn. This virtual space includes an interface for users to interact with.

[0327] Step 2:

[0328] The server generates AIs with individual thoughts, in numbers equivalent to the total world population, and places them in a virtual space. As input, it receives each AI's thought patterns and behavioral data, and generates an AI model based on this. As output, it places an AI that can act independently in the virtual space. This makes it possible for the AI ​​to act based on specific scenarios and verify hypotheses.

[0329] Step 3:

[0330] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. As input, it receives the influential person's thoughts and actions data and generates an AI model based on this. As output, it provides AI with which the user can interact. This AI imitates the knowledge and judgment of the influential person and provides useful information to the user.

[0331] Step 4:

[0332] The server simulates scenarios for optimizing work efficiency within a logistics center in a virtual space. It receives data on the layout and work flow of the logistics center as input and runs the simulation based on this data. It provides the simulation results as output. These results include data showing changes in work efficiency and the effects of optimization.

[0333] Step 5:

[0334] The server visualizes the simulation results and proposes the optimal strategy. It receives the simulation result data as input and generates graphs and charts based on this. As output, it provides a visual display of the simulation results and a proposal for the optimal strategy. Users can then use this to formulate strategies for their actual logistics centers.

[0335] In this way, through a series of processes, the server can run simulations that are useful for optimizing the logistics center and provide the results to the user.

[0336] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0337] "Example 1"

[0338] One embodiment of the present invention is a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the AI's behavior based on those emotions. Specifically, when the user is feeling joy, the AI ​​shares that joy and acts to make the interaction with the user more enjoyable. Also, when the user is feeling sad, the AI ​​understands that sadness and acts to comfort the user.

[0339] "Example 2"

[0340] Another possible system is to use an emotion engine to verify and visualize hypotheses based on user emotions. Specifically, when a user feels joy, a hypothesis can be formulated about what that joy comes from and what factors cause it, and then that hypothesis can be verified. This will enable a deeper understanding of the user's emotions and enable more appropriate responses to those emotions.

[0341] "Example 3"

[0342] Furthermore, a system that uses an emotion engine to adjust AI behavior based on the user's emotions is also conceivable. Specifically, when a user feels angry, a hypothesis can be made as to what the source of that anger is and what factors are causing it, and that hypothesis can be verified. This will enable a deeper understanding of the user's emotions and a more appropriate response to those emotions.

[0343] The processing flow of each embodiment will be described below.

[0344] "Example 1"

[0345] Step 1: The emotion engine recognizes the user's emotion.

[0346] Step 2: Adjust the AI's behavior based on the recognized emotions. Specifically, when the user feels joy, the AI ​​will share that joy and act in a way that makes the interaction with the user more enjoyable.

[0347] Step 3: When the user is feeling sad, the AI ​​understands that sadness and takes action to comfort the user.

[0348] "Example 2"

[0349] Step 1: The emotion engine recognizes the user's emotion.

[0350] Step 2: Create a hypothesis based on the recognized emotion. Specifically, when a user feels joy, create a hypothesis about what that joy comes from and what elements cause it.

[0351] Step 3: Test your hypotheses. This will help you better understand your users' emotions and better respond to them.

[0352] "Example 3"

[0353] Step 1: The emotion engine recognizes the user's emotion.

[0354] Step 2: Create a hypothesis based on the recognized emotion. Specifically, when a user feels angry, create a hypothesis about what the anger comes from and what factors are causing the anger.

[0355] Step 3: Test your hypotheses. This will help you better understand your users' emotions and better respond to them.

[0356] Example 1

[0357] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0358] Conventional historical reenactment systems simply reproduce past events and the actions of people, making it difficult to provide an interactive experience that responds to the user's emotions. Furthermore, there are only a limited number of systems that can provide appropriate information when a user asks about a specific historical event or person. Furthermore, there is a lack of systems that can inherit the thoughts and actions of influential people and use them to predict the future or formulate business strategies.

[0359] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0360] In this invention, the server includes a means for building a platform that enables historical reproduction; a means for generating AIs with individual thoughts equivalent to the total world population, placing them in a virtual space, and enabling them to act independently; a means for inheriting the specific thoughts and actions of influential people to turn them into AIs and enable dialogue; a means for realistically verifying and visualizing various hypotheses to help predict the future; a means for recognizing user emotions and adjusting the AI's behavior based on those emotions; and a means for the AI ​​to provide appropriate information based on prompts entered by the user. This makes it possible to provide an interactive experience that responds to the user's emotions and provides appropriate information about specific historical events or people. Furthermore, inheriting the thoughts and actions of influential people can be useful for predicting the future and formulating business strategies.

[0361] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience historical events and people within it.

[0362] "Artificial intelligence" refers to a program that has individual thoughts and acts independently, and is capable of interacting with users and carrying out specific tasks.

[0363] A "virtual space" is a three-dimensional computer-generated digital environment in which users can interact.

[0364] An "influential person" is someone who has played an important role in history or in the present day and whose actions and thoughts have had a major impact on society and the economy.

[0365] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to identify their emotional state.

[0366] A "prompt sentence" is a question or instruction sentence that a user inputs to a system, and is input data that the system uses to generate an appropriate response.

[0367] "Future prediction" is a technique for predicting future events and situations based on past and present data.

[0368] "Hypothesis verification and visualization" is a technique that formulates a hypothesis, verifies it through simulation and data analysis, and visually displays the results.

[0369] This invention is a system that builds a platform that enables historical reproduction and allows users to interactively experience historical events and people. Specific embodiments of this system are described below.

[0370] Hardware and software used

[0371] Hardware: High-performance servers, user devices (PCs, smartphones)

[0372] Software: emotion engine, generative AI model, database management system (DBMS), game engine (Unity or Unreal Engine)

[0373] System configuration

[0374] 1. The server collects historical data from the past to the present and stores it in a database. This data includes historical events, demographics, cultural background, etc. Specifically, it retrieves the data using an API and stores it in a DBMS such as MySQL or PostgreSQL.

[0375] 2. The server generates a virtual space along a timeline based on the stored historical data. It uses a game engine such as Unity or Unreal Engine to build the 3D virtual space. It analyzes the data and generates appropriate models to recreate the geographical layout, historical buildings, people, and other elements within the virtual space.

[0376] 3. The server places AIs in the virtual space in numbers equivalent to the total world population. These AIs have individual thoughts and act independently using generative AI models (such as GPT-4). Initial settings are made for each AI, and historical background and cultural information is input.

[0377] 4. When a user accesses the system, the device activates the emotion engine, which analyzes the user's facial expressions and voice to recognize emotions. It uses a camera and microphone to capture the user's facial expressions and tone of voice and sends the analysis results to the server.

[0378] 5. The server adjusts the behavior of the AI ​​in the virtual space based on the user's emotional data obtained from the emotion engine. If the user is feeling happy, the AI ​​will share that joy and act to make the interaction with the user more enjoyable. If the user is feeling sad, the AI ​​will understand that sadness and act to comfort the user.

[0379] 6. The user asks the system a question about a particular historical event or person by entering a prompt sentence, for example, "Tell me about World War II."

[0380] 7. The server analyzes the user's prompt and uses artificial intelligence to provide appropriate information. The artificial intelligence provides detailed information in response to the user's question, improving the user's learning experience through dialogue.

[0381] Specific examples

[0382] For example, a user might input a prompt such as, "I would like to know more about Renaissance art." The device analyzes the user's facial expressions and tone of voice and recognizes that the user is excited. Based on the emotional data, the server instructs the AI ​​in the virtual space to share the user's excitement and make the conversation more interesting. The AI ​​then provides detailed information about Renaissance art and answers the user's questions. For example, it might explain, "Leonardo da Vinci is a representative painter of the Renaissance. One of his most famous works is the Mona Lisa."

[0383] In this way, users can have an emotionally responsive and interactive learning experience.

[0384] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0385] Step 1:

[0386] The server collects historical data from the past to the present and stores it in a database. Specifically, it uses an API to obtain data such as historical events, demographics, and cultural background. The input is data from the internet and databases, and the output is stored in a database management system (DBMS). For example, DBMSs such as MySQL or PostgreSQL are used.

[0387] Step 2:

[0388] The server generates a virtual space along a timeline based on the stored historical data. Specifically, it uses game engines such as Unity or Unreal Engine to build a 3D virtual space. The input is historical data stored in a database, and the output is a generated virtual space. The data is analyzed and appropriate models are generated to recreate the geographical layout, historical buildings, people, and other elements within the virtual space.

[0389] Step 3:

[0390] The server places a number of AIs within the virtual space equivalent to the total world population. These AIs have individual thoughts and act independently using a generative AI model (such as GPT-4). The inputs are the generative AI model and historical data, and the output is the AIs placed within the virtual space. Initial settings are made for each AI, and historical background and cultural information are input.

[0391] Step 4:

[0392] When a user accesses the system, the device starts the emotion engine. The emotion engine analyzes the user's facial expressions and voice to recognize emotions. The input is the user's facial expressions and voice, and the output is analyzed emotion data. Specifically, the system uses a camera and microphone to capture the user's facial expressions and tone of voice, and sends the analysis results to the server.

[0393] Step 5:

[0394] The server adjusts the behavior of the AI ​​in the virtual space based on the user's emotional data obtained from the emotion engine. The input is the emotional data, and the output is the adjusted behavior of the AI. If the user is feeling happy, the AI ​​will share that joy and act to make the interaction with the user more enjoyable. If the user is feeling sad, the AI ​​will understand that sadness and act to comfort the user.

[0395] Step 6:

[0396] Users ask questions about particular historical events or people by entering prompts into the system. The input is the prompt entered by the user, and the output is the prompt sent to the server. For example, "Tell me about World War II."

[0397] Step 7:

[0398] The server uses artificial intelligence to analyze the user's prompt and provide appropriate information. The input is the prompt and the generative AI model, and the output is the information provided to the user. The AI ​​provides detailed information in response to the user's question, improving the user's learning experience through dialogue. For example, it might explain, "Leonardo da Vinci is a representative painter of the Renaissance period. One of his most famous works is the Mona Lisa."

[0399] (Application example 1)

[0400] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] Conventional history learning systems and virtual space systems have had the problem of making it difficult for users to empathize with or gain a deep understanding of historical events and people when learning about them. In addition, there has been a lack of systems that allow interactive dialogue based on the user's emotions, which has limited the learning effect.

[0402] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for building a platform that enables historical reproduction; means for generating AIs with individual thoughts equivalent to the total world population, placing them in a virtual space, and allowing them to act independently; means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue; means for realistically verifying and visualizing various hypotheses to help predict the future; means for recognizing user emotions and adjusting the AI's behavior based on those emotions; and means for the user to interact with historical events and people via their smartphone and deepen their learning through an emotion engine. This allows the user to learn more about historical events and people while gaining emotional empathy.

[0403] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present.

[0404] "AI with individual thoughts" is artificial intelligence that has its own unique thought patterns and acts independently.

[0405] A "virtual space" is a digital environment generated by a computer that users can experience interactively.

[0406] An "influential person" is someone who has played an important role in history or in the present day, and whose thoughts and actions have a great influence on others.

[0407] An "emotion engine" is a technology that recognizes the user's emotions and adjusts the system's behavior based on those emotions.

[0408] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[0409] "Dialogue" is two-way communication between a user and a system (or AI).

[0410] "Deepening learning" refers to users gaining a deeper understanding and mastering specific knowledge or skills.

[0411] "Hypothesis verification and visualization" is the process of actually testing a hypothesis and visually displaying the results.

[0412] "Future forecasting" refers to predicting future events or situations based on current data and trends.

[0413] The system for implementing this invention is configured as follows: The server builds a platform that enables the reproduction of history, generates AIs with individual thoughts equivalent to the total world population, and places them in a virtual space. These AIs act independently, inheriting the specific thoughts and actions of influential people and enabling dialogue. In addition, various hypotheses can be verified and visualized in real time, which can be used to predict the future.

[0414] Furthermore, it is equipped with an emotion engine that recognizes the user's emotions and adjusts the AI's behavior based on those emotions. Users can interact with historical events and people through their smartphones and deepen their learning through the emotion engine.

[0415] Specifically, the server was developed using Python and provides a smartphone application. This application receives user emotions as input and adjusts the behavior of historical AI characters accordingly. When a user inputs an emotion such as "happy" or "sad," the AI ​​character responds accordingly. It also provides users with randomly selected historical events.

[0416] The hardware used is a smartphone, and the software uses Python. Data processing generates responses from AI characters based on user emotional data, and data calculation randomly selects historical events.

[0417] As a concrete example, the prompt text when the user enters "happy" is shown below.

[0418] python

[0419] Prompt Sentence Examples

[0420] user_emotion = "happy"

[0421] historical_figure = HistoricalAI("Historical Figure", 1732, 1799)

[0422] response = historical_figure.respond_to_emotion(user_emotion)

[0423] event = historical_figure.historical_event()

[0424] print(response)

[0425] print(f"Historical Event: {event}")

[0426] When you run this prompt, you will get the following output:

[0427] Historical Figure is happy to see you happy!

[0428] Historical Event: The signing of the Declaration of Independence in 1776.

[0429] In this way, users can learn about historical events while sharing emotions with historical AI characters.

[0430] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0431] Step 1:

[0432] A user starts the application using a smartphone. The user selects their emotion on the emotion input screen and inputs an emotion such as "happy" or "sad." The input data is sent to the emotion engine.

[0433] Step 2:

[0434] The server uses an emotion engine to analyze the emotion data entered by the user. The emotion engine classifies the user's emotions into categories such as "happy" or "sad," and generates data to adjust the AI ​​character's behavior based on the results. The input is the user's emotion data, and the output is behavioral instruction data for the AI ​​character.

[0435] Step 3:

[0436] The server updates the AI ​​character's emotional state based on the AI ​​character's behavior instruction data. Specifically, it sets the AI ​​character's emotional attribute to "happy" or "sad" and generates a response message accordingly. The input is the behavior instruction data, and the output is the response message.

[0437] Step 4:

[0438] The server randomly selects an event from the historical event database. The selected event is prepared to be provided to the user. The input is unconditional, and the output is a randomly selected historical event.

[0439] Step 5:

[0440] The server combines the generated response message with a randomly selected historical event to generate data to send to the user. The input is the response message and the historical event, and the output is the final message sent to the user.

[0441] Step 6:

[0442] The device (smartphone) displays the final message received from the server to the user. The user can view the AI ​​character's response message and historical events, gaining emotional empathy and deepening their learning. The input is the final message from the server, and the output is the information displayed to the user.

[0443] Example 2

[0444] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0445] In order to inherit modern management and historical knowledge and utilize it for future decision-making, it is necessary to effectively learn and emulate the thinking and behavioral patterns of influential people. It is also necessary to gain a deeper understanding and take appropriate action through the verification and visualization of hypotheses based on user emotions. However, there is no system yet in place to efficiently and accurately realize these processes.

[0446] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting data on influential people, means for preprocessing the collected data, means for training a generative AI model using the preprocessed data, means for generating an AI that imitates the thoughts and actions of influential people using the trained model, means for collecting user emotional data, means for analyzing the collected emotional data and identifying the user's emotional state, means for formulating hypotheses based on the user's emotional state and verifying the hypotheses, and means for visualizing the results of the hypothesis verification. This makes it possible to inherit the knowledge and management decisions of influential people and verify and visualize hypotheses based on user emotions.

[0447] An "influential person" is someone who plays an important role in society or an organization and whose thoughts and actions have a great influence on others.

[0448] "Data collection" is the process of gathering information needed for a specific purpose from various sources.

[0449] "Preprocessing" is a series of operations used to convert collected data into a format suitable for analysis and learning.

[0450] A "generative AI model" is an artificial intelligence model that generates new information and predictions based on given data.

[0451] "Learning" is the process by which an AI model finds patterns and rules in the data it is given and uses them to improve its performance.

[0452] "Imitation" means reproducing the behavior and thought patterns of a particular person or system.

[0453] "Emotion data" is information that indicates the user's emotional state, and is obtained from facial expressions, voice, text, and the like.

[0454] "Analysis" is the process of examining collected data in detail to understand its meaning and patterns.

[0455] A "hypothesis" is a prediction or premise made to explain an observed phenomenon.

[0456] "Verification" is the process of confirming whether a hypothesis is correct.

[0457] "Visualization" is the representation of data or information in a visual format such as a graph or chart.

[0458] This invention includes a system that learns the thinking and behavior patterns of influential people and generates AI that imitates them, and a system that verifies and visualizes hypotheses based on user emotion data. Specific embodiments of this system are described below.

[0459] Learning and imitating the thinking and behavior patterns of influential people

[0460] Data collection

[0461] The server collects data on influential people, specifically from books, interviews, lecture notes, and social media posts by business leaders and historical figures. The software used is web scraping tools (e.g., BeautifulSoup, Scrapy) and APIs (e.g., Twitter API).

[0462] Data Preprocessing

[0463] The server preprocesses the collected data, specifically cleaning the text, tokenizing it, removing stop words, etc. The software used is a natural language processing library (e.g., NLTK, spaCy).

[0464] Model training

[0465] The server uses the preprocessed data to train a generative AI model (e.g., GPT-4). This model mimics the thought and behavior patterns of influential people. The hardware used is a server equipped with a high-performance GPU (e.g., NVIDIA Tesla V100).

[0466] AI generation

[0467] The server uses the trained model to generate AI that mimics the thoughts and actions of influential people. The generated AI is deployed as an API, making it accessible to users and devices.

[0468] Hypothesis verification and visualization using emotion engine

[0469] Collecting user emotion data

[0470] The device collects the user's emotional data. Specifically, it analyzes the user's facial expressions, voice, text input, etc. The hardware used is a camera and microphone, and the software is an emotion analysis tool (e.g., Microsoft® Azure® Emotion API).

[0471] Emotional Data Analysis

[0472] The server analyzes the collected emotion data and identifies the user's emotional state using machine learning libraries (e.g., TensorFlow, PyTorch).

[0473] Hypothesis formulation and verification

[0474] The server generates hypotheses based on the user's emotional state. For example, if the user is feeling happy, it identifies the cause of that happiness. The server analyzes the user's emotional data and related contextual information (e.g., the movie scene the user is watching, the music the user is listening to, etc.) to generate hypotheses about the cause of the happiness. It then performs additional data collection and analysis to validate these hypotheses.

