System

Abstract

To provide a system.SOLUTION: A system includes: means for inputting the past and present carriers, skills, values, etc., of a user; means for inputting a future image of the user; an AI agent for suggesting a future possibility matching the user based upon the input information on the user; means for simulating the possibility suggested by the AI agent and visualizing the life of the user; and means for generating a response by a generative AI model based upon the life of the user visualized by the means for visualizing the life, and returning the response to the user.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] In modern society, people are expected to manage their own careers and financial life plans. However, it is difficult to independently determine future possibilities based on one's background, skills, and values, and to create a life plan based on these. [Means for solving the problem]

[0005] This invention provides a means for inputting a user's past and present career history, skills, values, etc., a means for inputting an image of the user's future, an AI agent that proposes future possibilities that suit the user based on the input information, and a means for simulating the proposed possibilities and visualizing life, thereby enabling users to efficiently create a life plan that suits them. [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] The system of the present invention provides a means for users to input their past and current career history, skills, values, etc. Specifically, the system allows users to input their own information through a user interface. For example, users can input their work history, skill set, values, hobbies, interests, etc.

[0029] "Example 2"

[0030] Next, we provide a means for users to input their future vision. Specifically, we allow users to input their future goals and aspirations. For example, users can input their career goals, desired lifestyle, future income goals, etc.

[0031] "Example 3"

[0032] We provide an AI agent that suggests future possibilities that suit the user based on the information entered. Specifically, the AI ​​agent analyzes the information entered by the user and, based on that, suggests the most suitable career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values. "Example 4"

[0033] Finally, the system provides a means to simulate the proposed possibilities and visualize the user's life. Specifically, the system simulates and visualizes the user's future life based on the career path and life plan proposed by the system. For example, the system can simulate the user's future income and lifestyle based on the proposed career path and display them in graphs and charts.

[0034] The processing flow of each embodiment will be described below.

[0035] "Example 1"

[0036] Step 1: The user enters their past and current career history, skills, values, etc. through the system's user interface. For example, the user enters their work history, skill set, values, hobbies, interests, etc.

[0037] "Example 2"

[0038] Step 1: The user inputs their own image of the future through the system's user interface. For example, the user inputs their career goals, desired lifestyle, future income goals, etc.

[0039] "Example 3"

[0040] Step 1: The AI ​​agent analyzes the user's input.

[0041] Step 2: The AI ​​agent uses the analysis results to suggest the optimal career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values.

[0042] "Example 4"

[0043] Step 1: The system simulates the user's future life based on the career path and life plan suggested by the system.

[0044] Step 2: Visualize the simulation results. For example, you can simulate the user's future income and lifestyle based on the proposed career path and display it in graphs and charts.

[0045] Example 1

[0046] 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."

[0047] Conventional systems provided a way for users to input information such as their past and present career history, skills, and values, but lacked the means to propose specific future possibilities based on this information, or to simulate and visualize these proposals. Furthermore, there was no established process for efficiently analyzing the data entered by users and generating appropriate responses using a generative AI model. This made it difficult to provide specific and useful advice to users.

[0048] 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.

[0049] In this invention, the server includes: a means for inputting the user's past and present career history, skills, values, etc.; a means for inputting the user's image of the future; an AI agent that proposes future possibilities suitable for the user based on the input information; a means for simulating the proposed possibilities and visualizing life; a means for receiving the data input by the user and storing it in a database; a means for analyzing the stored data and inputting prompt sentences to the generative AI model; and a means for the generative AI model to generate responses and return the responses to the user. This makes it possible to propose specific future possibilities based on the user's input information and simulate and visualize the proposals. Furthermore, the generative AI model can be used to generate appropriate responses and provide specific and useful advice to the user.

[0050] "User" refers to an individual who uses the system to input their information and receive future opportunities and advice.

[0051] "Career" refers to the user's past job history, educational background, etc.

[0052] "Skills" refers to the skills, abilities, and expertise that a user possesses.

[0053] "Values" refer to the beliefs and ideas that users consider important.

[0054] "Image of the future" refers to the hopes, goals, and visions that users have for the future.

[0055] An "AI agent" refers to an artificial intelligence system that suggests future possibilities based on user input.

[0056] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[0057] "Database" means a digital storage system for storing and managing information entered by users.

[0058] A "generative AI model" refers to an artificial intelligence model that generates responses based on user input information.

[0059] "Prompt" refers to a textual instruction that is input to a generative AI model.