[0475] visualization

[0476] The server visualizes the hypothesis verification results by generating graphs and charts and presenting them to the user. The software used is a data visualization tool (e.g., Tableau, Matplotlib).

[0477] Examples and prompts

[0478] Specific examples

[0479] AI-generated managers:

[0480] The server collects lecture notes and interviews of a certain manager and generates an AI that learns his thought patterns. When a user asks a question about management, this AI provides answers that sound like the manager would.

[0481] Using the Emotion Engine:

[0482] The device uses a camera to analyze the user's facial expressions while watching a movie and identifies when the user feels joy at a particular scene. The server then analyzes the elements of that scene (music, characters, storyline, etc.) and hypothesizes the cause of the joy.

[0483] Prompt Sentence Examples

[0484] AI-generated managers:

[0485] "Please generate an AI that has learned the thought patterns of a certain CEO. Use his lecture transcripts and interviews as data."

[0486] Using the Emotion Engine:

[0487] "Collect emotional data while users are watching a movie, analyze the elements of the scene that evoke pleasure, and develop a hypothesis to identify the source of pleasure."

[0488] The above is a specific embodiment for carrying out the present invention.

[0489] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0490] Step 1: Data collection

[0491] The server collects data on influential people. Specifically, it targets books, interviews, lecture notes, and social media posts by business leaders and historical figures. The software used is a web scraping tool (e.g., BeautifulSoup, Scrapy) or an API (e.g., Twitter API). The input is the name of the person in question and related keywords, and the output is the collected text data.

[0492] Step 2: Data Preprocessing

[0493] The server preprocesses the collected data. Specifically, it performs text cleaning, tokenization, and stop word removal. The software used is a natural language processing library (e.g., NLTK, spaCy). The input is the collected text data, and the output is the preprocessed, clean text data.

[0494] Step 3: Training the model

[0495] The server uses the preprocessed data to train a generative AI model (e.g., GPT-4). This model mimics the thought and behavior patterns of influential people. The hardware used is a server equipped with a high-performance GPU (e.g., NVIDIA Tesla V100). The input is preprocessed text data, and the output is a trained generative AI model.

[0496] Step 4: Generate AI

[0497] The server uses the trained model to generate AI that mimics the thoughts and actions of influential people. The generated AI is deployed as an API, making it accessible to users and devices. The input is the trained generative AI model, and the output is the deployed AI service.

[0498] Step 5: Collecting user emotion data

[0499] The device collects the user's emotional data. Specifically, it analyzes the user's facial expressions, voice, text input, etc. The hardware used is a camera and microphone, and the software is an emotion analysis tool (e.g., Microsoft Azure Emotion API). The input is the user's real-time data (facial expressions, voice, text), and the output is analyzed emotional data.

[0500] Step 6: Analyze the sentiment data

[0501] The server analyzes the collected emotion data and identifies the user's emotional state. The software used is a machine learning library (e.g., TensorFlow, PyTorch). The input is the analyzed emotion data, and the output is the identified emotional state (e.g., joy, sadness, anger, etc.).

[0502] Step 7: Hypothesis formulation and testing

[0503] The server generates hypotheses based on the user's emotional state. For example, if the user is feeling happy, it identifies the cause of that happiness. The server analyzes the user's emotional data and related contextual information (e.g., the movie scene the user is watching, the music the user is listening to, etc.) to generate hypotheses about the cause of the happiness. It then performs additional data collection and analysis to verify this hypothesis. The input is the identified emotional state and related contextual information, and the output is the verified hypothesis.

[0504] Step 8: Visualization

[0505] The server visualizes the results of the hypothesis verification. Specifically, it generates graphs and charts and presents them to the user. The software used is a data visualization tool (e.g., Tableau, Matplotlib). The input is the verified hypothesis, and the output is the visualized data (graphs, charts).

[0506] (Application example 2)

[0507] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0508] In today's business environment, it is difficult to inherit the knowledge and management decisions of influential business leaders and historical figures. It is also difficult to recognize customer sentiment in real time and provide optimal advice based on that sentiment. Furthermore, the lack of means to display management advice in real time using smart devices hinders rapid decision-making on the ground. A system that can solve these issues is needed.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0510] In this invention, the server includes means for building a platform that enables the reproduction of history, means for generating AIs with individual thoughts equivalent to the total population of the world, placing them in a virtual space, and making them act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for recognizing users' emotions and providing optimal advice based on those emotions, and means for displaying management advice in real time using a smart device.This makes it possible to inherit the knowledge and management decisions of influential people and provide optimal advice based on customer emotions in real time.

[0511] A "platform that enables historical reenactment" is a system that recreates past events and the actions of people in a virtual space, allowing users to experience them.

[0512] "AI with individual thoughts" refers to artificial intelligence that has its own individual personality and thought patterns and acts independently.

[0513] "Inheriting the specific thoughts and actions of influential people and turning them into AI" means creating an AI that learns the thought patterns and actions of historical figures and famous business leaders and imitates them.

[0514] "Means to realistically verify and visualize hypotheses to help predict the future" refers to a technology that formulates hypotheses, verifies them through simulations and data analysis, and visually displays the results to help predict the future.

[0515] "Means for recognizing a user's emotions and providing optimal advice based on those emotions" refers to a system that analyzes emotions from a user's facial expressions and voice and generates appropriate advice based on those emotions.

[0516] "Means for displaying management advice in real time using a smart device" refers to technology that displays management advice in real time using devices such as smart glasses or smartphones.

[0517] The following system configuration is used as an embodiment of the present invention.

[0518] System Configuration

[0519] 1. Server:

[0520] The server will build a platform that will enable the re-creation of history, and will generate AIs with individual thoughts equivalent to the total population of the world, placing them in a virtual space.

[0521] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue.

[0522] The server will realistically verify and visualize various hypotheses, helping to predict the future.

[0523] The server recognizes the user's emotions and provides optimal advice based on those emotions.

[0524] The server displays management advice in real time using smart devices.

[0525] Hardware and software used

[0526] Hardware:

[0527] Smart glasses (with camera)

[0528] Server (with high-performance computing power)

[0529] software:

[0530] OpenAI API

[0531] Emotion Recognition Library

[0532] Data processing and calculation

[0533] 1. User Emotion Recognition:

[0534] Images of customers taken with the smart glasses camera are analyzed using the Emotion Recognition library to recognize the customer's emotions.

[0535] 2. Prompt generation:

[0536] Based on the perceived emotions and store scenarios, prompts are created to generate advice from the perspective of influential business owners.

[0537] 3. Advice Generation:

[0538] Uses the OpenAI API to generate management advice based on the generated prompts.

[0539] 4. Advice display:

[0540] The generated advice is displayed on the display of the smart glasses.

[0541] Specific examples

[0542] scenario

[0543] Scenario: New product promotion

[0544] Customer Emotion: Delight

[0545] Prompt Sentence Examples

[0546] Customers' emotions are delighted. Please provide the best advice from the perspective of an influential business executive on promoting new products.

[0547] This system makes it possible to inherit the knowledge and management decisions of influential people and provide optimal advice based on customer emotions in real time.

[0548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0549] Step 1:

[0550] User Emotion Recognition

[0551] Input: An image of the customer taken by the camera in the smart glasses

[0552] Processing: The device (smart glasses) uses the Emotion Recognition library to analyze the customer's image and recognize their emotions. Specifically, it extracts facial features in the image and classifies emotions such as joy, sadness, and anger.

[0553] Output: Perceived customer emotion (e.g., joy)

[0554] Step 2:

[0555] Prompt Generation

[0556] Input: Perceived customer sentiment (output of step 1) and store scenarios (e.g., new product promotions)

[0557] Processing: Based on the input emotions and scenarios, the server creates prompts to generate advice from the perspective of influential business leaders. Specifically, it generates sentences that combine emotions and scenarios.

[0558] Output: Generated prompt (e.g., "The customer's emotion is joy. Please provide the best advice from the perspective of an influential executive regarding the promotion of a new product.")

[0559] Step 3:

[0560] Advice Generation

[0561] Input: Generated prompt statement (output of step 2)

[0562] Processing: The server uses the OpenAI API to generate management advice based on the prompt sentence. Specifically, the prompt sentence is sent to the API, and the generative AI model returns appropriate advice.

[0563] Output: Generated management advice (e.g., "When promoting a new product, it is effective to offer special discounts to elicit customer delight.")

[0564] Step 4:

[0565] Advice display

[0566] Input: Generated management advice (output of Step 3)

[0567] Processing: The terminal (smart glasses) displays the generated management advice on the display. Specifically, the text of the advice is displayed on the display of the smart glasses in real time.

[0568] Output: Business advice displayed on the smart glasses display

[0569] In this way, users can receive optimal management advice based on customer sentiment in real time.

[0570] Example 3

[0571] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0572] In conventional systems, it was difficult to take user emotions into account when verifying hypotheses or making future predictions, and it was also difficult to visualize simulation results in real time in a virtual space. Furthermore, because scenario generation using a generative AI model and emotion analysis using an emotion engine were not integrated, there was an issue of not being able to respond appropriately based on user emotions.

[0573] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0574] In this invention, the server includes a means for a user to input a specific hypothesis, a means for generating a scenario based on the hypothesis using a generative AI model, a means for executing the scenario using virtual space simulation software, a means for visualizing the simulation results, a means for using an emotion engine to input and analyze the user's emotions, and a means for adjusting the behavior of the AI ​​based on the emotion analysis results. This allows the user's hypothesis to be verified in real time and used to predict the future. It also enables appropriate responses based on the user's emotions.

[0575] A "platform" is an underlying system or environment built to achieve a specific purpose.

[0576] "Artificial intelligence" refers to computer programs that mimic human intelligence and can learn, reason, and solve problems.

[0577] A "virtual space" is a three-dimensional simulated environment generated by a computer.

[0578] A "generative AI model" is a machine learning model trained to perform tasks such as natural language processing or image generation.

[0579] A "scenario" is a simulation of a series of events or circumstances based on a particular hypothesis.

[0580] "Simulation" is a technology that simulates and reproduces real-world phenomena and processes.

[0581] "Visualization" is a technique that makes data and information easier to understand by visually representing them.

[0582] An "emotion engine" is software that analyzes a user's emotions and responds appropriately based on the results.

[0583] "Sentiment analysis" is the process of identifying emotions from user input and behavior and analyzing the causes and effects of those emotions.

[0584] "Behavioral adjustment" is the process of changing the behavior of artificial intelligence based on the analysis results and taking appropriate action.

[0585] This invention is a system in which an AI acts autonomously in a virtual space, setting scenarios based on specific hypotheses and observing the results to obtain information useful for formulating business strategies and predicting the future. It also has a function to adjust the AI's behavior based on the user's emotions using an emotion engine.

[0586] Hardware and software used

[0587] Hardware: High-performance server (e.g., GPU-equipped server)

[0588] software:

[0589] Virtual space simulation software (e.g. Unity, Unreal Engine)

[0590] Emotion engines (e.g., Affectiva, IBM Watson® Tone Analyzer)

[0591] Generative AI models (e.g., GPT-4)

[0592] Explanation of program processing

[0593] 1. Enter your hypothesis

[0594] The user inputs a specific hypothesis into the system, for example, "the impact of launching a new product on sales."

[0595] The terminal receives the user's input and sends it to the server.

[0596] 2. Scenario generation

[0597] Based on the hypotheses received by the server, a scenario is generated using a generative AI model (e.g., GPT-4).

[0598] The server sends the generated scenario to the virtual space simulation software (e.g., Unity).

[0599] As a specific operation, the server generates a scenario in which a new product is introduced to the market and consumer reactions are observed.

[0600] 3. Running a simulation in virtual space

[0601] The server starts the virtual space simulation software and executes the generated scenario.

[0602] The server controls the AI ​​characters to act independently and monitors the progress of the scenario.

[0603] Specifically, the system simulates the process of a new product being released to the market in a virtual space and consumers purchasing the product.

[0604] 4. Visualizing the results

[0605] The server aggregates the simulation results and displays them using a visualization tool.

[0606] The terminal displays the visualized results to the user.

[0607] Specific actions include displaying sales fluctuation graphs and consumer feedback.

[0608] 5. Emotion Input and Analysis

[0609] The user inputs their feelings about the simulation results. For example, if they feel "anger," they input that emotion.

[0610] The device receives the user's emotion input and transmits it to the server.

[0611] The server uses an emotion engine (e.g., Affectiva) to analyze the user's emotions.

[0612] Specifically, the user inputs "anger" and the emotion engine analyzes the cause of that anger.

[0613] 6. Emotion-based behavioral regulation

[0614] The server adjusts the behavior of the artificial intelligence based on the analysis results of the emotion engine.

[0615] The server generates a new scenario and sends it to the virtual space simulation software.

[0616] Specifically, the cause of the user's anger is identified as "the price of the new product is too high," and a new scenario is generated to adjust the price.

[0617] Specific examples

[0618] Hypothesis input: The user inputs "the impact of launching a new product on sales."

[0619] Scenario generation: The server generates a scenario that involves "launching a new product on the market and observing consumer reactions."

[0620] Simulation execution: A simulation is performed in a virtual space to see how a new product is launched on the market and how consumers purchase it.

[0621] Visualize results: Display sales fluctuation graphs and consumer feedback.

[0622] Emotion input and analysis: The user inputs "anger" and the emotion engine analyzes the cause.

[0623] Behavioral adjustment: The cause of the user's anger is identified as "the price of the new product is too high," and a new scenario is generated in which the price is adjusted.

[0624] Prompt Sentence Examples

[0625] "Simulate the impact of introducing a new product to the market on sales."

[0626] "Analyze the cause of the user's anger and generate a scenario to resolve that cause."

[0627] This system allows users to realistically verify hypotheses and use them to predict the future. Furthermore, by using an emotion engine, appropriate responses based on the user's emotions become possible. The flow of the identification process in Example 3 will be described with reference to FIG. 21.

[0628] Step 1:

[0629] Entering a hypothesis

[0630] The user inputs a specific hypothesis into the system, for example, "the impact of launching a new product on sales."

[0631] The terminal receives the user's input and sends it to the server.

[0632] Input: User-entered hypotheses

[0633] Output: Hypothetical data sent to the server

[0634] Step 2:

[0635] Scenario generation

[0636] Based on the hypotheses received by the server, a scenario is generated using a generative AI model (e.g., GPT-4).

[0637] The server sends the generated scenario to the virtual space simulation software (e.g., Unity).

[0638] Input: Hypothetical data

[0639] Data processing: Generate scenarios using generative AI models

[0640] Output: Generated scenario data

[0641] Step 3:

[0642] Running a simulation in virtual space

[0643] The server starts the virtual space simulation software and executes the generated scenario.

[0644] The server controls the AI ​​characters to act independently and monitors the progress of the scenario.

[0645] Input: Generated scenario data

[0646] Data calculation: Execute scenarios in virtual space and simulate the actions of AI characters

[0647] Output: Simulation result data

[0648] Step 4:

[0649] Visualizing the results

[0650] The server aggregates the simulation results and displays them using a visualization tool.

[0651] The terminal displays the visualized results to the user.

[0652] Input: Simulation result data

[0653] Data processing: Processing the resulting data with a visualization tool

[0654] Output: Visualized results (e.g., sales fluctuation graphs, consumer feedback)

[0655] Step 5:

[0656] Emotion input and analysis

[0657] The user inputs their feelings about the simulation results. For example, if they feel "anger," they input that emotion.

[0658] The device receives the user's emotion input and transmits it to the server.

[0659] The server uses an emotion engine (e.g., Affectiva) to analyze the user's emotions.

[0660] Input: User emotion data

[0661] Data Calculation: Emotion Analysis Using an Emotion Engine

[0662] Output: Emotion analysis results

[0663] Step 6:

[0664] Emotion-based behavioral regulation

[0665] The server adjusts the behavior of the artificial intelligence based on the analysis results of the emotion engine.

[0666] The server generates a new scenario and sends it to the virtual space simulation software.

[0667] Input: Sentiment analysis results

[0668] Data processing: Generative AI models are used to generate new scenarios

[0669] Output: Adjusted scenario data

[0670] In this way, the user, terminal, and server work together at each step to create a system that verifies hypotheses and predicts the future.

[0671] (Application example 3)

[0672] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0673] Conventional AI systems in virtual spaces have difficulty responding in real time based on user emotions, and lack specific methods for improving the shopping experience, especially in physical stores. Furthermore, when formulating business strategies or making future predictions, scenarios that take user emotions into account were not set, so more accurate predictions were needed.

[0674] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for building a platform that enables historical reproduction, means for generating AIs with individual thoughts equivalent to the total world population and placing them in a virtual space to allow them to act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, and means for analyzing user emotions in real time and providing optimal product suggestions and services based on those emotions. This enables real-time responses that take user emotions into consideration, improving the shopping experience in physical stores and enabling the formulation of more accurate management strategies and future predictions.

[0675] A "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and learn within it.

[0676] "AI with individual thoughts" refers to artificial intelligence that has its own individual personality and thought patterns and acts independently.

[0677] A "virtual space" is a three-dimensional computer-generated digital environment in which users can interact.

[0678] An "influential person" is someone who has played an important role in history or the modern day and has influenced many people.

[0679] "Inheriting specific thoughts and actions to create AI" means incorporating the thought patterns and behavioral characteristics of a specific person into artificial intelligence, and generating AI that behaves like that person.

[0680] "Means enabling dialogue" refers to a function that allows users and AI to communicate using natural language.

[0681] "Realistic verification and visualization of hypotheses" means executing a scenario based on a specific hypothesis in a virtual space and visually displaying the results.

[0682] "Means for predicting the future" are methods for predicting future events and situations based on the results of hypothesis verification.

[0683] "Analyzing user emotions in real time" means analyzing the user's facial expressions and behavior in real time to identify their emotional state.

[0684] "Means for providing optimal product suggestions and services" refers to a function that selects and suggests appropriate products and services based on the user's emotional state.

[0685] The following system configuration will be described as an embodiment of the present invention.

[0686] System Configuration

[0687] 1. Hardware Configuration

[0688] Server: A server with high-performance computing power is required to train the AI ​​model and manage the virtual space.

[0689] Device: A device such as a smartphone or tablet is required. It is desirable for these devices to be equipped with a camera and microphone.

[0690] Network: A high-speed internet connection is required to connect the server and your device.

[0691] 2. Software Configuration

[0692] AI Model: A generative AI model is required for emotion recognition and behavior prediction, specifically using a deep learning framework such as Keras or TensorFlow.

[0693] Virtual space management software: Build virtual spaces using game engines such as Unity and Unreal Engine.

[0694] Emotion analysis software: OpenCV is used to detect faces from camera footage and input them into an emotion recognition model.

[0695] REST API: Use the API to obtain product and service information.

[0696] Processing flow

[0697] 1. Server Processing

[0698] The server will manage the virtual space and train the AI ​​models. Specifically, it will build a platform that enables historical reenactment and generate AIs with individual thoughts, equivalent to the total world population, and place them in the virtual space.

[0699] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue.

[0700] 2. Terminal Processing

[0701] The device captures camera footage and inputs it into an emotion recognition model to analyze the user's emotions in real time.

[0702] Based on the emotion recognition results, the device retrieves optimal product suggestions and service information via a REST API and displays them to the user.

[0703] 3. User Operation

[0704] Users scan their face using their smartphone camera, which allows the device to analyze their emotions and suggest appropriate products and services.

[0705] Specific examples

[0706] For example, when a user scans their face using their smartphone camera while shopping in a physical store, the application analyzes the user's emotions and, if they are feeling angry, suggests products with a relaxing effect (aroma candles or relaxation goods).

[0707] Prompt Sentence Examples

[0708] Design a system in which a user scans their face using their smartphone camera while shopping in a physical store, and the application analyzes the user's emotions. For example, if the user is feeling "anger," the system suggests products with a relaxing effect (aroma candles or relaxation goods).

[0709] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0710] Step 1:

[0711] The server manages the virtual space and trains the AI ​​model. Specifically, it builds a platform that enables historical reproduction, generates AI with individual thoughts equivalent to the world's total population, and places them in the virtual space. Past historical data and demographic data are used as input, and the output is the generation of AI agents that can act independently within the virtual space.

[0712] Step 2:

[0713] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. The input is the history of the influential person's actions and statements, and the output is an AI agent that behaves like that person.

[0714] Step 3:

[0715] The device captures camera footage and inputs it into an emotion recognition model for real-time analysis of the user's emotions. The input is video data acquired from the smartphone camera, and the output is identifying the user's emotional state (e.g., anger, joy, sadness, etc.).

[0716] Step 4:

[0717] Based on the emotion recognition results, the device retrieves optimal product suggestions and service information via a REST API and displays it to the user. The emotion recognition results and the user's current location information are used as input, and a list of appropriate products and services is generated as output.

[0718] Step 5:

[0719] Users scan their face using their smartphone camera, which allows the device to analyze the user's emotions and suggest appropriate products and services. The input is the user's facial image, and the output is the emotion analysis results and product suggestions based on them.

[0720] Step 6:

[0721] The terminal displays the retrieved product information and service information to the user. As input, it uses the product information and service information retrieved from the REST API, and as output, it generates a product list or service list to be displayed on the user's smartphone screen.

[0722] Step 7:

[0723] The user checks the proposed products and services and purchases or uses them as necessary. The product and service information displayed on the terminal is used as input, and the user's purchasing behavior and service usage behavior are obtained as output.

[0724] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0725] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt containing an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in the data format of voice data, text data, etc.

[0726] Here, inference can refer to, for example, analysis, classification, prediction, and / or summarization.

[0727] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0728] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0729] [Second embodiment]

[0730] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0731] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0732] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0733] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0734] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0735] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0736] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0737] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0738] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0739] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0740] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0741] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0742] "Example 1"

[0743] As an embodiment of the present invention, we will build a platform that enables the reproduction of history. This platform will generate a virtual space along a timeline based on historical data from the past to the present. In this virtual space, AIs equivalent to the total world population will be placed. These AIs will have their own individual thoughts and will act independently.

[0744] "Example 2"

[0745] Furthermore, the specific thoughts and actions of influential people can be inherited and turned into AI. Specifically, the AI ​​learns the thought patterns and behaviors of business leaders and historical figures and imitates them. This makes it possible to inherit the knowledge and management decisions of business leaders even after they retire. It is also possible to obtain new management hints through dialogue with historical figures.

[0746] "Example 3"

[0747] Furthermore, various hypotheses can be realistically verified and visualized to aid in future predictions. Specifically, scenarios based on specific hypotheses are set in a virtual space where AI acts autonomously, and the results are observed. This makes it possible to obtain information that is useful for formulating business strategies and making future predictions.

[0748] The processing flow of each embodiment will be described below.

[0749] "Example 1"

[0750] Step 1: Collect historical data from the past to the present. This data includes information about people's behavior, events, technological advances, and other time-based information.

[0751] Step 2: Based on the collected historical data, a virtual space along a timeline is generated. This virtual space will become a platform that enables historical reconstruction.

[0752] Step 3: Create a number of AIs equivalent to the total population of the world. These AIs will have their own thoughts and behave independently.

[0753] Step 4: Place the generated AI in a virtual space, creating an environment in which the AI ​​can act autonomously to recreate history.

[0754] "Example 2"

[0755] Step 1: Learn the thought and behavior patterns of influential people. Specifically, extract the thought and behavior patterns from the statements and actions of business leaders and historical figures. Step 2: Generate AI that imitates the extracted thought and behavior patterns.

[0756] Step 3: The generated AI is placed in a virtual space, allowing interaction with the AI ​​that inherits the thoughts and actions of influential people.

[0757] "Example 3"

[0758] Step 1: Create a scenario based on a specific hypothesis. This scenario will serve as a guide for the AI ​​to act autonomously in a virtual space.

[0759] Step 2: The AI ​​acts independently based on the set scenario.

[0760] Step 3: Observe the results of AI actions and analyze the results, which will enable us to obtain information that will be useful for formulating business strategies and making future predictions.

[0761] Example 1

[0762] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0763] With current technology, it is difficult to realistically recreate past history and allow users to experience and learn from it. It is also difficult to inherit the thoughts and actions of influential historical figures and interact with them in a virtual space. Furthermore, there is a lack of means to verify hypotheses and make realistic predictions about the future, making it difficult to use for formulating business strategies or predicting the future.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0765] In this invention, the server includes means for building a platform that enables historical reproduction, means for collecting historical data from the past to the present and storing it in a database, means for generating a virtual space along a timeline based on the collected data, means for generating AIs with individual thoughts equivalent to the total world population and placing them in the virtual space and making them act autonomously, means for customizing and displaying the virtual space based on user requests, means for users to interact with AI agents in the virtual space and obtain information, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help predict the future.This allows users to realistically experience and learn about past history, interact with influential historical figures, and further verify hypotheses and make realistic predictions about the future.

[0766] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience and learn within it.

[0767] "Historical data" refers to information about history, such as past events, demographics, cultural background, and geographic information.

[0768] A "database" is a collection of information that stores collected historical data and is indexed for rapid access through queries.

[0769] "Virtual space" is a three-dimensional digital space generated along a timeline based on collected historical data.

[0770] An "AI agent" is an artificial intelligence that uses a generative AI model to have individual thoughts and act independently.

[0771] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to communicate with users and other AI agents.

[0772] A "User Request" is a request submitted by a User to the Platform specifying a particular historical period or location.

[0773] "Customization" means adjusting the virtual space based on the user's requests and generating detailed scenes relating to specific times and places.

[0774] An "influential person" is someone who has had a major impact in a particular field, such as someone who played an important role in history or a business leader.

[0775] "Hypothesis testing" involves trying out various scenarios in a virtual space and observing the results.

[0776] "Future prediction" is the prediction of future events or situations based on the results of hypothesis verification.

[0777] MODE FOR CARRYING OUT THE INVENTION

[0778] The present invention aims to build a platform that enables historical reproduction, allowing users to realistically experience and learn about past history. A specific embodiment of this system will be described below.

[0779] Generating a Program

[0780] The server generates a platform program that enables historical reproduction. This program has the function of generating a virtual space along a timeline based on historical data from the past to the present.

[0781] Program processing

[0782] The server first collects historical data and stores it in a database, which includes past events, demographics, cultural background, geographic information, etc. The collected data is stored in a database such as MongoDB or MySQL.

[0783] The server then uses this data to generate a virtual space. This virtual space is built using a game engine such as Unity or Unreal Engine. For example, to recreate 19th century Paris, the server places buildings, cityscapes, and scenery from that era into the virtual space. This is done using assets created in 3D modeling tools such as Blender.

[0784] AI agents equivalent in number to the world's total population are placed in the virtual space. These AI agents are configured to have individual thoughts and act autonomously using generative AI models (e.g., OpenAI's GPT-4). The AI ​​agents communicate with users and other AI agents using natural language processing (NLP) technology.

[0785] Specific examples

[0786] When a user accesses the platform using a device, the server generates a virtual space in response to the user's request and displays it on the device. For example, if a user requests a recreation of 19th century Paris, the server generates a virtual space based on data about 19th century Paris and displays it on the device.

[0787] As a concrete example, a user inputs the following prompt sentence into a generative AI model:

[0788] "Recreate life in 19th century Paris. I'd especially like to learn more about the construction of the Eiffel Tower."

[0789] The server receives this prompt and generates a virtual space based on data about 19th-century Paris, recreating the construction process of the Eiffel Tower in detail. The AI ​​agents act autonomously as workers and citizens of the time, providing real-time information to the user.

[0790] In this way, users can experience past history in a realistic way and interact with influential historical figures. They can also verify hypotheses and make realistic predictions about the future, which can be useful for formulating business strategies and forecasting the future.

[0791] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0792] Step 1:

[0793] The server collects historical data and stores it in a database.

[0794] Input: reliable data sources on the internet (e.g., historical databases and literature)

[0795] How it works: The server uses scraping technology to collect data such as historical events, demographics, cultural background, and geographic information. The collected data is then stored in a database such as MongoDB or MySQL.

[0796] Output: Archived historical data

[0797] Step 2:

[0798] The server generates a virtual space based on the collected data.

[0799] Input: Stored historical data

[0800] How it works: The server uses game engines such as Unity or Unreal Engine to generate 3D models based on the collected data. For example, to recreate 19th century Paris, it places 3D models of buildings and roads from that time. This uses assets created in 3D modeling tools such as Blender.

[0801] Output: Generated virtual space

[0802] Step 3:

[0803] The server places and configures AI agents within the virtual space.

[0804] Input: Generated virtual space, generative AI model

[0805] Specific operation: The server uses a generative AI model (e.g., GPT-4) to set an individual profile for each AI agent. For example, one AI agent is set as a worker in 19th century Paris, while others are set as citizens or merchants. This allows each AI agent to have different behavioral patterns.

[0806] Output: The configured AI agent

[0807] Step 4:

[0808] A user accesses the platform using a terminal and requests a particular historical period or location.

[0809] Input: User request (e.g., "I want a 19th century Paris re-created")

[0810] Specific operation: A user accesses the platform through a browser on their device and requests a specific time and location.

[0811] Output: User request data

[0812] Step 5:

[0813] The server customizes and displays the virtual space based on the user's request.

[0814] Input: User request data, generated virtual space

[0815] How it works: The server customizes the virtual space based on the user's request. For example, if a user requests 19th-century Paris, the server generates a detailed scene, including the construction of the Eiffel Tower, and streams it to the device in real time.

[0816] Output: Customized virtual space

[0817] Step 6:

[0818] Users explore the virtual space through their devices and interact with AI agents.

[0819] Input: A customized virtual space, a user prompt (e.g., "Tell me about the construction of the Eiffel Tower").

[0820] Specific operation: The user moves freely through the virtual space via the terminal and interacts with the AI ​​agent, which uses the generative AI model to respond and provide information in real time based on the user's prompts.

[0821] Output: Response from the AI ​​agent, user experience information

[0822] (Application example 1)

[0823] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0824] Conventional historical reenactment systems simply visually reproduce past events, making it difficult for users to interact with people from that era or move freely around and experience them. Furthermore, interactions within the virtual space are limited, making it impossible to generate real-time responses based on user input. Furthermore, the visual experience using a head-mounted display is insufficient, resulting in a lack of immersion.

[0825] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0826] In this invention, the server includes means for building a platform that enables the reproduction of history, means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to allow them to act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for enabling users to move freely within the virtual space and interact with AI characters, means for visually experiencing the virtual space using a head-mounted display, and means for generating responses from AI characters based on user input and displaying them in the virtual space, thereby enabling users to experience past historical events and eras in the virtual space and interact with AI characters.

[0827] The "platform that enables historical reenactment" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience historical events within it.

[0828] "AI with individual thoughts" is artificial intelligence that has its own unique thought patterns and acts independently.

[0829] A "virtual space" is a three-dimensional digital space generated by a computer, in which users can move freely and interact.

[0830] An "influential person" is someone who has played an important role in history or in the present day, and whose thoughts and actions have a great influence on others.

[0831] "Means enabling dialogue" refers to a function that allows users to have natural conversations with AI characters.

[0832] "A means to realistically verify and visualize hypotheses to help predict the future" is a function that simulates various scenarios in a virtual space and visually displays the results, helping to predict the future and formulate strategies.

[0833] "Means that allow users to move freely and interact with AI characters" refers to a function that allows users to move freely within the virtual space and interact with placed AI characters.

[0834] A "head-mounted display" is a display device that the user wears on their head, allowing them to visually experience a virtual space.

[0835] "Means for generating responses from an AI character based on user input and displaying them in a virtual space" refers to a function that receives input from a user, generates responses from an AI character in real time in response to the input, and displays them in a virtual space.

[0836] The system for implementing this invention uses the following hardware and software: a head-mounted display (e.g., Oculus Rift, HTC Vive) as hardware, and a VR engine (e.g., Unity, Unreal Engine), OpenAI API, and a history database as software.

[0837] The server first builds a platform that enables historical reproduction. Specifically, it generates a virtual space along a timeline based on historical data from the past to the present. In this virtual space, it generates and places AIs with individual thoughts, in numbers equivalent to the total world population. These AIs act autonomously and are able to interact with users.

[0838] By wearing a head-mounted display, users can move freely within the virtual space and interact with AI characters. Based on the user's input, the server uses the OpenAI API to generate responses from the AI ​​characters and display them in the virtual space. This allows users to realistically experience past historical events and eras.

[0839] For example, if a user says, "I want to meet Napoleon," the server will generate an AI character of Napoleon in the virtual space and have it interact with the user. The following is an example of a prompt sentence:

[0840] User: I want to meet Napoleon

[0841] AI: Hello, I'm Napoleon Bonaparte. What question do you have?

[0842] In this way, users can interact with historical figures and experience past events. Hypothesis verification and visualization can also be used to predict the future and formulate strategies.

[0843] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0844] Step 1:

[0845] The server loads historical data from the past to the present from the historical database. The input is the historical database, and the output is the loaded historical data. Specifically, the server executes a database query to obtain the required data.

[0846] Step 2:

[0847] The server generates a virtual space along a timeline based on the loaded historical data. The input is the loaded historical data, and the output is the generated virtual space. Specifically, the server uses a VR engine to construct a three-dimensional virtual space.

[0848] Step 3:

[0849] The server generates AIs with individual thoughts, in numbers equivalent to the total world population, and places them in a virtual space. The input is historical data and a generative AI model, and the output is an AI character placed in the virtual space. Specifically, the server uses the OpenAI API to generate AI characters and place them in the virtual space.

[0850] Step 4:

[0851] The user wears a head-mounted display and accesses the virtual space. The input is the user's visual information, and the output is the visual experience of the virtual space. Specifically, the user wears the head-mounted display and moves freely within the virtual space.

[0852] Step 5:

[0853] The user provides input to interact with the AI ​​character in the virtual space. The input is the user's voice or text, and the output is the user's input data. Specifically, the user speaks to the AI ​​character using voice recognition or text input.

[0854] Step 6:

[0855] The server generates responses for the AI ​​character based on the user's input. The input is the user's input data and the generative AI model, and the output is the AI ​​character's response. Specifically, the server uses the OpenAI API to generate appropriate responses to the user's input.

[0856] Step 7:

[0857] The server displays the generated AI character's response in the virtual space. The input is the AI ​​character's response, and the output is the response displayed in the virtual space. Specifically, the server uses the VR engine to visually display the response.

[0858] Step 8:

[0859] The user checks the response of the AI ​​character displayed in the virtual space and performs the next interaction. The input is the response displayed in the virtual space, and the output is the user's next input. In concrete terms, the user checks the displayed response and asks the next question or gives the next instruction.

[0860] Example 2

[0861] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0862] There is a need to inherit the knowledge and management decisions of influential figures and utilize that knowledge even after retirement. It is also important to obtain new management hints through dialogue with historical figures. However, there is a lack of concrete methods to effectively inherit this knowledge and decisions and utilize them in actual management. Furthermore, a system is needed to verify hypotheses and make realistic predictions about the future.

[0863] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0864] In this invention, the server includes means for collecting data on influential people, means for preprocessing the collected data, means for training a machine learning model based on the preprocessed data, means for evaluating the trained model, means for providing an interface for users to interact with the AI, means for the AI ​​to generate answers based on user input, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help with future predictions. This makes it possible to effectively inherit the knowledge and management decisions of influential people and use them in actual management. Furthermore, dialogue with historical figures can provide new management insights, allowing for realistic hypothesis verification and future predictions.

[0865] An "influential person" is someone who plays an important role in society or an organization and whose thoughts and actions have a significant impact on others.

[0866] "Data collection" refers to the process of obtaining information needed for a specific purpose from sources such as the internet or databases.

[0867] "Preprocessing" refers to a series of operations performed on collected data to transform it into a form suitable for analysis and model training, including data cleaning, tokenization, and normalization.

[0868] A "machine learning model" refers to an algorithm or mathematical model that automatically learns specific tasks based on data and makes predictions or classifications.

[0869] "Model training" refers to the process of using collected data to train a machine learning model and improve its performance.

[0870] "Model evaluation" refers to the process of evaluating the performance of a trained machine learning model using test data to confirm its accuracy and effectiveness.

[0871] "User interface" refers to the software and hardware components that provide a means for a user to interact with a system, including chatbots and voice recognition.

[0872] A "prompt" refers to the text of a question or instruction that a user enters into an AI.