[0060] "Response" refers to the advice or suggestions that the generative AI model generates based on the prompt.

[0061] This invention is a system that allows users to input their past and present career history, skills, values, etc., and then suggests and simulates future possibilities based on that information. Specific embodiments of this system are described below.

[0062] First, the user accesses the user interface provided through a web browser. This interface is built using web technologies such as HTML, CSS, and JavaScript. The user then enters information such as work history, skill set, values, hobbies, and interests into an input form.

[0063] When the user completes the input and clicks the submit button, the device sends the input data to the server as an HTTP request. This request contains data in JSON format. The server receives the HTTP request sent from the device, analyzes the received data, and stores it in a database. The database may be MySQL (registered trademark) or MongoDB.

[0064] The server analyzes the stored data to extract information such as the user's work history, skill set, values, hobbies, and interests. The analysis is performed using programming languages ​​such as Python and Node.js. Based on the analysis results, the server generates a prompt. The generated prompt is then input into a generative AI model (e.g., OpenAI's GPT-4).

[0065] The generative AI model generates a response based on the input prompt. The response may include career advice or suggestions for skill improvement for the user. The server receives the response from the generative AI model and returns it to the user's device. The user can view the response in their web browser.

[0066] For example, if a user enters "5 years of experience as a software engineer" as their work history and "Python, JavaScript, React" as their skill set, the server stores this information in the database and then inputs the following prompt to the generative AI model:

[0067] Example prompt sentence:

[0068] User's work experience: 5 years of experience as a software engineer

[0069] User skill set: Python, JavaScript, React

[0070] User values: Emphasize teamwork

[0071] User's hobbies: programming, reading

[0072] User Interest: Latest Trends in AI Technology

[0073] Based on this prompt, the generative AI model generates career advice and skill improvement suggestions tailored to the user, such as, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[0074] In this way, users can receive specific and useful advice based on their own information.

[0075] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0076] Step 1:

[0077] The user enters information

[0078] Users access the user interface provided through a web browser and enter information such as their work history, skill set, values, hobbies, and interests into an input form. Examples of input data include "5 years of experience as a software engineer," "Python, JavaScript, React," "emphasis on teamwork," "programming, reading," and "latest trends in AI technology."

[0079] Step 2:

[0080] The device sends the input data to the server

[0081] When the user clicks the submit button, the terminal sends the input data as an HTTP request to the server. This request contains data in JSON format. The input data is information entered by the user, such as work history, skill set, values, hobbies, and interests. The terminal sends this data to the server.

[0082] Step 3:

[0083] The server receives the data and stores it in the database

[0084] The server receives HTTP requests sent from the terminal. It analyzes the received data and stores it in a database. Databases such as MySQL and MongoDB are used. The input data includes information such as the user's work history, skill set, values, hobbies, and interests, and this is stored in the database. For example, the following data is stored in a MySQL database:

[0085] sql

[0086] INSERT INTO user_data (Work history, Skill set, Values, Hobbies, Interests) VALUES ('5 years of experience as a software engineer', '["Python", "JavaScript", "React"]', 'Values ​​teamwork', '["Programming", "Reading"]', 'The latest trends in AI technology');

[0087] Step 4:

[0088] The server analyzes the stored data

[0089] The server analyzes the user information stored in the database. Programming languages ​​such as Python and Node.js are used for the analysis. As a result of the analysis, the user's work history, skill set, values, hobbies, interests, etc. are extracted. The input data is the user information stored in the database, and the output data is the user's work history, skill set, values, hobbies, interests, etc. extracted by the analysis.

[0090] Step 5:

[0091] The server inputs a prompt to the generative AI model.

[0092] The server generates a prompt sentence based on the analysis results. The generated prompt sentence is input into the generative AI model. The input data is the user information extracted as the analysis result, and the output data is the generated prompt sentence. For example, the following prompt sentence is generated:

[0093] User's work experience: 5 years of experience as a software engineer

[0094] User skill set: Python, JavaScript, React

[0095] User values: Emphasize teamwork

[0096] User's hobbies: programming, reading

[0097] User Interest: Latest Trends in AI Technology

[0098] Step 6:

[0099] A generative AI model generates a response

[0100] The generative AI model generates a response based on the input prompt. The response can include career advice or suggestions for skill improvement for the user. The input data is the generated prompt, and the output data is the response generated by the generative AI model. For example, the generated advice might be, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[0101] Step 7:

[0102] The server returns the generated response to the user

[0103] The server receives the response from the generative AI model and returns it to the user's device. The user can view the response on a web browser. The input data is the response from the generative AI model, and the output data is the response displayed on the user's device.

[0104] (Application example 1)

[0105] 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."

[0106] Previous systems provided a way for users to input their past and current career history, skills, values, etc., but lacked the functionality to recommend the most suitable content to users. This made it difficult for users to find content that matched their interests and skills. Furthermore, there was no way to calculate the similarity of recommended content and present the most suitable content. This resulted in low user satisfaction and limited the usefulness of the system.

[0107] 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.

[0108] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user. This allows users to easily find content that matches their interests and skills, improving the utility value of the system.

[0109] "Means for inputting users' past and present career history, skills, values, etc." refers to means that provide an interface for users to input information such as their work history, skill set, values, hobbies, and interests.

[0110] "Means for inputting the user's image of the future" refers to a means for providing an interface for the user to input information such as their future goals and desired career path.

[0111] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the best future job type, company, and next step goal for the user.

[0112] "Means for simulating proposed possibilities and visualizing life" refers to a means for simulating and visually displaying a user's life plan based on future possibilities proposed by an AI agent.

[0113] "Means for recommending optimal content based on information entered by the user" refers to a means for analyzing information entered by the user, such as career history, skills, values, hobbies, and interests, and then recommending the most appropriate content for the user, such as movies, books, music, and news articles, based on that information.

[0114] The "means for calculating the similarity of the recommended content" refers to an algorithm or software for calculating the similarity between the recommended content and the user's input information.

[0115] The "means for presenting the most similar content to the user" refers to a means for selecting the most suitable content for the user based on the calculated similarity and presenting it to the user.

[0116] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user.

[0117] System configuration

[0118] The server provides an interface, which may include a smartphone application or a web interface, for users to enter information about their work history, skill set, values, hobbies, interests, etc. The information entered by the user is sent to the server and stored in a database.

[0119] The server then uses an AI agent to suggest future jobs, companies, and next steps based on the user's input. This AI agent uses a generative AI model to analyze the user's information and suggest optimal future possibilities.

[0120] Furthermore, the server provides a means for simulating and visually displaying the user's life plan based on the proposed future possibilities, so that the user can easily understand the future scenario concretely.

[0121] Content recommendation function

[0122] To recommend optimal content based on user input, the server analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends the most suitable content for the user, such as movies, books, music, and news articles. This recommendation method uses a generative AI model to compare the user's information with information in a content database and select the most suitable content.

[0123] To calculate the similarity of the recommended content, the server uses an algorithm such as cosine similarity, which calculates the similarity between the user's input information and the content description, and presents the most similar content to the user.

[0124] Hardware and software used

[0125] This system is realized using smartphones, servers, databases, generative AI models, and software such as TfidfVectorizer and cosine_similarity. The smartphone provides the user interface, while the server processes and stores data. The generative AI model is used to analyze user information and recommend optimal content.

[0126] Specific examples

[0127] For example, if a user enters the following information:

[0128] Work Experience: Data Scientist

[0129] Skillset: Python, Data Analysis, Machine Learning

[0130] Values: Data-driven decision making

[0131] Hobbies: Reading, watching movies

[0132] Interests: Big Data, AI

[0133] In this case, the server will recommend the book "The Future of AI."

[0134] Prompt Sentence Examples

[0135] Enter the user's work experience, skillset, values, hobbies, and interests. For example, enter "Work experience: Data Scientist, Skill set: Python, Data analysis, Machine learning, Values: Data-driven decision-making, Hobbies: Reading, Watching movies, Interests: Big data, AI."

[0136] In this way, a system can be realized that recommends optimal content to users.

[0137] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0138] Step 1:

[0139] Users use a smartphone or web interface to enter information such as their work history, skill set, values, hobbies, and interests. The entered information is sent to a server and stored in a database. The input data is in text format and includes the user's past and present work history, skills, values, etc.

[0140] Step 2:

[0141] The server uses a generative AI model to suggest future jobs, companies, and desired next steps based on the information entered by the user. The generative AI model analyzes the user's input data and suggests optimal future possibilities. This analysis uses natural language processing technology, which converts the user's input data into a feature vector. The output is the future jobs, companies, and desired next steps suggested to the user.