[0873] "Hypothesis verification" refers to the process of verifying whether a particular hypothesis is correct using actual data or simulations.

[0874] "Future forecasting" refers to the process of predicting future events or conditions based on current data and trends.

[0875] This invention is a system for inheriting the knowledge and management decisions of influential people and utilizing that knowledge even after they retire. A specific embodiment of this system will be described below.

[0876] The server first collects data on influencers, including their past statements, behavioral history, and decision-making processes, using web scraping tools (e.g., BeautifulSoup, Scrapy) or APIs.

[0877] The server then preprocesses the collected data, which includes cleaning the text data (denoising, normalising), tokenising, removing stop words, etc. This is done using natural language processing libraries such as Python's NLTK or spaCy.

[0878] The server then uses the preprocessed data to train a machine learning model designed to learn the thought and behavior patterns of influential people. Training is performed using deep learning frameworks such as TensorFlow and PyTorch, and is run on a server equipped with high-performance GPUs.

[0879] The trained model is evaluated by the server. The evaluation involves checking the accuracy of the model using test data and adjusting hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc.

[0880] The device provides an interface for users to interact with the AI, including chatbot-style interfaces and voice-activated applications, using web frameworks such as Flask and Django.

[0881] The user poses a question to the AI ​​through their device. For example, the user might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the device's chat box. For example, a response might read, "When entering a new market, it is important to first conduct thorough market research. To minimize risk, it is necessary to work with local partners and understand differences in laws, regulations, and culture."

[0882] In this way, the knowledge and management decisions of influential figures can be effectively passed on and put to use in actual management. Furthermore, through dialogue with historical figures, new management hints can be obtained, and hypotheses can be verified and future predictions can be made in real time.

[0883] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0884] Step 1:

[0885] The server collects data on influential people. Specifically, it uses web scraping tools (e.g., BeautifulSoup, Scrapy) and APIs to retrieve data such as executives' past statements, behavioral history, and decision-making processes from the internet and corporate databases. The input is the website URL or API endpoint, and the output is the collected text data.

[0886] Step 2:

[0887] The server preprocesses the collected data. Specifically, it uses Python's NLTK and spaCy to clean the text data (remove noise, normalize), tokenize, and remove stop words. The input is the collected text data, and the output is the preprocessed, clean text data.

[0888] Step 3:

[0889] The server trains a machine learning model based on the preprocessed data. Specifically, it uses TensorFlow and PyTorch to build a deep learning model that learns the thought patterns and behavior patterns of influential people. The input is the preprocessed text data, and the output is the trained machine learning model.

[0890] Step 4:

[0891] The server evaluates the trained model. Specifically, it checks the model's accuracy using test data and adjusts hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc. The input is the trained machine learning model and test data, and the output is the evaluation results and the adjusted model.

[0892] Step 5:

[0893] The terminal provides an interface for users to interact with the AI. Specifically, Flask and Django are used to build an application with a chatbot-style interface and speech recognition functionality. The input is the user's questions and instructions (prompts), and the output is the AI's response.

[0894] Step 6:

[0895] The user poses a question to the AI ​​through the terminal. For example, they might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the terminal's chat box. The input is the user's prompt, and the output is the answer from the AI.

[0896] (Application example 2)

[0897] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0898] In today's business environment, there is a need to inherit and utilize in real time the knowledge and management decisions of influential business leaders and historical figures. However, existing technologies have limited the means to effectively utilize this knowledge, making it difficult to optimize customer service, product placement, and promotions, especially in physical stores.

[0899] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0900] In this invention, the server includes a means for building a platform that enables the reproduction of history, a means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, a means for providing the knowledge and management decisions of influential people in real time using smart devices, and a means for verifying and visualizing various hypotheses in real time to help predict the future. This will enable the optimization of customer service, product placement, and promotions even in physical stores.

[0901] A "platform that enables historical reenactment" is a system that recreates past events and the actions of people in a virtual space, allowing users to experience them.

[0902] "AI with individual thoughts" is artificial intelligence that learns the thought patterns of a specific person or character and acts independently based on that.

[0903] "Inheriting the specific thoughts and actions of influential people and turning them into AI" means creating an AI that learns the thinking and behavior patterns of famous historical figures and modern business leaders and imitates them.

[0904] "Interaction-enabling means" refers to interfaces and technologies that allow users to have natural conversations with artificial intelligence.

[0905] A "smart device" is an electronic device that can connect to the Internet and run various applications. Examples include smartphones and smart glasses.

[0906] "A means of providing insights and business decisions from influential people in real time" is a technology that allows users to instantly receive insights and business decisions from influential people based on their current situation.

[0907] "A means of realistically verifying and visualizing hypotheses to aid in future predictions" is a technology that simulates hypotheses and visually displays the results to aid in future predictions and strategy formulation.

[0908] To implement the present invention, the following system configuration and program are required.

[0909] First, the server builds a platform that enables historical reenactment. This platform recreates past events and the actions of people in a virtual space, allowing users to experience them. Next, the server generates AI with individual thoughts, in numbers equivalent to the world's total population, places them in the virtual space, and lets them act independently. This AI learns the thought patterns of specific people and characters and acts independently based on those patterns.

[0910] Furthermore, the server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. This AI learns and imitates the thinking and behavior patterns of famous historical figures and modern business leaders. Users can have natural conversations with this AI.

[0911] Next, we will implement a method to provide influential people's insights and business decisions in real time using smart devices such as smartphones and smart glasses. This allows users to instantly receive insights and business decisions from influential people based on their current situation.

[0912] Specifically, an application installed on the smart glasses analyzes customer behavior through the camera and sends the data to a server. The server uses the data to generate appropriate prompts and provides advice using a generative AI model. For example, if a customer picks up a specific product, the server generates a prompt such as, "Please tell us what to do if a customer picks up the product," and the AI ​​provides real-time advice such as, "Provide a detailed description of the product and share related promotional information."

[0913] The hardware used includes smart glasses (with a camera) and smartphones, and the software uses OpenAI API and OpenCV (image processing library), enabling optimization of customer service, product placement, and promotions in physical stores.

[0914] Examples of prompts include:

[0915] "What should I do if a customer picks up my product?"

[0916] In this way, store staff can tap into the knowledge of renowned business leaders and marketing experts from history to optimize customer interactions.

[0917] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0918] Step 1:

[0919] The user puts on the smart glasses and launches the application.

[0920] Input: Smart glasses camera image

[0921] Output: Real-time video data

[0922] Specific operation: The camera in the smart glasses captures video in real time, and the application acquires the video data.

[0923] Step 2:

[0924] The device analyzes camera footage and detects customer behavior.

[0925] Input: Real-time video data

[0926] Output: Customer behavior data (e.g., product pick-up behavior)

[0927] Specific operation: The device uses OpenCV to analyze video data and detect specific actions, such as a customer picking up a product.

[0928] Step 3:

[0929] The device transmits the detected behavior data to the server.

[0930] Input: Customer behavior data

[0931] Output: Send data to the server

[0932] Specific operation: The device generates an API request to send the detected customer behavior data to the server and sends it to the server.

[0933] Step 4:

[0934] The server generates a prompt sentence based on the behavioral data received.

[0935] Input: Customer behavior data

[0936] Output: Prompt statement (e.g., "What should I do if the customer picks up the item?")

[0937] Specific behavior: The server analyzes the received behavioral data and executes logic to generate appropriate prompt sentences.

[0938] Step 5:

[0939] The prompt sentence generated by the server is input into the generative AI model to obtain advice.

[0940] Input: prompt statement

[0941] Output: AI advice (e.g., "Provide a detailed description of the product and share relevant promotional information.")

[0942] Specific operation: The server uses the OpenAI API to input prompt sentences into the generative AI model and obtain advice from the AI.

[0943] Step 6:

[0944] The server transmits the obtained advice to the terminal.

[0945] Input: AI advice

[0946] Output: Sending data to the terminal

[0947] Specific operation: The server generates an API request to send the obtained advice to the terminal and sends it to the terminal.

[0948] Step 7:

[0949] The terminal displays the received advice to the user.

[0950] Input: AI advice

[0951] Output: Advice displayed on the smart glasses display

[0952] Specific operation: The terminal displays the received advice on the display of the smart glasses so that the user can check it.

[0953] In this way, users can receive real-time insights and business decisions from influential people and optimize customer service, product placement, and promotions.

[0954] Example 3

[0955] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0956] Hypothesis verification and scenario simulation are important in modern business strategies and future predictions, but experiments and verifications in the real world require a great deal of time and cost. It is also difficult to inherit the knowledge and management decisions of influential people and use them in simulations in virtual space. Furthermore, there is a lack of systems that can convert user-defined hypotheses into concrete scenarios and observe and analyze the results in real time.

[0957] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0958] In this invention, the server includes means for building a platform that enables historical reproduction, means for generating artificial intelligences with individual thoughts equivalent to the total world population, placing them in a virtual space, and making them act independently, means for inheriting the specific thoughts and actions of influential people and turning them into artificial intelligences that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for a user to set hypotheses and generate prompt statements, means for analyzing the generated prompt statements and generating specific instructions to be executed in the virtual space, means for constructing a virtual space, placing artificial intelligence agents, and executing scenarios, means for observing results, collecting data, analyzing them, and generating reports, and means for displaying the results to the user. This enables a user to set hypotheses, execute specific scenarios in the virtual space, and observe and analyze the results in real time.

[0959] The "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and observe that environment.

[0960] "Artificial intelligence" is a computer program that mimics human thought and behavior and has the ability to learn, judge, and act independently.

[0961] A "virtual space" is a computer-generated, three-dimensional digital environment, a simulated environment in which users and artificial intelligence can interact.

[0962] An "influential person" is someone whose actions and decisions have a widespread impact, such as a historical figure or a modern business leader.

[0963] "Inheriting thoughts and actions to create artificial intelligence" means collecting data on the thought patterns and actions of influential people and building artificial intelligence based on that data.

[0964] A "hypothesis" is a prediction or assumption about a certain phenomenon or event, and is a prerequisite for confirming its validity through verification and experimentation.

[0965] A "prompt sentence" is an input sentence for converting a hypothesis set by the user into a specific scenario.

[0966] A "generative AI model" is an artificial intelligence model that analyzes prompt statements and generates specific instructions to be executed in a virtual space.

[0967] A "scenario" is a hypothetical sequence of events or situations that is carried out in a virtual space.

[0968] "Means of observing results, collecting data, analyzing, and generating reports" refers to the process of observing the results of scenarios executed in virtual space in real time, collecting and analyzing that data, and creating reports to provide to users.

[0969] "Means for displaying results to the user" refers to an interface that visually displays the collected and analyzed data and allows the user to review and evaluate the results.

[0970] This invention is a system that uses artificial intelligence in a virtual space to verify hypotheses and is useful for future predictions and the formulation of business strategies. Specific embodiments of this system will be described below.

[0971] First, the user sets a hypothesis through an interface on a web browser. For example, the user inputs a hypothesis such as "Sales fluctuations when new product A is launched on the market." The terminal generates a prompt based on the hypothesis entered by the user. Specifically, the prompt generated is "Please simulate how sales will fluctuate over the next six months when new product A is launched on the market."

[0972] The server then sends the generated prompt to a generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual world. This generative AI model is built using a machine learning framework such as TensorFlow or PyTorch.

[0973] The server uses software such as Unity to create a virtual world, which is designed based on a scenario set by the user and includes stores, consumers, competitors, and more.

[0974] The server deploys artificial intelligence agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The artificial intelligence agents are controlled by machine learning models written in Python, which allows the server to simulate consumer behavior and observe fluctuations in sales.

[0975] The results of the scenario execution are observed in real time by the server, which collects sales data and consumer behavior data. This data is stored in a database. The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of a report. The report includes graphs showing sales trends and statistical information on consumer purchasing behavior.

[0976] Finally, the terminal displays the report received from the server to the user, who can then use the dashboard to view sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions.

[0977] As a concrete example, consider a simulation of the impact of a new product launch on sales. The user inputs the following prompt into the generative AI model:

[0978] "If we launch new product A into the market, please simulate how sales will fluctuate over the next six months."

[0979] The server receives this prompt and sets up a market launch scenario for new product A in the virtual space. The artificial intelligence agent simulates consumer behavior and observes fluctuations in sales. The observation results are provided to the user in the form of graphs and reports, which can be used to formulate business strategies and make future predictions. The flow of the specific processing in Example 3 will be explained using FIG. 15.

[0980] Step 1:

[0981] The user sets the hypothesis

[0982] The user opens the interface on a web browser and inputs a hypothesis. For example, they input a hypothesis such as "Sales fluctuations when new product A is released to the market." The input data is the text information of the hypothesis. The output is that the hypothesis is registered in the system.

[0983] Step 2:

[0984] The terminal generates a prompt

[0985] The terminal generates a prompt based on the hypothesis entered by the user. Specifically, it generates the prompt, "Please simulate how sales will fluctuate over the next six months if new product A is released to the market." The input data is the hypothesis set by the user, and the output is the generated prompt.

[0986] Step 3:

[0987] The server sends a prompt to the generative AI model

[0988] The server sends the prompt received from the device to the generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual space. The input data is the generated prompt, and the output is specific scenario instructions.

[0989] Step 4:

[0990] The server creates the virtual space

[0991] The server uses software such as Unity to build a virtual space. This virtual space is designed based on a scenario set by the user. The input data are specific scenario instructions, and the output is the constructed virtual space.

[0992] Step 5:

[0993] The server deploys AI agents and executes scenarios.

[0994] The server deploys AI agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The AI ​​agents are controlled by machine learning models written in Python. The input data are specific scenario instructions, and the output is the results of the executed scenario.

[0995] Step 6:

[0996] The server observes the results and collects the data.

[0997] The server observes the results of the scenario execution in real time and collects sales data and consumer behavior data. These data are stored in a database. The input data are the results of the executed scenario, and the output is the collected data.

[0998] Step 7:

[0999] The server analyzes the results and generates a report

[1000] The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of reports. The reports include graphs showing sales trends and statistical information on consumer purchasing behavior. The input data is the collected data, and the output is the generated report.

[1001] Step 8:

[1002] The device displays the results to the user

[1003] The terminal displays the report received from the server to the user. Through the dashboard, the user can check sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions. The input data is the generated report, and the output is the result displayed to the user.

[1004] (Application example 3)

[1005] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1006] Optimizing work efficiency is an important issue in modern logistics centers. However, trying out new layouts and work flows in a real environment is not easy due to the costs and risks involved. It is also difficult to verify hypotheses when formulating business strategies or making future predictions. To solve these issues, a means is needed to utilize simulations in virtual space to find optimal strategies that are efficient, low-risk, and efficient.

[1007] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for building a platform that enables historical reproduction, a means for generating AIs with individual thoughts equivalent to the total world population and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can interact, a means for simulating scenarios in a virtual space to optimize work efficiency within a logistics center, and a means for visualizing the simulation results and proposing optimal strategies. This makes it possible to evaluate the effects of new layouts and work flows in logistics centers with low risk and to formulate optimal strategies.

[1008] A "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and learn within it.

[1009] "AI with individual thinking" is artificial intelligence that imitates the thought patterns and behavior of a specific individual and makes decisions and takes action independently.

[1010] A "virtual space" is a digital environment generated by computer simulation, an area in which users can interact.

[1011] "Means for autonomous action" refers to technologies and algorithms that allow AI to make decisions and take action on its own without external instructions.

[1012] An "influential person" is an individual who has had a significant impact on society or an organization, either historically or in the present day.

[1013] "Means to inherit specific thoughts and actions, turn them into AI, and enable dialogue" refers to technology that incorporates the thoughts and behavioral patterns of influential people into AI, allowing users to interact with that AI.

[1014] "A means to realistically verify and visualize hypotheses to help predict the future" is a technology that executes scenarios set up in virtual space and visually displays the results, helping to predict the future and formulate strategies.

[1015] "A means of simulating scenarios in a virtual space to optimize work efficiency within a logistics center" is a technology that tests the layout and work flow of a logistics center in a virtual space and evaluates their effectiveness.

[1016] "Means for visualizing simulation results and proposing optimal strategies" refers to technology that visually displays the results of simulations in graphs, charts, etc., and suggests optimal actions and strategies to users.

[1017] The following system configuration will be described as an embodiment of the present invention.

[1018] System Configuration

[1019] The server includes the following means:

[1020] 1. A means of building a platform that allows historical re-enactment

[1021] 2. A method to generate AI with individual thoughts equivalent to the total population of the world, place them in a virtual space, and make them act independently.

[1022] 3. A means to inherit the specific thoughts and actions of influential people and turn them into AI, enabling dialogue

[1023] 4. A means of simulating scenarios in virtual space to optimize work efficiency within a logistics center

[1024] 5. A means to visualize simulation results and propose optimal strategies

[1025] Hardware and software used

[1026] Hardware: Servers, smartphones, computers

[1027] Software: Python, NumPy, Matplotlib, Scikit-learn

[1028] Data processing and calculation

[1029] The server will first build a platform that enables historical reenactment. This platform is a system that recreates past events and situations in a virtual space, allowing users to experience and learn from them.

[1030] The server then generates a number of AIs with individual thoughts equivalent to the total population of the world and places them in a virtual space, allowing the AIs to act autonomously and test hypotheses based on specific scenarios.

[1031] Furthermore, the specific thoughts and actions of influential people will be inherited and turned into AI, enabling dialogue, allowing users to interact with historical figures and business leaders and gain insights.

[1032] This also includes a means of simulating scenarios in a virtual space to optimize work efficiency within a logistics center, in which layouts and work flows of the logistics center are tested in a virtual space and their effectiveness is evaluated.

[1033] Finally, we use a method to visualize the simulation results and propose optimal strategies. This allows us to visually display the simulation results in graphs and charts, and to propose optimal actions and strategies to users.

[1034] Specific examples

[1035] For example, it is possible to simulate how work efficiency changes when the layout of a logistics center is changed, and it is also possible to evaluate the effects of introducing a new work flow.

[1036] Prompt Sentence Examples

[1037] "Perform simulations to optimize your distribution center layout and maximize operational efficiency. Set up scenarios involving new layouts and workflow changes and visualize the results."

[1038] In this way, simulation applications can be developed to help optimize logistics centers and then tested in real environments with low risk.