[0142] Step 3:

[0143] The server simulates and visually displays the user's life plan based on the proposed future possibilities. The simulation means, which allows the user to concretely understand future scenarios, includes visual elements such as graphs and charts. The input is the proposed data from the generative AI model, and the output is a visually displayed life plan.

[0144] Step 4:

[0145] The server uses a generative AI model to recommend optimal content based on user input. It analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends content such as movies, books, music, and news articles that are optimal for the user. The input is the user's input data, and the output is a list of recommended content.

[0146] Step 5:

[0147] The server uses an algorithm such as cosine similarity to calculate the similarity between the user's input information and the content description. The input is the user's feature vector and the content's feature vector, and the output is a similarity score.

[0148] Step 6:

[0149] The server selects the most suitable content for the user based on the calculated similarity and presents it to the user. The most similar content is presented to the user. The input is the similarity score, and the output is the optimal content to be presented to the user.

[0150] In this way, a system for recommending optimal content to a user is realized.

[0151] Example 2

[0152] 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."

[0153] In conventional systems, it was difficult for users to input a specific image of their future and receive appropriate suggestions based on that. Furthermore, there was a lack of means to utilize generative AI models based on the user's future goals and aspirations, resulting in a lack of accuracy and specificity in the suggestions made to users. This made it difficult for users to specifically understand and plan for their future possibilities.

[0154] 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.

[0155] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing life, means for sending prompt sentences to the generative AI model based on the image of the future input by the user, and means for the generative AI model to generate responses and present them to the user. This allows the user to specifically input their image of the future and receive highly accurate suggestions based on it using the generative AI model.

[0156] A "user" is an individual who uses the system to input information about their past and present, as well as an image of their future, and receives suggestions.

[0157] "Career" refers to the user's career history, including occupations and educational background.

[0158] "Skills" refer to the skills and abilities that users possess.

[0159] "Values" refer to the beliefs and ideas that users consider important.

[0160] "Image of the future" refers to the goals and hopes that users want to achieve in the future.

[0161] An "AI agent" is a program that suggests future possibilities that suit the user based on the information they input.

[0162] "Simulation" is the process of virtually trying out proposed future possibilities and visualizing the results.

[0163] "Generative AI model" refers to an artificial intelligence model for generating responses based on user input.

[0164] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[0165] "Response" refers to the output that a generative AI model generates based on a prompt.

[0166] This invention is a system that allows users to input specific images of their future and receive highly accurate proposals based on those images using a generative AI model. Specific embodiments of this system are described below.

[0167] Hardware and software used

[0168] Hardware: Servers, user devices (PCs, smartphones, etc.)

[0169] Software: web browsers, server-side applications (e.g., Node.js), databases (e.g., MySQL), generative AI models (e.g., GPT-4)

[0170] System configuration

[0171] 1. User input:

[0172] Users open a web browser on a device such as a PC or smartphone, access the system's URL, and enter their past and present career history, skills, values, and image of the future into a form displayed on the system's web page.

[0173] 2. Means of data transmission:

[0174] When the user clicks the submit button on the form, the device sends the entered data to the server as an HTTP POST request.

[0175] 3. Data storage means:

[0176] The server processes the received data and saves it to a database. For example, the server receives the data using Node.js and saves it by executing an "INSERT" query in a MySQL database.

[0177] 4. How to send prompts to the generative AI model:

[0178] The server sends prompts to the generative AI model based on the stored data. For example, the server might generate a prompt such as, "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and send it to GPT-4.

[0179] 5. How the generative AI model generates responses:

[0180] The generative AI model generates a response based on the prompt and returns it to the server. For example, GPT-4 might generate a response like, "To succeed as a data scientist, it's important to master the following skills..." and return it to the server.

[0181] 6. Response Presentation Method:

[0182] The server sends the generated response to the user's terminal, where the user can view the generated response on their web browser.

[0183] Specific examples

[0184] User input: "Future career goal: Data scientist, Desired lifestyle: Remote work, Future income goal: Annual income of 10 million yen"

[0185] Prompt for the generative AI model: "The user's career goal is to become a data scientist. Their desired lifestyle is remote work, and their future income goal is to earn 10 million yen a year. Based on this, please suggest steps the user can take to achieve this goal."

[0186] In this way, the system allows users to input specific images of their future, and the generative AI model generates responses based on those images. This system allows users to concretely understand and plan for their future possibilities.

[0187] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0188] Step 1:

[0189] A user accesses the system using a terminal.

[0190] A user opens a web browser using a device such as a PC or smartphone and enters the system's URL to access it. For example, a user accesses "https: / / example.com" using GOOGLE CHROME (registered trademark). The input is the URL, and the output is the system's web page.

[0191] Step 2:

[0192] The user inputs an image of the future.

[0193] Users enter their past and present career history, skills, values, and future vision into a form displayed on the system's web page. For example, they enter "I want to become a data scientist" as their "career goal," "remote work" as their desired lifestyle, and "annual income of 10 million yen" as their future income goal. The input is the user's information, and the output is the data entered into the form.

[0194] Step 3:

[0195] The terminal sends the input data to the server.

[0196] When a user clicks the submit button on a form, the terminal sends the entered data to the server as an HTTP POST request. For example, when a user clicks the "Submit" button, the data is sent to "https: / / example.com / submit". The input is the form data, and the output is an HTTP request to the server.

[0197] Step 4:

[0198] The server receives the data and stores it in a database.

[0199] The server processes the received data and stores it in a database. For example, the server receives the data using Node.js and executes an "INSERT" query in a MySQL database to store the data. The input is the data from the HTTP request and the output is the record stored in the database.

[0200] Step 5:

[0201] The server sends a prompt to the generative AI model.

[0202] The server sends prompts to the generative AI model based on the stored data. For example, the server generates a prompt such as "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and sends it to the generative AI model. The input is the database record, and the output is the generated prompt.

[0203] Step 6:

[0204] The generative AI model generates a response and returns it to the server.

[0205] The generative AI model generates a response based on the prompt sentence and returns it to the server. For example, the generative AI model generates a response such as "To succeed as a data scientist, it is important to master the following skills..." and returns it to the server. The input is the prompt sentence, and the output is the generated response.

[0206] Step 7:

[0207] The server sends a response to the user terminal.

[0208] The server sends the generated response to the user terminal. For example, the server sends the generated response as an HTTP response to the user's web browser. The input is the generated response, and the output is the HTTP response to the user terminal.

[0209] Step 8:

[0210] The user confirms the response.

[0211] The user sees the generated response in their web browser. For example, the user reads the message "To be successful as a data scientist, it is important that you master the following skills..." The input is the HTTP response and the output is the user's understanding.

[0212] (Application example 2)

[0213] 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."

[0214] Conventional systems lack a means for users to specifically input their future goals and aspirations and then provide personalized content based on those goals. This makes it difficult to efficiently provide information and resources that match the user's vision of the future. Furthermore, there is a need for a system that can generate specific content based on the user's future goals, thereby increasing the user's motivation and helping them achieve their goals.

[0215] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing life, a means for generating relevant content based on the user's future goals and hopes, and a means for providing the generated content to the user. This makes it possible to provide personalized content that matches the user's vision of the future.

[0216] "User" refers to any individual or entity that uses the System.

[0217] "Past and current experience" refers to information such as the user's work history, educational background, and skills.

[0218] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by the user.

[0219] "Values" refers to the beliefs, ethics, and lifestyles that users consider important.

[0220] "Image of the future" refers to the goals that users want to achieve in the future, their desired lifestyle, income goals, etc.

[0221] An "AI agent" refers to an artificial intelligence system that analyzes information input by the user and suggests future possibilities.

[0222] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[0223] "Life visualization tools" refers to tools and technologies that allow users to visually display future scenarios.

[0224] "Content" refers to information, videos, articles, podcasts, and other media provided to users.

[0225] "Generation means" refers to the technology or algorithms used to create relevant content based on user input.

[0226] "Means of delivery" refers to the technology and methods used to deliver the generated content to users.

[0227] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for generating relevant content based on the user's future goals and hopes, and means for providing the generated content to the user.

[0228] System configuration

[0229] 1. User input method:

[0230] Users use devices such as smartphones or computers to input their past and present career history, skills, values, and vision for the future, and this information is sent to a server.

[0231] 2. AI Agents:

[0232] The server receives the information sent by the user and analyzes it using an AI agent, which uses a generative AI model to suggest future possibilities for the user.

[0233] 3. Simulation methods:

[0234] The server runs a simulation based on the proposed future possibilities and visualizes the user's life, and the results of this simulation are displayed on the user's device.

[0235] 4. Content Generation Methods:

[0236] The server generates relevant content based on the user's future goals and aspirations, using generative AI models in the process to provide the most relevant information to the user.