[1039] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1040] Step 1:

[1041] The server builds a platform that enables historical reconstruction. As input, it receives data on past events and situations and generates a virtual space based on this data. As output, it provides a virtual space where users can experience and learn. This virtual space includes an interface for users to interact with.

[1042] Step 2:

[1043] The server generates AIs with individual thoughts, in numbers equivalent to the total world population, and places them in a virtual space. As input, it receives each AI's thought patterns and behavioral data, and generates an AI model based on this. As output, it places an AI that can act independently in the virtual space. This makes it possible for the AI ​​to act based on specific scenarios and verify hypotheses.

[1044] Step 3:

[1045] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. As input, it receives the influential person's thoughts and actions data and generates an AI model based on this. As output, it provides AI with which the user can interact. This AI imitates the knowledge and judgment of the influential person and provides useful information to the user.

[1046] Step 4:

[1047] The server simulates scenarios for optimizing work efficiency within a logistics center in a virtual space. It receives data on the layout and work flow of the logistics center as input and runs the simulation based on this data. It provides the simulation results as output. These results include data showing changes in work efficiency and the effects of optimization.

[1048] Step 5:

[1049] The server visualizes the simulation results and proposes the optimal strategy. It receives the simulation result data as input and generates graphs and charts based on this. As output, it provides a visual display of the simulation results and a proposal for the optimal strategy. Users can then use this to formulate strategies for their actual logistics centers.

[1050] In this way, through a series of processes, the server can run simulations that are useful for optimizing the logistics center and provide the results to the user.

[1051] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1052] "Example 1"

[1053] One embodiment of the present invention is a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the AI's behavior based on those emotions. Specifically, when the user is feeling joy, the AI ​​shares that joy and acts to make the interaction with the user more enjoyable. Also, when the user is feeling sad, the AI ​​understands that sadness and acts to comfort the user.

[1054] "Example 2"

[1055] Another possible system is to use an emotion engine to verify and visualize hypotheses based on user emotions. Specifically, when a user feels joy, a hypothesis can be formulated about what that joy comes from and what factors cause it, and then that hypothesis can be verified. This will enable a deeper understanding of the user's emotions and enable more appropriate responses to those emotions.

[1056] "Example 3"

[1057] Furthermore, a system that uses an emotion engine to adjust AI behavior based on the user's emotions is also conceivable. Specifically, when a user feels angry, a hypothesis can be made as to what the source of that anger is and what factors are causing it, and that hypothesis can be verified. This will enable a deeper understanding of the user's emotions and a more appropriate response to those emotions.

[1058] The processing flow of each embodiment will be described below.

[1059] "Example 1"

[1060] Step 1: The emotion engine recognizes the user's emotion.

[1061] Step 2: Adjust the AI's behavior based on the recognized emotions. Specifically, when the user feels joy, the AI ​​will share that joy and act in a way that makes the interaction with the user more enjoyable.

[1062] Step 3: When the user is feeling sad, the AI ​​understands that sadness and takes action to comfort the user.

[1063] "Example 2"

[1064] Step 1: The emotion engine recognizes the user's emotion.

[1065] Step 2: Create a hypothesis based on the recognized emotion. Specifically, when a user feels joy, create a hypothesis about what that joy comes from and what elements cause it.

[1066] Step 3: Test your hypotheses. This will help you better understand your users' emotions and better respond to them.

[1067] "Example 3"

[1068] Step 1: The emotion engine recognizes the user's emotion.

[1069] Step 2: Create a hypothesis based on the recognized emotion. Specifically, when a user feels angry, create a hypothesis about what the anger comes from and what factors are causing the anger.

[1070] Step 3: Test your hypotheses. This will help you better understand your users' emotions and better respond to them.

[1071] Example 1

[1072] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1073] Conventional historical reenactment systems simply reproduce past events and the actions of people, making it difficult to provide an interactive experience that responds to the user's emotions. Furthermore, there are only a limited number of systems that can provide appropriate information when a user asks about a specific historical event or person. Furthermore, there is a lack of systems that can inherit the thoughts and actions of influential people and use them to predict the future or formulate business strategies.

[1074] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1075] In this invention, the server includes a means for building a platform that enables historical reproduction; a means for generating AIs with individual thoughts equivalent to the total world population, placing them in a virtual space, and enabling them to act independently; a means for inheriting the specific thoughts and actions of influential people to turn them into AIs and enable dialogue; a means for realistically verifying and visualizing various hypotheses to help predict the future; a means for recognizing user emotions and adjusting the AI's behavior based on those emotions; and a means for the AI ​​to provide appropriate information based on prompts entered by the user. This makes it possible to provide an interactive experience that responds to the user's emotions and provides appropriate information about specific historical events or people. Furthermore, inheriting the thoughts and actions of influential people can be useful for predicting the future and formulating business strategies.

[1076] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience historical events and people within it.

[1077] "Artificial intelligence" refers to a program that has individual thoughts and acts independently, and is capable of interacting with users and carrying out specific tasks.

[1078] A "virtual space" is a three-dimensional computer-generated digital environment in which users can interact.

[1079] An "influential person" is someone who has played an important role in history or in the present day and whose actions and thoughts have had a major impact on society and the economy.

[1080] "Emotion recognition" is a technology that analyzes a user's facial expressions and voice to identify their emotional state.

[1081] A "prompt sentence" is a question or instruction sentence that a user inputs to a system, and is input data that the system uses to generate an appropriate response.

[1082] "Future prediction" is a technique for predicting future events and situations based on past and present data.

[1083] "Hypothesis verification and visualization" is a technique that formulates a hypothesis, verifies it through simulation and data analysis, and visually displays the results.

[1084] This invention is a system that builds a platform that enables historical reproduction and allows users to interactively experience historical events and people. Specific embodiments of this system are described below.

[1085] Hardware and software used

[1086] Hardware: High-performance servers, user devices (PCs, smartphones)

[1087] Software: emotion engine, generative AI model, database management system (DBMS), game engine (Unity or Unreal Engine)

[1088] System configuration

[1089] 1. The server collects historical data from the past to the present and stores it in a database. This data includes historical events, demographics, cultural background, etc. Specifically, it retrieves the data using an API and stores it in a DBMS such as MySQL or PostgreSQL.

[1090] 2. The server generates a virtual space along a timeline based on the stored historical data. It uses a game engine such as Unity or Unreal Engine to build the 3D virtual space. It analyzes the data and generates appropriate models to recreate the geographical layout, historical buildings, people, and other elements within the virtual space.

[1091] 3. The server places AIs in the virtual space in numbers equivalent to the total world population. These AIs have individual thoughts and act independently using generative AI models (such as GPT-4). Initial settings are made for each AI, and historical background and cultural information is input.

[1092] 4. When a user accesses the system, the device activates the emotion engine, which analyzes the user's facial expressions and voice to recognize emotions. It uses a camera and microphone to capture the user's facial expressions and tone of voice and sends the analysis results to the server.

[1093] 5. The server adjusts the behavior of the AI ​​in the virtual space based on the user's emotional data obtained from the emotion engine. If the user is feeling happy, the AI ​​will share that joy and act to make the interaction with the user more enjoyable. If the user is feeling sad, the AI ​​will understand that sadness and act to comfort the user.

[1094] 6. The user asks the system a question about a particular historical event or person by entering a prompt sentence, for example, "Tell me about World War II."

[1095] 7. The server analyzes the user's prompt and uses artificial intelligence to provide appropriate information. The artificial intelligence provides detailed information in response to the user's question, improving the user's learning experience through dialogue.

[1096] Specific examples

[1097] For example, a user might input a prompt such as, "I would like to know more about Renaissance art." The device analyzes the user's facial expressions and tone of voice and recognizes that the user is excited. Based on the emotional data, the server instructs the AI ​​in the virtual space to share the user's excitement and make the conversation more interesting. The AI ​​then provides detailed information about Renaissance art and answers the user's questions. For example, it might explain, "Leonardo da Vinci is a representative painter of the Renaissance. One of his most famous works is the Mona Lisa."

[1098] In this way, users can have an emotionally responsive and interactive learning experience.

[1099] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1100] Step 1:

[1101] The server collects historical data from the past to the present and stores it in a database. Specifically, it uses an API to obtain data such as historical events, demographics, and cultural background. The input is data from the internet and databases, and the output is stored in a database management system (DBMS). For example, DBMSs such as MySQL or PostgreSQL are used.

[1102] Step 2:

[1103] The server generates a virtual space along a timeline based on the stored historical data. Specifically, it uses game engines such as Unity or Unreal Engine to build a 3D virtual space. The input is historical data stored in a database, and the output is a generated virtual space. The data is analyzed and appropriate models are generated to recreate the geographical layout, historical buildings, people, and other elements within the virtual space.

[1104] Step 3:

[1105] The server places a number of AIs within the virtual space equivalent to the total world population. These AIs have individual thoughts and act independently using a generative AI model (such as GPT-4). The inputs are the generative AI model and historical data, and the output is the AIs placed within the virtual space. Initial settings are made for each AI, and historical background and cultural information are input.

[1106] Step 4:

[1107] When a user accesses the system, the device starts the emotion engine. The emotion engine analyzes the user's facial expressions and voice to recognize emotions. The input is the user's facial expressions and voice, and the output is analyzed emotion data. Specifically, the system uses a camera and microphone to capture the user's facial expressions and tone of voice, and sends the analysis results to the server.

[1108] Step 5:

[1109] The server adjusts the behavior of the AI ​​in the virtual space based on the user's emotional data obtained from the emotion engine. The input is the emotional data, and the output is the adjusted behavior of the AI. If the user is feeling happy, the AI ​​will share that joy and act to make the interaction with the user more enjoyable. If the user is feeling sad, the AI ​​will understand that sadness and act to comfort the user.

[1110] Step 6:

[1111] Users ask questions about particular historical events or people by entering prompts into the system. The input is the prompt entered by the user, and the output is the prompt sent to the server. For example, "Tell me about World War II."

[1112] Step 7:

[1113] The server uses artificial intelligence to analyze the user's prompt and provide appropriate information. The input is the prompt and the generative AI model, and the output is the information provided to the user. The AI ​​provides detailed information in response to the user's question, improving the user's learning experience through dialogue. For example, it might explain, "Leonardo da Vinci is a representative painter of the Renaissance period. One of his most famous works is the Mona Lisa."

[1114] (Application example 1)

[1115] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1116] Conventional history learning systems and virtual space systems have had the problem of making it difficult for users to empathize with or gain a deep understanding of historical events and people when learning about them. In addition, there has been a lack of systems that allow interactive dialogue based on the user's emotions, which has limited the learning effect.

[1117] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for building a platform that enables historical reproduction; means for generating AIs with individual thoughts equivalent to the total world population, placing them in a virtual space, and allowing them to act independently; means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue; means for realistically verifying and visualizing various hypotheses to help predict the future; means for recognizing user emotions and adjusting the AI's behavior based on those emotions; and means for the user to interact with historical events and people via their smartphone and deepen their learning through an emotion engine. This allows the user to learn more about historical events and people while gaining emotional empathy.

[1118] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present.

[1119] "AI with individual thoughts" is artificial intelligence that has its own unique thought patterns and acts independently.

[1120] A "virtual space" is a digital environment generated by a computer that users can experience interactively.

[1121] An "influential person" is someone who has played an important role in history or in the present day, and whose thoughts and actions have a great influence on others.

[1122] An "emotion engine" is a technology that recognizes the user's emotions and adjusts the system's behavior based on those emotions.

[1123] A "smartphone" is a multi-functional mobile device that can connect to the Internet and run applications in addition to the functions of a mobile phone.

[1124] "Dialogue" is two-way communication between a user and a system (or AI).

[1125] "Deepening learning" refers to users gaining a deeper understanding and mastering specific knowledge or skills.

[1126] "Hypothesis verification and visualization" is the process of actually testing a hypothesis and visually displaying the results.

[1127] "Future forecasting" refers to predicting future events or situations based on current data and trends.

[1128] The system for implementing this invention is configured as follows: The server builds a platform that enables the reproduction of history, generates AIs with individual thoughts equivalent to the total world population, and places them in a virtual space. These AIs act independently, inheriting the specific thoughts and actions of influential people and enabling dialogue. In addition, various hypotheses can be verified and visualized in real time, which can be used to predict the future.

[1129] Furthermore, it is equipped with an emotion engine that recognizes the user's emotions and adjusts the AI's behavior based on those emotions. Users can interact with historical events and people through their smartphones and deepen their learning through the emotion engine.

[1130] Specifically, the server was developed using Python and provides a smartphone application. This application receives user emotions as input and adjusts the behavior of historical AI characters accordingly. When a user inputs an emotion such as "happy" or "sad," the AI ​​character responds accordingly. It also provides users with randomly selected historical events.

[1131] The hardware used is a smartphone, and the software uses Python. Data processing generates responses from AI characters based on user emotional data, and data calculation randomly selects historical events.

[1132] As a concrete example, the prompt text when the user enters "happy" is shown below.

[1133] python

[1134] Prompt Sentence Examples

[1135] user_emotion = "happy"

[1136] historical_figure = HistoricalAI("Historical Figure", 1732, 1799)

[1137] response = historical_figure.respond_to_emotion(user_emotion)

[1138] event = historical_figure.historical_event()

[1139] print(response)

[1140] print(f"Historical Event: {event}")

[1141] When you run this prompt, you will get the following output:

[1142] Historical Figure is happy to see you happy!

[1143] Historical Event: The signing of the Declaration of Independence in 1776.

[1144] In this way, users can learn about historical events while sharing emotions with historical AI characters.

[1145] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1146] Step 1:

[1147] A user starts the application using a smartphone. The user selects their emotion on the emotion input screen and inputs an emotion such as "happy" or "sad." The input data is sent to the emotion engine.

[1148] Step 2:

[1149] The server uses an emotion engine to analyze the emotion data entered by the user. The emotion engine classifies the user's emotions into categories such as "happy" or "sad," and generates data to adjust the AI ​​character's behavior based on the results. The input is the user's emotion data, and the output is behavioral instruction data for the AI ​​character.

[1150] Step 3:

[1151] The server updates the AI ​​character's emotional state based on the AI ​​character's behavior instruction data. Specifically, it sets the AI ​​character's emotional attribute to "happy" or "sad" and generates a response message accordingly. The input is the behavior instruction data, and the output is the response message.

[1152] Step 4:

[1153] The server randomly selects an event from the historical event database. The selected event is prepared to be provided to the user. The input is unconditional, and the output is a randomly selected historical event.

[1154] Step 5:

[1155] The server combines the generated response message with a randomly selected historical event to generate data to send to the user. The input is the response message and the historical event, and the output is the final message sent to the user.

[1156] Step 6:

[1157] The device (smartphone) displays the final message received from the server to the user. The user can view the AI ​​character's response message and historical events, gaining emotional empathy and deepening their learning. The input is the final message from the server, and the output is the information displayed to the user.

[1158] Example 2

[1159] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1160] In order to inherit modern management and historical knowledge and utilize it for future decision-making, it is necessary to effectively learn and emulate the thinking and behavioral patterns of influential people. It is also necessary to gain a deeper understanding and take appropriate action through the verification and visualization of hypotheses based on user emotions. However, there is no system yet in place to efficiently and accurately realize these processes.

[1161] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting data on influential people, means for preprocessing the collected data, means for training a generative AI model using the preprocessed data, means for generating an AI that imitates the thoughts and actions of influential people using the trained model, means for collecting user emotional data, means for analyzing the collected emotional data and identifying the user's emotional state, means for formulating hypotheses based on the user's emotional state and verifying the hypotheses, and means for visualizing the results of the hypothesis verification. This makes it possible to inherit the knowledge and management decisions of influential people and verify and visualize hypotheses based on user emotions.

[1162] An "influential person" is someone who plays an important role in society or an organization and whose thoughts and actions have a great influence on others.

[1163] "Data collection" is the process of gathering information needed for a specific purpose from various sources.

[1164] "Preprocessing" is a series of operations used to convert collected data into a format suitable for analysis and learning.

[1165] A "generative AI model" is an artificial intelligence model that generates new information and predictions based on given data.

[1166] "Learning" is the process by which an AI model finds patterns and rules in the data it is given and uses them to improve its performance.

[1167] "Imitation" means reproducing the behavior and thought patterns of a particular person or system.

[1168] "Emotion data" is information that indicates the user's emotional state, and is obtained from facial expressions, voice, text, and the like.

[1169] "Analysis" is the process of examining collected data in detail to understand its meaning and patterns.

[1170] A "hypothesis" is a prediction or premise made to explain an observed phenomenon.

[1171] "Verification" is the process of confirming whether a hypothesis is correct.

[1172] "Visualization" is the representation of data or information in a visual format such as a graph or chart.

[1173] This invention includes a system that learns the thinking and behavior patterns of influential people and generates AI that imitates them, and a system that verifies and visualizes hypotheses based on user emotion data. Specific embodiments of this system are described below.

[1174] Learning and imitating the thinking and behavior patterns of influential people

[1175] Data collection

[1176] The server collects data on influential people, specifically from books, interviews, lecture notes, and social media posts by business leaders and historical figures. The software used is web scraping tools (e.g., BeautifulSoup, Scrapy) and APIs (e.g., Twitter API).

[1177] Data Preprocessing

[1178] The server preprocesses the collected data, specifically cleaning the text, tokenizing it, removing stop words, etc. The software used is a natural language processing library (e.g., NLTK, spaCy).

[1179] Model training

[1180] The server uses the preprocessed data to train a generative AI model (e.g., GPT-4). This model mimics the thought and behavior patterns of influential people. The hardware used is a server equipped with a high-performance GPU (e.g., NVIDIA Tesla V100).

[1181] AI generation

[1182] The server uses the trained model to generate AI that mimics the thoughts and actions of influential people. The generated AI is deployed as an API, making it accessible to users and devices.

[1183] Hypothesis verification and visualization using emotion engine

[1184] Collecting user emotion data

[1185] The device collects the user's emotional data by analyzing the user's facial expressions, voice, and text input. The hardware used is a camera and microphone, and the software is an emotion analysis tool (e.g., Microsoft Azure Emotion API).

[1186] Emotional Data Analysis

[1187] The server analyzes the collected emotion data and identifies the user's emotional state using machine learning libraries (e.g., TensorFlow, PyTorch).