[0237] 5. Content Delivery Method:

[0238] The server delivers the generated content to the user's device, where the user can view the content via their smartphone or PC.

[0239] Hardware and software used

[0240] Hardware: smartphones, PCs, servers

[0241] Software: Python, OpenAI API

[0242] Data processing and calculation

[0243] The server receives the data sent by the user and performs the following processing.

[0244] 1. Data analysis: Analyze the user's background, skills, values, and future vision.

[0245] 2. Prompt generation: Generate prompts based on the user's goals.

[0246] 3. Content generation: Use generative AI models to generate personalized content based on prompts.

[0247] Specific examples

[0248] For example, if a user enters the goals "become a data scientist," "achieve remote work," and "earn 10 million yen a year," the following prompt sentences will be generated:

[0249] Example prompt sentence:

[0250] The user's career goal is to become a data scientist, their desired lifestyle is to work remotely, and their future income goal is to earn 10 million yen a year. Please suggest content related to this.

[0251] By inputting this prompt into a generative AI model, the system can provide users with the most appropriate content, such as learning resources for becoming a data scientist, tips for remote work, or a career path to earning 10 million yen a year.

[0252] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0253] Step 1:

[0254] Users use devices such as smartphones or PCs to input their past and present career history, skills, values, and vision for the future. The input information is sent from the device to a server. Specifically, the user enters information into an input form and presses the send button, which sends the data to the server.

[0255] Step 2:

[0256] The server receives the data sent by the user and stores it in a database. The stored data includes the user's career history, skills, values, and future image. Specifically, the server analyzes the received data, converts it into an appropriate format, and stores it in the database.

[0257] Step 3:

[0258] The server generates prompts based on the stored data to suggest future possibilities for the user. The generated prompts are created based on the user's goals and wishes. Specifically, the server analyzes the user's input data and constructs prompts suitable for the generative AI model.

[0259] Step 4:

[0260] The server uses the generated prompt sentence to send a request to the generative AI model, which then generates personalized content based on the prompt sentence. Specifically, the server uses the OpenAI API to send the prompt sentence and receive the generated content.

[0261] Step 5:

[0262] The server analyzes the generated content and converts it into a format for providing to the user. Specifically, the server converts the generated content into an appropriate format and arranges it in a form that is easy for the user to view.

[0263] Step 6:

[0264] The server delivers the prepared content to the user's device, who can then view it via a smartphone or PC. Specifically, the server sends the content to the user's device, allowing the user to view the content through an application.

[0265] Step 7:

[0266] The user browses the provided content and obtains information and resources for achieving future goals. Specifically, the user browses the content through the application and obtains the necessary information.

[0267] Example 3

[0268] 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."

[0269] Conventional career path and life plan suggestion systems have difficulty fully analyzing the information entered by users and making optimal suggestions for each individual user. Furthermore, they lacked a way to visually understand the future impact of the suggested career path or life plan, making it difficult for users to visualize the specifics of the suggestions. This led to problems such as insufficient decision-making when planning their own future.

[0270] 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.

[0271] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing a life, natural language processing means for analyzing the user's input information, machine learning means for proposing optimal career paths and life plans based on the analysis results, means for simulating and visualizing future life based on the proposed career paths and life plans, and visualization means for displaying the simulation results in graphs and charts.This allows the user to be proposed optimal career paths and life plans based on their own skill sets and values, and to visually understand the impact of these on their future.

[0272] "User" refers to an individual who uses the system to plan their own career path or life plan.

[0273] "Career" refers to the user's past job history, educational background, etc.

[0274] "Skills" refers to the specialized knowledge and techniques possessed by the user.

[0275] "Values" refer to the beliefs and ideas that users consider important.

[0276] "Image of the future" refers to the hopes and goals that users have for the future.

[0277] An "AI agent" is software that analyzes information entered by the user and suggests optimal career paths and life plans.

[0278] "Simulation" refers to the process of predicting a user's future life based on suggested career paths and life plans.

[0279] "Visualization" refers to displaying simulation results in a visual format such as a graph or chart.

[0280] "Natural language processing means" refers to technology for analyzing text data entered by a user.

[0281] "Machine learning methods" refer to algorithms that suggest optimal career paths and life plans based on past data.

[0282] "Graphs and charts" refer to diagrams that visually display the results of a simulation.

[0283] This invention is a system that inputs a user's past and present career history, skills, values, etc., and based on that, proposes future career paths and life plans, and then simulates and visualizes the proposals. Specific embodiments of this system are described below.