[1188] Hypothesis formulation and verification

[1189] The server generates hypotheses based on the user's emotional state. For example, if the user is feeling happy, it identifies the cause of that happiness. The server analyzes the user's emotional data and related contextual information (e.g., the movie scene the user is watching, the music the user is listening to, etc.) to generate hypotheses about the cause of the happiness. It then performs additional data collection and analysis to validate these hypotheses.

[1190] visualization

[1191] The server visualizes the hypothesis verification results by generating graphs and charts and presenting them to the user. The software used is a data visualization tool (e.g., Tableau, Matplotlib).

[1192] Examples and prompts

[1193] Specific examples

[1194] AI-generated managers:

[1195] The server collects lecture notes and interviews of a certain manager and generates an AI that learns his thought patterns. When a user asks a question about management, this AI provides answers that sound like the manager would.

[1196] Using the Emotion Engine:

[1197] The device uses a camera to analyze the user's facial expressions while watching a movie and identifies when the user feels joy at a particular scene. The server then analyzes the elements of that scene (music, characters, storyline, etc.) and hypothesizes the cause of the joy.

[1198] Prompt Sentence Examples

[1199] AI-generated managers:

[1200] "Please generate an AI that has learned the thought patterns of a certain CEO. Use his lecture transcripts and interviews as data."

[1201] Using the Emotion Engine:

[1202] "Collect emotional data while users are watching a movie, analyze the elements of the scene that evoke pleasure, and develop a hypothesis to identify the source of pleasure."

[1203] The above is a specific embodiment for carrying out the present invention.

[1204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1205] Step 1: Data collection

[1206] The server collects data on influential people. Specifically, it targets books, interviews, lecture notes, and social media posts by business leaders and historical figures. The software used is a web scraping tool (e.g., BeautifulSoup, Scrapy) or an API (e.g., Twitter API). The input is the name of the person in question and related keywords, and the output is the collected text data.

[1207] Step 2: Data Preprocessing

[1208] The server preprocesses the collected data. Specifically, it performs text cleaning, tokenization, and stop word removal. The software used is a natural language processing library (e.g., NLTK, spaCy). The input is the collected text data, and the output is the preprocessed, clean text data.

[1209] Step 3: Training the model

[1210] The server uses the preprocessed data to train a generative AI model (e.g., GPT-4). This model mimics the thought and behavior patterns of influential people. The hardware used is a server equipped with a high-performance GPU (e.g., NVIDIA Tesla V100). The input is preprocessed text data, and the output is a trained generative AI model.

[1211] Step 4: Generate AI

[1212] The server uses the trained model to generate AI that mimics the thoughts and actions of influential people. The generated AI is deployed as an API, making it accessible to users and devices. The input is the trained generative AI model, and the output is the deployed AI service.

[1213] Step 5: Collecting user emotion data

[1214] The device collects the user's emotional data. Specifically, it analyzes the user's facial expressions, voice, text input, etc. The hardware used is a camera and microphone, and the software is an emotion analysis tool (e.g., Microsoft Azure Emotion API). The input is the user's real-time data (facial expressions, voice, text), and the output is analyzed emotional data.

[1215] Step 6: Analyze the sentiment data

[1216] The server analyzes the collected emotion data and identifies the user's emotional state. The software used is a machine learning library (e.g., TensorFlow, PyTorch). The input is the analyzed emotion data, and the output is the identified emotional state (e.g., joy, sadness, anger, etc.).

[1217] Step 7: Hypothesis formulation and testing

[1218] The server generates hypotheses based on the user's emotional state. For example, if the user is feeling happy, it identifies the cause of that happiness. The server analyzes the user's emotional data and related contextual information (e.g., the movie scene the user is watching, the music the user is listening to, etc.) to generate hypotheses about the cause of the happiness. It then performs additional data collection and analysis to verify this hypothesis. The input is the identified emotional state and related contextual information, and the output is the verified hypothesis.

[1219] Step 8: Visualization

[1220] The server visualizes the results of the hypothesis verification. Specifically, it generates graphs and charts and presents them to the user. The software used is a data visualization tool (e.g., Tableau, Matplotlib). The input is the verified hypothesis, and the output is the visualized data (graphs, charts).

[1221] (Application example 2)

[1222] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1223] In today's business environment, it is difficult to inherit the knowledge and management decisions of influential business leaders and historical figures. It is also difficult to recognize customer sentiment in real time and provide optimal advice based on that sentiment. Furthermore, the lack of means to display management advice in real time using smart devices hinders rapid decision-making on the ground. A system that can solve these issues is needed.

[1224] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1225] In this invention, the server includes means for building a platform that enables the reproduction of history, means for generating AIs with individual thoughts equivalent to the total population of the world, placing them in a virtual space, and making them act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for recognizing users' emotions and providing optimal advice based on those emotions, and means for displaying management advice in real time using a smart device.This makes it possible to inherit the knowledge and management decisions of influential people and provide optimal advice based on customer emotions in real time.

[1226] A "platform that enables historical reenactment" is a system that recreates past events and the actions of people in a virtual space, allowing users to experience them.

[1227] "AI with individual thoughts" refers to artificial intelligence that has its own individual personality and thought patterns and acts independently.

[1228] "Inheriting the specific thoughts and actions of influential people and turning them into AI" means creating an AI that learns the thought patterns and actions of historical figures and famous business leaders and imitates them.

[1229] "Means to realistically verify and visualize hypotheses to help predict the future" refers to a technology that formulates hypotheses, verifies them through simulations and data analysis, and visually displays the results to help predict the future.

[1230] "Means for recognizing the user's emotions and providing optimal advice based on those emotions" refers to a system that analyzes the user's emotions from their facial expressions and voice, and generates appropriate advice based on those emotions.

[1231] "Means for displaying management advice in real time using a smart device" refers to technology that displays management advice in real time using devices such as smart glasses or smartphones.

[1232] The following system configuration is used as an embodiment of the present invention.

[1233] System Configuration

[1234] 1. Server:

[1235] The server will build a platform that will enable the re-creation of history, and will generate AIs with individual thoughts equivalent to the total population of the world, placing them in a virtual space.

[1236] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue.

[1237] The server will realistically verify and visualize various hypotheses, helping to predict the future.

[1238] The server recognizes the user's emotions and provides optimal advice based on those emotions.

[1239] The server displays management advice in real time using smart devices.

[1240] Hardware and software used

[1241] Hardware:

[1242] Smart glasses (with camera)

[1243] Server (with high-performance computing power)

[1244] software:

[1245] OpenAI API

[1246] Emotion Recognition Library

[1247] Data processing and calculation

[1248] 1. User Emotion Recognition:

[1249] Images of customers taken with the smart glasses camera are analyzed using the Emotion Recognition library to recognize the customer's emotions.

[1250] 2. Prompt generation:

[1251] Based on the perceived emotions and store scenarios, prompts are created to generate advice from the perspective of influential business owners.

[1252] 3. Advice Generation:

[1253] Uses the OpenAI API to generate management advice based on the generated prompts.

[1254] 4. Advice display:

[1255] The generated advice is displayed on the display of the smart glasses.

[1256] Specific examples

[1257] scenario

[1258] Scenario: New product promotion

[1259] Customer Emotion: Delight

[1260] Prompt Sentence Examples

[1261] Customers' emotions are delighted. Please provide the best advice from the perspective of an influential business executive on promoting new products.

[1262] This system makes it possible to inherit the knowledge and management decisions of influential people and provide optimal advice based on customer emotions in real time.

[1263] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1264] Step 1:

[1265] User Emotion Recognition

[1266] Input: An image of the customer taken by the camera in the smart glasses

[1267] Processing: The device (smart glasses) uses the Emotion Recognition library to analyze the customer's image and recognize their emotions. Specifically, it extracts facial features in the image and classifies emotions such as joy, sadness, and anger.

[1268] Output: Perceived customer emotion (e.g., joy)

[1269] Step 2:

[1270] Prompt Generation

[1271] Input: Perceived customer sentiment (output of step 1) and store scenarios (e.g., new product promotions)

[1272] Processing: Based on the input emotions and scenarios, the server creates prompts to generate advice from the perspective of influential business leaders. Specifically, it generates sentences that combine emotions and scenarios.

[1273] Output: Generated prompt (e.g., "The customer's emotion is joy. Please provide the best advice from the perspective of an influential executive regarding the promotion of a new product.")

[1274] Step 3:

[1275] Advice Generation

[1276] Input: Generated prompt statement (output of step 2)

[1277] Processing: The server uses the OpenAI API to generate management advice based on the prompt sentence. Specifically, the prompt sentence is sent to the API, and the generative AI model returns appropriate advice.

[1278] Output: Generated management advice (e.g., "When promoting a new product, it is effective to offer special discounts to elicit customer delight.")

[1279] Step 4:

[1280] Advice display

[1281] Input: Generated management advice (output of Step 3)

[1282] Processing: The terminal (smart glasses) displays the generated management advice on the display. Specifically, the text of the advice is displayed on the display of the smart glasses in real time.

[1283] Output: Business advice displayed on the smart glasses display

[1284] In this way, users can receive optimal management advice based on customer sentiment in real time.

[1285] Example 3

[1286] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1287] In conventional systems, it was difficult to take user emotions into account when verifying hypotheses or making future predictions, and it was also difficult to visualize simulation results in real time in a virtual space. Furthermore, because scenario generation using a generative AI model and emotion analysis using an emotion engine were not integrated, there was an issue of not being able to respond appropriately based on user emotions.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1289] In this invention, the server includes a means for a user to input a specific hypothesis, a means for generating a scenario based on the hypothesis using a generative AI model, a means for executing the scenario using virtual space simulation software, a means for visualizing the simulation results, a means for using an emotion engine to input and analyze the user's emotions, and a means for adjusting the behavior of the AI ​​based on the emotion analysis results. This allows the user's hypothesis to be verified in real time and used to predict the future. It also enables appropriate responses based on the user's emotions.

[1290] A "platform" is an underlying system or environment built to achieve a specific purpose.

[1291] "Artificial intelligence" refers to computer programs that mimic human intelligence and can learn, reason, and solve problems.

[1292] A "virtual space" is a three-dimensional simulated environment generated by a computer.

[1293] A "generative AI model" is a machine learning model trained to perform tasks such as natural language processing or image generation.

[1294] A "scenario" is a simulation of a series of events or circumstances based on a particular hypothesis.

[1295] "Simulation" is a technology that simulates and reproduces real-world phenomena and processes.

[1296] "Visualization" is a technique that makes data and information easier to understand by visually representing them.

[1297] An "emotion engine" is software that analyzes a user's emotions and responds appropriately based on the results.

[1298] "Sentiment analysis" is the process of identifying emotions from user input and behavior and analyzing the causes and effects of those emotions.

[1299] "Behavioral adjustment" is the process of changing the behavior of artificial intelligence based on the analysis results and taking appropriate action.

[1300] This invention is a system in which an AI acts autonomously in a virtual space, setting scenarios based on specific hypotheses and observing the results to obtain information useful for formulating business strategies and predicting the future. It also has a function to adjust the AI's behavior based on the user's emotions using an emotion engine.

[1301] Hardware and software used

[1302] Hardware: High-performance server (e.g., GPU-equipped server)

[1303] software:

[1304] Virtual space simulation software (e.g. Unity, Unreal Engine)

[1305] Emotion engines (e.g., Affectiva, IBM Watson Tone Analyzer)

[1306] Generative AI models (e.g., GPT-4)

[1307] Explanation of program processing

[1308] 1. Enter your hypothesis

[1309] The user inputs a specific hypothesis into the system, for example, "the impact of launching a new product on sales."

[1310] The terminal receives the user's input and sends it to the server.

[1311] 2. Scenario generation

[1312] Based on the hypotheses received by the server, a scenario is generated using a generative AI model (e.g., GPT-4).

[1313] The server sends the generated scenario to the virtual space simulation software (e.g., Unity).

[1314] As a specific operation, the server generates a scenario in which a new product is introduced to the market and consumer reactions are observed.

[1315] 3. Running a simulation in virtual space

[1316] The server starts the virtual space simulation software and executes the generated scenario.

[1317] The server controls the AI ​​characters to act independently and monitors the progress of the scenario.

[1318] Specifically, the system simulates the process of a new product being released to the market in a virtual space and consumers purchasing the product.

[1319] 4. Visualizing the results

[1320] The server aggregates the simulation results and displays them using a visualization tool.

[1321] The terminal displays the visualized results to the user.

[1322] Specific actions include displaying sales fluctuation graphs and consumer feedback.

[1323] 5. Emotion Input and Analysis

[1324] The user inputs their feelings about the simulation results. For example, if they feel "anger," they input that emotion.

[1325] The device receives the user's emotion input and transmits it to the server.

[1326] The server uses an emotion engine (e.g., Affectiva) to analyze the user's emotions.

[1327] Specifically, the user inputs "anger" and the emotion engine analyzes the cause of that anger.

[1328] 6. Emotion-based behavioral regulation

[1329] The server adjusts the behavior of the artificial intelligence based on the analysis results of the emotion engine.

[1330] The server generates a new scenario and sends it to the virtual space simulation software.

[1331] Specifically, the cause of the user's anger is identified as "the price of the new product is too high," and a new scenario is generated to adjust the price.

[1332] Specific examples

[1333] Hypothesis input: The user inputs "the impact of launching a new product on sales."

[1334] Scenario generation: The server generates a scenario that involves "launching a new product on the market and observing consumer reactions."

[1335] Simulation execution: A simulation is performed in a virtual space to see how a new product is launched on the market and how consumers purchase it.

[1336] Visualize results: Display sales fluctuation graphs and consumer feedback.

[1337] Emotion input and analysis: The user inputs "anger" and the emotion engine analyzes the cause.

[1338] Behavioral adjustment: The cause of the user's anger is identified as "the price of the new product is too high," and a new scenario is generated in which the price is adjusted.

[1339] Prompt Sentence Examples

[1340] "Simulate the impact of introducing a new product to the market on sales."

[1341] "Analyze the cause of the user's anger and generate a scenario to resolve that cause."

[1342] This system allows users to realistically verify hypotheses and use them to predict the future. Furthermore, by using an emotion engine, appropriate responses based on the user's emotions become possible. The flow of the identification process in Example 3 will be described with reference to FIG. 21.

[1343] Step 1:

[1344] Entering a hypothesis

[1345] The user inputs a specific hypothesis into the system, for example, "the impact of launching a new product on sales."

[1346] The terminal receives the user's input and sends it to the server.

[1347] Input: User-entered hypotheses

[1348] Output: Hypothetical data sent to the server

[1349] Step 2:

[1350] Scenario generation

[1351] Based on the hypotheses received by the server, a scenario is generated using a generative AI model (e.g., GPT-4).

[1352] The server sends the generated scenario to the virtual space simulation software (e.g., Unity).

[1353] Input: Hypothetical data

[1354] Data processing: Generate scenarios using generative AI models

[1355] Output: Generated scenario data

[1356] Step 3:

[1357] Running a simulation in virtual space

[1358] The server starts the virtual space simulation software and executes the generated scenario.

[1359] The server controls the AI ​​characters to act independently and monitors the progress of the scenario.

[1360] Input: Generated scenario data

[1361] Data calculation: Execute scenarios in virtual space and simulate the actions of AI characters

[1362] Output: Simulation result data

[1363] Step 4:

[1364] Visualizing the results

[1365] The server aggregates the simulation results and displays them using a visualization tool.

[1366] The terminal displays the visualized results to the user.

[1367] Input: Simulation result data

[1368] Data processing: Processing the resulting data with a visualization tool

[1369] Output: Visualized results (e.g., sales fluctuation graphs, consumer feedback)

[1370] Step 5:

[1371] Emotion input and analysis

[1372] The user inputs their feelings about the simulation results. For example, if they feel "anger," they input that emotion.

[1373] The device receives the user's emotion input and transmits it to the server.

[1374] The server uses an emotion engine (e.g., Affectiva) to analyze the user's emotions.

[1375] Input: User emotion data

[1376] Data Calculation: Emotion Analysis Using an Emotion Engine

[1377] Output: Emotion analysis results

[1378] Step 6:

[1379] Emotion-based behavioral regulation

[1380] The server adjusts the behavior of the artificial intelligence based on the analysis results of the emotion engine.

[1381] The server generates a new scenario and sends it to the virtual space simulation software.

[1382] Input: Sentiment analysis results

[1383] Data processing: Generative AI models are used to generate new scenarios

[1384] Output: Adjusted scenario data

[1385] In this way, the user, terminal, and server work together at each step to create a system that verifies hypotheses and predicts the future.

[1386] (Application example 3)

[1387] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1388] Conventional AI systems in virtual spaces have difficulty responding in real time based on user emotions, and lack specific methods for improving the shopping experience, especially in physical stores. Furthermore, when formulating business strategies or making future predictions, scenarios that take user emotions into account were not set, so more accurate predictions were needed.

[1389] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for building a platform that enables historical reproduction, means for generating AIs with individual thoughts equivalent to the total world population and placing them in a virtual space to allow them to act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, and means for analyzing user emotions in real time and providing optimal product suggestions and services based on those emotions. This enables real-time responses that take user emotions into consideration, improving the shopping experience in physical stores and enabling the formulation of more accurate management strategies and future predictions.

[1390] A "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and learn within it.

[1391] "AI with individual thoughts" refers to artificial intelligence that has its own individual personality and thought patterns and acts independently.

[1392] A "virtual space" is a three-dimensional computer-generated digital environment in which users can interact.

[1393] An "influential person" is someone who has played an important role in history or the modern day and has influenced many people.

[1394] "Inheriting specific thoughts and actions to create AI" means incorporating the thought patterns and behavioral characteristics of a specific person into artificial intelligence, and generating AI that behaves like that person.

[1395] "Means enabling dialogue" refers to a function that allows users and AI to communicate using natural language.

[1396] "Realistic verification and visualization of hypotheses" means executing a scenario based on a specific hypothesis in a virtual space and visually displaying the results.

[1397] "Means for predicting the future" are methods for predicting future events and situations based on the results of hypothesis verification.

[1398] "Analyzing user emotions in real time" means analyzing the user's facial expressions and behavior in real time to identify their emotional state.

[1399] "Means for providing optimal product suggestions and services" refers to a function that selects and suggests appropriate products and services based on the user's emotional state.

[1400] The following system configuration will be described as an embodiment of the present invention.

[1401] System Configuration

[1402] 1. Hardware Configuration

[1403] Server: A server with high-performance computing power is required to train the AI ​​model and manage the virtual space.

[1404] Device: A device such as a smartphone or tablet is required. It is desirable for these devices to be equipped with a camera and microphone.

[1405] Network: A high-speed internet connection is required to connect the server and your device.

[1406] 2. Software Configuration

[1407] AI Model: A generative AI model is required for emotion recognition and behavior prediction, specifically using a deep learning framework such as Keras or TensorFlow.

[1408] Virtual space management software: Build virtual spaces using game engines such as Unity and Unreal Engine.

[1409] Emotion analysis software: OpenCV is used to detect faces from camera footage and input them into an emotion recognition model.

[1410] REST API: Use the API to obtain product and service information.

[1411] Processing flow

[1412] 1. Server Processing

[1413] The server will manage the virtual space and train the AI ​​models. Specifically, it will build a platform that enables historical reenactment and generate AIs with individual thoughts, equivalent to the total world population, and place them in the virtual space.

[1414] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue.

[1415] 2. Terminal Processing

[1416] The device captures camera footage and inputs it into an emotion recognition model to analyze the user's emotions in real time.

[1417] Based on the emotion recognition results, the device retrieves optimal product suggestions and service information via a REST API and displays them to the user.

[1418] 3. User Operation

[1419] Users scan their face using their smartphone camera, which allows the device to analyze their emotions and suggest appropriate products and services.

[1420] Specific examples

[1421] For example, when a user scans their face using their smartphone camera while shopping in a physical store, the application analyzes the user's emotions and, if they are feeling angry, suggests products with a relaxing effect (aroma candles or relaxation goods).

[1422] Prompt Sentence Examples

[1423] Design a system in which a user scans their face using their smartphone camera while shopping in a physical store, and the application analyzes the user's emotions. For example, if the user is feeling "anger," the system suggests products with a relaxing effect (aroma candles or relaxation goods).

[1424] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1425] Step 1:

[1426] The server manages the virtual space and trains the AI ​​model. Specifically, it builds a platform that enables historical reproduction, generates AI with individual thoughts equivalent to the total world population, and places them in the virtual space. Past historical data and demographic data are used as input, and the output is the generation of AI agents that can act autonomously within the virtual space.

[1427] Step 2:

[1428] The server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. The input is the history of the influential person's actions and statements, and the output is an AI agent that behaves like that person.

[1429] Step 3:

[1430] The device captures camera footage and inputs it into an emotion recognition model for real-time analysis of the user's emotions. The input is video data acquired from the smartphone camera, and the output is identifying the user's emotional state (e.g., anger, joy, sadness, etc.).

[1431] Step 4:

[1432] Based on the emotion recognition results, the device retrieves optimal product suggestions and service information via a REST API and displays it to the user. The emotion recognition results and the user's current location information are used as input, and a list of appropriate products and services is generated as output.

[1433] Step 5:

[1434] Users scan their face using their smartphone camera, which allows the device to analyze the user's emotions and suggest appropriate products and services. The input is the user's facial image, and the output is the emotion analysis results and product suggestions based on them.

[1435] Step 6:

[1436] The terminal displays the retrieved product information and service information to the user. As input, it uses the product information and service information retrieved from the REST API, and as output, it generates a product list or service list to be displayed on the user's smartphone screen.

[1437] Step 7:

[1438] The user checks the proposed products and services and purchases or uses them as necessary. The product and service information displayed on the terminal is used as input, and the user's purchasing behavior and service usage behavior are obtained as output.

[1439] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1440] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1441] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1442] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1443] [Third embodiment]

[1444] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1445] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1446] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1447] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1448] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1449] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1450] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1451] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1452] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1453] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1454] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1455] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1456] "Example 1"

[1457] As an embodiment of the present invention, we will build a platform that enables the reproduction of history. This platform will generate a virtual space along a timeline based on historical data from the past to the present. In this virtual space, AIs equivalent to the total world population will be placed. These AIs will have their own individual thoughts and will act independently.

[1458] "Example 2"

[1459] Furthermore, the specific thoughts and actions of influential people can be inherited and turned into AI. Specifically, the AI ​​learns the thought patterns and behaviors of business leaders and historical figures and imitates them. This makes it possible to inherit the knowledge and management decisions of business leaders even after they retire. It is also possible to obtain new management hints through dialogue with historical figures.

[1460] "Example 3"

[1461] Furthermore, various hypotheses can be realistically verified and visualized to aid in future predictions. Specifically, scenarios based on specific hypotheses are set in a virtual space where AI acts autonomously, and the results are observed. This makes it possible to obtain information that is useful for formulating business strategies and making future predictions.

[1462] The processing flow of each embodiment will be described below.

[1463] "Example 1"

[1464] Step 1: Collect historical data from the past to the present. This data includes information about people's behavior, events, technological advances, and other time-based information.

[1465] Step 2: Based on the collected historical data, a virtual space along a timeline is generated. This virtual space will become a platform that enables historical reconstruction.

[1466] Step 3: Create a number of AIs equivalent to the total population of the world. These AIs will have their own thoughts and behave independently.

[1467] Step 4: Place the generated AI in a virtual space, creating an environment in which the AI ​​can act autonomously to recreate history.

[1468] "Example 2"

[1469] Step 1: Learn the thought and behavior patterns of influential people. Specifically, extract the thought and behavior patterns from the statements and actions of business leaders and historical figures. Step 2: Generate AI that imitates the extracted thought and behavior patterns.

[1470] Step 3: The generated AI is placed in a virtual space, allowing interaction with the AI ​​that inherits the thoughts and actions of influential people.

[1471] "Example 3"

[1472] Step 1: Create a scenario based on a specific hypothesis. This scenario will serve as a guide for the AI ​​to act autonomously in a virtual space.

[1473] Step 2: The AI ​​acts independently based on the set scenario.

[1474] Step 3: Observe the results of AI actions and analyze the results, which will enable us to obtain information that will be useful for formulating business strategies and making future predictions.

[1475] Example 1

[1476] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1477] With current technology, it is difficult to realistically recreate past history and allow users to experience and learn from it. It is also difficult to inherit the thoughts and actions of influential historical figures and interact with them in a virtual space. Furthermore, there is a lack of means to verify hypotheses and make realistic predictions about the future, making it difficult to use for formulating business strategies or predicting the future.

[1478] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1479] In this invention, the server includes means for building a platform that enables historical reproduction, means for collecting historical data from the past to the present and storing it in a database, means for generating a virtual space along a timeline based on the collected data, means for generating AIs with individual thoughts equivalent to the total world population and placing them in the virtual space and making them act autonomously, means for customizing and displaying the virtual space based on user requests, means for users to interact with AI agents in the virtual space and obtain information, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help predict the future.This allows users to realistically experience and learn about past history, interact with influential historical figures, and further verify hypotheses and make realistic predictions about the future.

[1480] The "platform that enables historical reproduction" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience and learn within it.

[1481] "Historical data" refers to information about history, such as past events, demographics, cultural background, and geographic information.

[1482] A "database" is a collection of information that stores collected historical data and is indexed for rapid access through queries.

[1483] "Virtual space" is a three-dimensional digital space generated along a timeline based on collected historical data.

[1484] An "AI agent" is an artificial intelligence that uses a generative AI model to have individual thoughts and act independently.

[1485] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to communicate with users and other AI agents.

[1486] A "User Request" is a request submitted by a User to the Platform specifying a particular historical period or location.

[1487] "Customization" means adjusting the virtual space based on the user's requests and generating detailed scenes relating to specific times and places.

[1488] An "influential person" is someone who has had a major impact in a particular field, such as someone who played an important role in history or a business leader.

[1489] "Hypothesis testing" involves trying out various scenarios in a virtual space and observing the results.

[1490] "Future prediction" is the prediction of future events or situations based on the results of hypothesis verification.

[1491] MODE FOR CARRYING OUT THE INVENTION

[1492] The present invention aims to build a platform that enables historical reproduction, allowing users to realistically experience and learn about past history. A specific embodiment of this system will be described below.

[1493] Generating a Program

[1494] The server generates a platform program that enables historical reproduction. This program has the function of generating a virtual space along a timeline based on historical data from the past to the present.

[1495] Program processing

[1496] The server first collects historical data and stores it in a database, which includes past events, demographics, cultural background, geographic information, etc. The collected data is stored in a database such as MongoDB or MySQL.

[1497] The server then uses this data to generate a virtual space. This virtual space is built using a game engine such as Unity or Unreal Engine. For example, to recreate 19th century Paris, the server places buildings, cityscapes, and scenery from that era into the virtual space. This is done using assets created in 3D modeling tools such as Blender.

[1498] AI agents equivalent in number to the world's total population are placed in the virtual space. These AI agents are configured to have individual thoughts and act autonomously using generative AI models (e.g., OpenAI's GPT-4). The AI ​​agents communicate with users and other AI agents using natural language processing (NLP) technology.

[1499] Specific examples

[1500] When a user accesses the platform using a device, the server generates a virtual space in response to the user's request and displays it on the device. For example, if a user requests a recreation of 19th century Paris, the server generates a virtual space based on data about 19th century Paris and displays it on the device.

[1501] As a concrete example, a user inputs the following prompt sentence into a generative AI model:

[1502] "Recreate life in 19th century Paris. I'd especially like to learn more about the construction of the Eiffel Tower."

[1503] The server receives this prompt and generates a virtual space based on data about 19th-century Paris, recreating the construction process of the Eiffel Tower in detail. The AI ​​agents act autonomously as workers and citizens of the time, providing real-time information to the user.

[1504] In this way, users can experience past history in a realistic way and interact with influential historical figures. They can also verify hypotheses and make realistic predictions about the future, which can be useful for formulating business strategies and forecasting the future.

[1505] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1506] Step 1:

[1507] The server collects historical data and stores it in a database.

[1508] Input: reliable data sources on the internet (e.g., historical databases and literature)

[1509] How it works: The server uses scraping technology to collect data such as historical events, demographics, cultural background, and geographic information. The collected data is then stored in a database such as MongoDB or MySQL.

[1510] Output: Archived historical data

[1511] Step 2:

[1512] The server generates a virtual space based on the collected data.

[1513] Input: Stored historical data

[1514] How it works: The server uses game engines such as Unity or Unreal Engine to generate 3D models based on the collected data. For example, to recreate 19th century Paris, it places 3D models of buildings and roads from that time. This uses assets created in 3D modeling tools such as Blender.

[1515] Output: Generated virtual space

[1516] Step 3:

[1517] The server places and configures AI agents within the virtual space.

[1518] Input: Generated virtual space, generative AI model

[1519] Specific operation: The server uses a generative AI model (e.g., GPT-4) to set an individual profile for each AI agent. For example, one AI agent is set as a worker in 19th century Paris, while others are set as citizens or merchants. This allows each AI agent to have different behavioral patterns.

[1520] Output: The configured AI agent

[1521] Step 4:

[1522] A user accesses the platform using a terminal and requests a particular historical period or location.

[1523] Input: User request (e.g., "I want a 19th century Paris re-created")

[1524] Specific operation: A user accesses the platform through a browser on their device and requests a specific time and location.

[1525] Output: User request data

[1526] Step 5:

[1527] The server customizes and displays the virtual space based on the user's request.

[1528] Input: User request data, generated virtual space

[1529] How it works: The server customizes the virtual space based on the user's request. For example, if a user requests 19th-century Paris, the server generates a detailed scene, including the construction of the Eiffel Tower, and streams it to the device in real time.

[1530] Output: Customized virtual space

[1531] Step 6:

[1532] Users explore the virtual space through their devices and interact with AI agents.

[1533] Input: A customized virtual space, a user prompt (e.g., "Tell me about the construction of the Eiffel Tower").

[1534] Specific operation: The user moves freely through the virtual space via the terminal and interacts with the AI ​​agent, which uses the generative AI model to respond and provide information in real time based on the user's prompts.

[1535] Output: Response from the AI ​​agent, user experience information

[1536] (Application example 1)

[1537] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1538] Conventional historical reenactment systems simply visually reproduce past events, making it difficult for users to interact with people from that era or move freely around and experience them. Furthermore, interactions within the virtual space are limited, making it impossible to generate real-time responses based on user input. Furthermore, the visual experience using a head-mounted display is insufficient, resulting in a lack of immersion.

[1539] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1540] In this invention, the server includes means for building a platform that enables the reproduction of history, means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to allow them to act independently, means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for enabling users to move freely within the virtual space and interact with AI characters, means for visually experiencing the virtual space using a head-mounted display, and means for generating responses from AI characters based on user input and displaying them in the virtual space, thereby enabling users to experience past historical events and eras in the virtual space and interact with AI characters.

[1541] The "platform that enables historical reenactment" is a system that generates a virtual space along a timeline based on historical data from the past to the present, allowing users to experience historical events within it.

[1542] "AI with individual thoughts" is artificial intelligence that has its own unique thought patterns and acts independently.

[1543] A "virtual space" is a three-dimensional digital space generated by a computer, in which users can move freely and interact.

[1544] An "influential person" is someone who has played an important role in history or in the present day, and whose thoughts and actions have a great influence on others.

[1545] "Means enabling dialogue" refers to a function that allows users to have natural conversations with AI characters.

[1546] "A means to realistically verify and visualize hypotheses to help predict the future" is a function that simulates various scenarios in a virtual space and visually displays the results, helping to predict the future and formulate strategies.

[1547] "Means that allow users to move freely and interact with AI characters" refers to a function that allows users to move freely within the virtual space and interact with placed AI characters.

[1548] A "head-mounted display" is a display device that the user wears on their head, allowing them to visually experience a virtual space.

[1549] "Means for generating responses from an AI character based on user input and displaying them in a virtual space" refers to a function that receives input from a user, generates responses from an AI character in real time in response to the input, and displays them in a virtual space.

[1550] The system for implementing this invention uses the following hardware and software: a head-mounted display (e.g., Oculus Rift, HTC Vive) as hardware, and a VR engine (e.g., Unity, Unreal Engine), OpenAI API, and a history database as software.

[1551] The server first builds a platform that enables historical reproduction. Specifically, it generates a virtual space along a timeline based on historical data from the past to the present. In this virtual space, it generates and places AIs with individual thoughts, in numbers equivalent to the total world population. These AIs act autonomously and are able to interact with users.

[1552] By wearing a head-mounted display, users can move freely within the virtual space and interact with AI characters. Based on the user's input, the server uses the OpenAI API to generate responses from the AI ​​characters and display them in the virtual space. This allows users to realistically experience past historical events and eras.

[1553] For example, if a user says, "I want to meet Napoleon," the server will generate an AI character of Napoleon in the virtual space and have it interact with the user. The following is an example of a prompt sentence:

[1554] User: I want to meet Napoleon

[1555] AI: Hello, I'm Napoleon Bonaparte. What question do you have?

[1556] In this way, users can interact with historical figures and experience past events. Hypothesis verification and visualization can also be used to predict the future and formulate strategies.

[1557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1558] Step 1:

[1559] The server loads historical data from the past to the present from the historical database. The input is the historical database, and the output is the loaded historical data. Specifically, the server executes a database query to obtain the required data.

[1560] Step 2:

[1561] The server generates a virtual space along a timeline based on the loaded historical data. The input is the loaded historical data, and the output is the generated virtual space. Specifically, the server uses a VR engine to construct a three-dimensional virtual space.

[1562] Step 3:

[1563] The server generates AIs with individual thoughts, in numbers equivalent to the total world population, and places them in a virtual space. The input is historical data and a generative AI model, and the output is an AI character placed in the virtual space. Specifically, the server uses the OpenAI API to generate AI characters and place them in the virtual space.

[1564] Step 4:

[1565] The user wears a head-mounted display and accesses the virtual space. The input is the user's visual information, and the output is the visual experience of the virtual space. Specifically, the user wears the head-mounted display and moves freely within the virtual space.

[1566] Step 5:

[1567] The user provides input to interact with the AI ​​character in the virtual space. The input is the user's voice or text, and the output is the user's input data. Specifically, the user speaks to the AI ​​character using voice recognition or text input.

[1568] Step 6:

[1569] The server generates responses for the AI ​​character based on the user's input. The input is the user's input data and the generative AI model, and the output is the AI ​​character's response. Specifically, the server uses the OpenAI API to generate appropriate responses to the user's input.

[1570] Step 7:

[1571] The server displays the generated AI character's response in the virtual space. The input is the AI ​​character's response, and the output is the response displayed in the virtual space. Specifically, the server uses the VR engine to visually display the response.

[1572] Step 8:

[1573] The user checks the response of the AI ​​character displayed in the virtual space and performs the next interaction. The input is the response displayed in the virtual space, and the output is the user's next input. In concrete terms, the user checks the displayed response and asks the next question or gives the next instruction.

[1574] Example 2

[1575] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1576] There is a need to inherit the knowledge and management decisions of influential figures and utilize that knowledge even after retirement. It is also important to obtain new management hints through dialogue with historical figures. However, there is a lack of concrete methods to effectively inherit this knowledge and decisions and utilize them in actual management. Furthermore, a system is needed to verify hypotheses and make realistic predictions about the future.

[1577] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1578] In this invention, the server includes means for collecting data on influential people, means for preprocessing the collected data, means for training a machine learning model based on the preprocessed data, means for evaluating the trained model, means for providing an interface for users to interact with the AI, means for the AI ​​to generate answers based on user input, means for inheriting the specific thoughts and actions of influential people and turning them into AI to enable dialogue, and means for realistically verifying and visualizing various hypotheses to help with future predictions. This makes it possible to effectively inherit the knowledge and management decisions of influential people and use them in actual management. Furthermore, dialogue with historical figures can provide new management insights, allowing for realistic hypothesis verification and future predictions.

[1579] An "influential person" is someone who plays an important role in society or an organization and whose thoughts and actions have a significant impact on others.

[1580] "Data collection" refers to the process of obtaining information needed for a specific purpose from sources such as the internet or databases.

[1581] "Preprocessing" refers to a series of operations performed on collected data to transform it into a form suitable for analysis and model training, including data cleaning, tokenization, and normalization.

[1582] A "machine learning model" refers to an algorithm or mathematical model that automatically learns specific tasks based on data and makes predictions or classifications.