[0284] System configuration

[0285] Hardware and software configuration:

[0286] Server: Receives data, analyzes, simulates, and visualizes it. The server must have a powerful processor and ample memory.

[0287] Device: The device where a user enters information and sees results, such as a computer, tablet, or smartphone.

[0288] Natural language processing libraries: Use Python NLP libraries such as spaCy and NLTK.

[0289] Machine learning libraries: Use scikit-learn or TENSORFLOW (registered trademark).

[0290] Visualization tools: Use Matplotlib or Plotly.

[0291] Program processing

[0292] Data collection and analysis:

[0293] The user uses the device to input information such as their skill set, values, and interests. For example, the user inputs a skill set such as "programming (Python, Java (registered trademark)) and data analysis" or values ​​such as "work-life balance and social contribution." The device sends the input information to the server. The server analyzes the received data using a natural language processing library (e.g., spaCy or NLTK).

[0294] Career path and life plan suggestions:

[0295] The server then uses the analysis results to suggest the best career path or life plan for the user. For example, it might suggest jobs such as data scientist or software engineer at an edtech company based on the user's skill set and values. It then uses machine learning libraries (such as scikit-learn and TensorFlow) to compare the results with past data to determine the best option.

[0296] Simulation and visualization:

[0297] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib or Plotly). The server sends the generated graphs and charts to the device, which then displays them to the user.

[0298] Specific examples

[0299] The user enters the following information:

[0300] Skill set: Programming (Python, Java), Data analysis

[0301] Values: Work-life balance, social contribution

[0302] Interests: Environmental protection, education

[0303] The AI ​​agent analyzes this information and makes suggestions such as:

[0304] Suitable jobs: Data scientist, software engineer at an edtech company

[0305] Suitable companies: Environmental startups, educational nonprofits

[0306] It also simulates your future income and lifestyle based on your proposed career path, displaying graphs like the one below:

[0307] Income trend graph

[0308] A chart showing lifestyle changes

[0309] Example prompt sentence:

[0310] "Please suggest suitable jobs and companies based on the user's skill set and values. The user's skill set is programming (Python, Java) and data analysis. Their values ​​are work-life balance and social contribution. Their interests are environmental protection and education."

[0311] In this way, the user is presented with an optimal career path and life plan based on their own skill set and values, and is able to visually understand the impact of these on the future. The flow of the identification process in Example 3 will be described with reference to FIG.

[0312] Step 1:

[0313] The user uses the device to input information such as their skill set, values, and interests. For example, the user might input a skill set such as "programming (Python, Java) and data analysis" or values ​​such as "work-life balance and social contribution." The input information is saved in the input form on the device.

[0314] Input: Information about the user's skill set, values, interests, etc.

[0315] Output: User information stored on the device

[0316] Step 2:

[0317] The device converts the entered user information into JSON format and sends it to the server using an HTTP POST request, which then stores the received data in a database.

[0318] Input: User information stored on the device

[0319] Output: User information sent to the server

[0320] Step 3:

[0321] The server passes the stored data to an AI agent, which uses a natural language processing library (e.g., spaCy or NLTK) to tokenize the text data and analyze the user's skill set and values. For example, it analyzes the skill set "Programming (Python, Java)" and identifies related job titles.

[0322] Input: User information stored on the server

[0323] Output: Analyzed user's skill set and values

[0324] Step 4:

[0325] The AI ​​agent applies machine learning models using scikit-learn and TensorFlow to suggest optimal career paths and life plans for users, such as jobs like "data scientist" or "software engineer at an edtech company."

[0326] Input: Parsed user's skill set and values

[0327] Output: Suggested career path or life plan

[0328] Step 5:

[0329] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib and Plotly).

[0330] Input: Proposed career path or life plan

[0331] Output: Graphs and charts of simulation results

[0332] Step 6:

[0333] The server sends the generated graphs and charts to the terminal, which then displays the received graphs and charts to the user. For example, it displays a graph showing changes in income or lifestyle.

[0334] Input: Graphs and charts of simulation results

[0335] Output: Graphs and charts displayed on the terminal

[0336] (Application example 3)

[0337] 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."

[0338] Conventional career planning systems can suggest future possibilities based on a user's past and present career history, skills, and values, but they lack the means to specifically simulate and visualize future income based on the proposed career path. This makes it difficult for users to understand the specific economic impact of the proposed career path, making it difficult for them to make decisions.