[1583] "Model training" refers to the process of using collected data to train a machine learning model and improve its performance.

[1584] "Model evaluation" refers to the process of evaluating the performance of a trained machine learning model using test data to confirm its accuracy and effectiveness.

[1585] "User interface" refers to the software and hardware components that provide a means for a user to interact with a system, including chatbots and voice recognition.

[1586] A "prompt" refers to the text of a question or instruction that a user enters into an AI.

[1587] "Hypothesis verification" refers to the process of verifying whether a particular hypothesis is correct using actual data or simulations.

[1588] "Future forecasting" refers to the process of predicting future events or conditions based on current data and trends.

[1589] This invention is a system for inheriting the knowledge and management decisions of influential people and utilizing that knowledge even after they retire. A specific embodiment of this system will be described below.

[1590] The server first collects data on influencers, including their past statements, behavioral history, and decision-making processes, using web scraping tools (e.g., BeautifulSoup, Scrapy) or APIs.

[1591] The server then preprocesses the collected data, which includes cleaning the text data (denoising, normalising), tokenising, removing stop words, etc. This is done using natural language processing libraries such as Python's NLTK or spaCy.

[1592] The server then uses the preprocessed data to train a machine learning model designed to learn the thought and behavior patterns of influential people. Training is performed using deep learning frameworks such as TensorFlow and PyTorch, and is run on a server equipped with high-performance GPUs.

[1593] The trained model is evaluated by the server. The evaluation involves checking the accuracy of the model using test data and adjusting hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc.

[1594] The device provides an interface for users to interact with the AI, including chatbot-style interfaces and voice-activated applications, using web frameworks such as Flask and Django.

[1595] The user poses a question to the AI ​​through their device. For example, the user might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the device's chat box. For example, a response might read, "When entering a new market, it is important to first conduct thorough market research. To minimize risk, it is necessary to work with local partners and understand differences in laws, regulations, and culture."

[1596] In this way, the knowledge and management decisions of influential figures can be effectively passed on and put to use in actual management. Furthermore, through dialogue with historical figures, new management hints can be obtained, and hypotheses can be verified and future predictions can be made in real time.

[1597] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1598] Step 1:

[1599] The server collects data on influential people. Specifically, it uses web scraping tools (e.g., BeautifulSoup, Scrapy) and APIs to retrieve data such as executives' past statements, behavioral history, and decision-making processes from the internet and corporate databases. The input is the website URL or API endpoint, and the output is the collected text data.

[1600] Step 2:

[1601] The server preprocesses the collected data. Specifically, it uses Python's NLTK and spaCy to clean the text data (remove noise, normalize), tokenize, and remove stop words. The input is the collected text data, and the output is the preprocessed, clean text data.

[1602] Step 3:

[1603] The server trains a machine learning model based on the preprocessed data. Specifically, it uses TensorFlow and PyTorch to build a deep learning model that learns the thought patterns and behavior patterns of influential people. The input is the preprocessed text data, and the output is the trained machine learning model.

[1604] Step 4:

[1605] The server evaluates the trained model. Specifically, it checks the model's accuracy using test data and adjusts hyperparameters as necessary. Evaluation metrics include precision, recall, F1 score, etc. The input is the trained machine learning model and test data, and the output is the evaluation results and the adjusted model.

[1606] Step 5:

[1607] The terminal provides an interface for users to interact with the AI. Specifically, Flask and Django are used to build an application with a chatbot-style interface and speech recognition functionality. The input is the user's questions and instructions (prompts), and the output is the AI's response.

[1608] Step 6:

[1609] The user poses a question to the AI ​​through the terminal. For example, they might type, "What are your thoughts on risk management when entering a new market?" The server receives this prompt and generates an answer based on the trained model. The generated answer is displayed in the terminal's chat box. The input is the user's prompt, and the output is the answer from the AI.

[1610] (Application example 2)

[1611] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1612] In today's business environment, there is a need to inherit and utilize in real time the knowledge and management decisions of influential business leaders and historical figures. However, existing technologies have limited the means to effectively utilize this knowledge, making it difficult to optimize customer service, product placement, and promotions, especially in physical stores.

[1613] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1614] In this invention, the server includes a means for building a platform that enables the reproduction of history, a means for generating AIs with individual thoughts equivalent to the total population of the world and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can engage in dialogue, a means for providing the knowledge and management decisions of influential people in real time using smart devices, and a means for verifying and visualizing various hypotheses in real time to help predict the future. This will enable the optimization of customer service, product placement, and promotions even in physical stores.

[1615] A "platform that enables historical reenactment" is a system that recreates past events and the actions of people in a virtual space, allowing users to experience them.

[1616] "AI with individual thoughts" is artificial intelligence that learns the thought patterns of a specific person or character and acts independently based on that.

[1617] "Inheriting the specific thoughts and actions of influential people and turning them into AI" means creating an AI that learns the thinking and behavior patterns of famous historical figures and modern business leaders and imitates them.

[1618] "Interaction-enabling means" refers to interfaces and technologies that allow users to have natural conversations with artificial intelligence.

[1619] A "smart device" is an electronic device that can connect to the Internet and run various applications. Examples include smartphones and smart glasses.

[1620] "A means of providing insights and business decisions from influential people in real time" is a technology that allows users to instantly receive insights and business decisions from influential people based on their current situation.

[1621] "A means of realistically verifying and visualizing hypotheses to aid in future predictions" is a technology that simulates hypotheses and visually displays the results to aid in future predictions and strategy formulation.

[1622] To implement the present invention, the following system configuration and program are required.

[1623] First, the server builds a platform that enables historical reenactment. This platform recreates past events and the actions of people in a virtual space, allowing users to experience them. Next, the server generates AI with individual thoughts, in numbers equivalent to the world's total population, places them in the virtual space, and lets them act independently. This AI learns the thought patterns of specific people and characters and acts independently based on those patterns.

[1624] Furthermore, the server inherits the specific thoughts and actions of influential people and turns them into AI, enabling dialogue. This AI learns and imitates the thinking and behavior patterns of famous historical figures and modern business leaders. Users can have natural conversations with this AI.

[1625] Next, we will implement a method to provide influential people's insights and business decisions in real time using smart devices such as smartphones and smart glasses. This allows users to instantly receive insights and business decisions from influential people based on their current situation.

[1626] Specifically, an application installed on the smart glasses analyzes customer behavior through the camera and sends the data to a server. The server uses the data to generate appropriate prompts and provides advice using a generative AI model. For example, if a customer picks up a specific product, the server generates a prompt such as, "Please tell us what to do if a customer picks up the product," and the AI ​​provides real-time advice such as, "Provide a detailed description of the product and share related promotional information."

[1627] The hardware used includes smart glasses (with a camera) and smartphones, and the software uses OpenAI API and OpenCV (image processing library), enabling optimization of customer service, product placement, and promotions in physical stores.

[1628] Examples of prompts include:

[1629] "What should I do if a customer picks up my product?"

[1630] In this way, store staff can tap into the knowledge of renowned business leaders and marketing experts from history to optimize customer interactions.

[1631] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1632] Step 1:

[1633] The user puts on the smart glasses and launches the application.

[1634] Input: Smart glasses camera image

[1635] Output: Real-time video data

[1636] Specific operation: The camera in the smart glasses captures video in real time, and the application acquires the video data.

[1637] Step 2:

[1638] The device analyzes camera footage and detects customer behavior.

[1639] Input: Real-time video data

[1640] Output: Customer behavior data (e.g., product pick-up behavior)

[1641] Specific operation: The device uses OpenCV to analyze video data and detect specific actions, such as a customer picking up a product.

[1642] Step 3:

[1643] The device transmits the detected behavior data to the server.

[1644] Input: Customer behavior data

[1645] Output: Send data to the server

[1646] Specific operation: The device generates an API request to send the detected customer behavior data to the server and sends it to the server.

[1647] Step 4:

[1648] The server generates a prompt sentence based on the behavioral data received.

[1649] Input: Customer behavior data

[1650] Output: Prompt statement (e.g., "What should I do if the customer picks up the item?")

[1651] Specific behavior: The server analyzes the received behavioral data and executes logic to generate appropriate prompt sentences.

[1652] Step 5:

[1653] The prompt sentence generated by the server is input into the generative AI model to obtain advice.

[1654] Input: prompt statement

[1655] Output: AI advice (e.g., "Provide a detailed description of the product and share relevant promotional information.")

[1656] Specific operation: The server uses the OpenAI API to input prompt sentences into the generative AI model and obtain advice from the AI.

[1657] Step 6:

[1658] The server transmits the obtained advice to the terminal.

[1659] Input: AI advice

[1660] Output: Sending data to the terminal

[1661] Specific operation: The server generates an API request to send the obtained advice to the terminal and sends it to the terminal.

[1662] Step 7:

[1663] The terminal displays the received advice to the user.

[1664] Input: AI advice

[1665] Output: Advice displayed on the smart glasses display

[1666] Specific operation: The terminal displays the received advice on the display of the smart glasses so that the user can check it.

[1667] In this way, users can receive real-time insights and business decisions from influential people and optimize customer service, product placement, and promotions.

[1668] Example 3

[1669] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1670] Hypothesis verification and scenario simulation are important in modern business strategies and future predictions, but experiments and verifications in the real world require a great deal of time and cost. It is also difficult to inherit the knowledge and management decisions of influential people and use them in simulations in virtual space. Furthermore, there is a lack of systems that can convert user-defined hypotheses into concrete scenarios and observe and analyze the results in real time.

[1671] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1672] In this invention, the server includes means for building a platform that enables historical reproduction, means for generating artificial intelligences with individual thoughts equivalent to the total world population, placing them in a virtual space, and making them act independently, means for inheriting the specific thoughts and actions of influential people and turning them into artificial intelligences that can engage in dialogue, means for realistically verifying and visualizing various hypotheses to help predict the future, means for a user to set hypotheses and generate prompt statements, means for analyzing the generated prompt statements and generating specific instructions to be executed in the virtual space, means for constructing a virtual space, placing artificial intelligence agents, and executing scenarios, means for observing results, collecting data, analyzing them, and generating reports, and means for displaying the results to the user. This enables a user to set hypotheses, execute specific scenarios in the virtual space, and observe and analyze the results in real time.

[1673] The "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and observe that environment.

[1674] "Artificial intelligence" is a computer program that mimics human thought and behavior and has the ability to learn, judge, and act independently.

[1675] A "virtual space" is a computer-generated, three-dimensional digital environment, a simulated environment in which users and artificial intelligence can interact.

[1676] An "influential person" is someone whose actions and decisions have a widespread impact, such as a historical figure or a modern business leader.

[1677] "Inheriting thoughts and actions to create artificial intelligence" means collecting data on the thought patterns and actions of influential people and building artificial intelligence based on that data.

[1678] A "hypothesis" is a prediction or assumption about a certain phenomenon or event, and is a prerequisite for confirming its validity through verification and experimentation.

[1679] A "prompt sentence" is an input sentence for converting a hypothesis set by the user into a specific scenario.

[1680] A "generative AI model" is an artificial intelligence model that analyzes prompt statements and generates specific instructions to be executed in a virtual space.

[1681] A "scenario" is a hypothetical sequence of events or situations that is carried out in a virtual space.

[1682] "Means of observing results, collecting data, analyzing, and generating reports" refers to the process of observing the results of scenarios executed in virtual space in real time, collecting and analyzing that data, and creating reports to provide to users.

[1683] "Means for displaying results to the user" refers to an interface that visually displays the collected and analyzed data and allows the user to review and evaluate the results.

[1684] This invention is a system that uses artificial intelligence in a virtual space to verify hypotheses and is useful for future predictions and the formulation of business strategies. Specific embodiments of this system will be described below.

[1685] First, the user sets a hypothesis through an interface on a web browser. For example, the user inputs a hypothesis such as "Sales fluctuations when new product A is launched on the market." The terminal generates a prompt based on the hypothesis entered by the user. Specifically, the prompt generated is "Please simulate how sales will fluctuate over the next six months when new product A is launched on the market."

[1686] The server then sends the generated prompt to a generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual world. This generative AI model is built using a machine learning framework such as TensorFlow or PyTorch.

[1687] The server uses software such as Unity to create a virtual world, which is designed based on a scenario set by the user and includes stores, consumers, competitors, and more.

[1688] The server deploys artificial intelligence agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The artificial intelligence agents are controlled by machine learning models written in Python, which allows the server to simulate consumer behavior and observe fluctuations in sales.

[1689] The results of the scenario execution are observed in real time by the server, which collects sales data and consumer behavior data. This data is stored in a database. The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of a report. The report includes graphs showing sales trends and statistical information on consumer purchasing behavior.

[1690] Finally, the terminal displays the report received from the server to the user, who can then use the dashboard to view sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions.

[1691] As a concrete example, consider a simulation of the impact of a new product launch on sales. The user inputs the following prompt into the generative AI model:

[1692] "If we launch new product A into the market, please simulate how sales will fluctuate over the next six months."

[1693] The server receives this prompt and sets up a market launch scenario for new product A in the virtual space. The artificial intelligence agent simulates consumer behavior and observes fluctuations in sales. The observation results are provided to the user in the form of graphs and reports, which can be used to formulate business strategies and make future predictions. The flow of the specific processing in Example 3 will be explained using FIG. 15.

[1694] Step 1:

[1695] The user sets the hypothesis

[1696] The user opens the interface on a web browser and inputs a hypothesis. For example, they input a hypothesis such as "Sales fluctuations when new product A is released to the market." The input data is the text information of the hypothesis. The output is that the hypothesis is registered in the system.

[1697] Step 2:

[1698] The terminal generates a prompt

[1699] The terminal generates a prompt based on the hypothesis entered by the user. Specifically, it generates the prompt, "Please simulate how sales will fluctuate over the next six months if new product A is released to the market." The input data is the hypothesis set by the user, and the output is the generated prompt.

[1700] Step 3:

[1701] The server sends a prompt to the generative AI model

[1702] The server sends the prompt received from the device to the generative AI model, which analyzes the prompt and generates specific instructions to execute in the virtual space. The input data is the generated prompt, and the output is specific scenario instructions.

[1703] Step 4:

[1704] The server creates the virtual space

[1705] The server uses software such as Unity to build a virtual space. This virtual space is designed based on a scenario set by the user. The input data are specific scenario instructions, and the output is the constructed virtual space.

[1706] Step 5:

[1707] The server deploys AI agents and executes scenarios.

[1708] The server deploys AI agents in the virtual space and executes scenarios based on instructions received from the generative AI model. The AI ​​agents are controlled by machine learning models written in Python. The input data are specific scenario instructions, and the output is the results of the executed scenario.

[1709] Step 6:

[1710] The server observes the results and collects the data.

[1711] The server observes the results of the scenario execution in real time and collects sales data and consumer behavior data. These data are stored in a database. The input data are the results of the executed scenario, and the output is the collected data.

[1712] Step 7:

[1713] The server analyzes the results and generates a report

[1714] The server analyzes the collected data and compiles sales fluctuations and consumer behavior patterns in the form of reports. The reports include graphs showing sales trends and statistical information on consumer purchasing behavior. The input data is the collected data, and the output is the generated report.

[1715] Step 8:

[1716] The device displays the results to the user

[1717] The terminal displays the report received from the server to the user. Through the dashboard, the user can check sales trend graphs and consumer behavior statistics, which can be used to formulate business strategies and make future predictions. The input data is the generated report, and the output is the result displayed to the user.

[1718] (Application example 3)

[1719] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1720] Optimizing work efficiency is an important issue in modern logistics centers. However, trying out new layouts and work flows in a real environment is not easy due to the costs and risks involved. It is also difficult to verify hypotheses when formulating business strategies or making future predictions. To solve these issues, a means is needed to utilize simulations in virtual space to find optimal strategies that are efficient, low-risk, and efficient.

[1721] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a means for building a platform that enables historical reproduction, a means for generating AIs with individual thoughts equivalent to the total world population and placing them in a virtual space to act independently, a means for inheriting the specific thoughts and actions of influential people and turning them into AIs that can interact, a means for simulating scenarios in a virtual space to optimize work efficiency within a logistics center, and a means for visualizing the simulation results and proposing optimal strategies. This makes it possible to evaluate the effects of new layouts and work flows in logistics centers with low risk and to formulate optimal strategies.

[1722] A "platform that enables historical reenactment" is a system that recreates past events and situations in a virtual space, allowing users to experience and learn within it.

[1723] "AI with individual thinking" is artificial intelligence that imitates the thought patterns and behavior of a specific individual and makes decisions and takes action independently.

[1724] A "virtual space" is a digital environment generated by computer simulation, an area in which users can interact.

[1725] "Means for autonomous action" refers to technologies and algorithms that allow AI to make decisions and take action on its own without external instructions.

[1726] An "influential person" is an individual who has had a significant impact on society or an organization, either historically or in the present day.

[1727] "Means to inherit specific thoughts and actions, turn them into AI, and enable dialogue" refers to technology that incorporates the thoughts and behavioral patterns of influential people into AI, allowing users to interact with that AI.

[1728] "A means to realistically verify and visualize hypotheses to help predict the future" is a technology that executes scenarios set up in virtual space and visually displays the results, helping to predict the future and formulate strategies.

[1729] "A means of simulating scenarios in a virtual space to optimize work efficiency within a logistics center" is a technology that tests the layout and work flow of a logistics center in a virtual space and evaluates their effectiveness.

[1730] "Means for visualizing simulation results and proposing optimal st...

Claims

1. A means to build a platform that allows historical reenactment; A means of collecting historical data from the past to the present and storing it in a database; A means for generating a virtual space along a time axis based on the collected historical data; A means to generate AI with individual thoughts in a number equivalent to the total population of the world, place them in a virtual space, and have them act independently; A means for customizing and displaying a virtual space based on a user request; A means for a user to interact with an AI agent in a virtual space and obtain information; A means to inherit the specific thoughts and actions of influential people and turn them into AI, enabling dialogue; A means to realistically verify and visualize hypotheses and use them to predict the future, A system including:

2. The system according to claim 1, further comprising a means for turning business leaders and historical figures, who are considered influential people, into AI and passing on their knowledge and business decisions.

3. The system according to claim 1, further comprising a means for verifying and visualizing hypotheses to aid in formulating business strategies and making future predictions.

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