[0339] 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 inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the proposed career path and visualizing it in a graph. This makes it easier for the user to understand the specific economic impact of the proposed career path, enabling more appropriate decision-making.

[0340] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, and values ​​into the system.

[0341] The "means for inputting the user's image of the future" is an interface that allows the user to input information such as their future goals and desired lifestyle into the system.

[0342] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the optimal career path and life plan.

[0343] "Means to simulate proposed possibilities and visualize life" is a function that simulates the user's future life based on proposed career paths and life plans and displays them in graphs and charts.

[0344] "Means for simulating future income based on a proposed career path and visualizing it in a graph" is a function for predicting future income based on a proposed career path and displaying the results in a graph.

[0345] A system for carrying out this invention includes means for inputting a user's past and present career history, skills, values, etc.; means for inputting an image of the user's future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the suggested career path and visualizing it in a graph.

[0346] 1. Program Generation

[0347] The program for this system can be implemented using Python. Specifically, we will build an AI agent to analyze user input data and propose optimal career paths. Furthermore, we will add a function to simulate future income based on the proposed career paths and visualize the results in a graph.

[0348] 2. Explanation of program processing

[0349] The server receives and analyzes information entered by the user, such as their career history, skills, and values. This analysis is performed using natural language processing and machine learning algorithms. Specific software used is the Python libraries Numpy and Pandas, and the machine learning library Scikit-learn.

[0350] Based on the analysis results, the AI ​​agent will suggest the most suitable career path for the user. This suggestion is based on the user's skill set and values. For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the AI ​​agent will suggest "software engineer."

[0351] Next, future earnings are simulated based on the proposed career path. The simulation uses data such as earnings growth rates and industry average salaries. These data can be obtained from external databases or APIs. The simulation results are visualized in graphs using Matplotlib.

[0352] 3. Adding concrete examples

[0353] For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the AI ​​agent will suggest "software engineer" and simulate their future income and display it in a graph.

[0354] Prompt Sentence Examples

[0355] Create a Python program that suggests the optimal career path based on the user's skills and values, simulates future income based on that career path, and visualizes it in a graph. The user's skills are "programming" and "data analysis," and their values ​​are "innovation" and "stability."

[0356] In this way, users can better understand the specific financial implications of proposed career paths and make better decisions.

[0357] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0358] Step 1:

[0359] Users use a terminal to input information such as their past and present career history, skills, and values. The input information is then sent to the server. The input data includes work history, educational background, specialized knowledge, skills, and values.

[0360] Step 2:

[0361] The server receives input data sent by the user and stores it in a database. The stored data is used for subsequent analysis. Specifically, the data is formatted using the Python Pandas library and converted into an analyzable format.

[0362] Step 3:

[0363] The server analyzes the stored data using natural language processing and machine learning algorithms. Specifically, it uses the Scikit-learn library to cluster the user's skill set and values ​​and generate a model to suggest the optimal career path. Based on the input data, it identifies the most suitable job type and career path for the user.

[0364] Step 4:

[0365] The server then suggests the most suitable career path for the user based on the analysis results. The suggested career path is sent to the terminal and displayed to the user. For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the server will suggest "software engineer."

[0366] Step 5:

[0367] The server simulates future income based on the proposed career path. The simulation uses data such as income growth rate and industry average salary. This data is obtained from external databases and APIs. Specifically, the server uses the Numpy library to calculate income growth and predict future income.

[0368] Step 6:

[0369] The server visualizes the simulation results in graphs using the Matplotlib library. The graphs are then sent to the terminal and displayed to the user. For example, a graph could show how the user's future income will change based on the proposed career path.

[0370] Step 7:

[0371] Users can use their devices to check the proposed career paths and simulation results and consider their future life plans. This makes it easier for users to understand the specific economic impact of the proposed career paths, enabling them to make more appropriate decisions.

[0372] 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.

[0373] "Example 1"

[0374] In one embodiment of the present invention, the AI ​​agent includes an emotion engine that recognizes a user's emotions. The emotion engine reads emotions from the user's tone of voice, facial expressions, and choice of words. For example, if the user says, "Thinking about my future makes me anxious," the emotion engine recognizes that the user is feeling anxious.

[0375] "Example 2"

[0376] The emotion engine suggests future possibilities that suit the user based on the emotions it recognizes. For example, if the user is feeling anxious, the emotion engine will suggest possibilities that include a stable job and a steady income. If the user is excited, the emotion engine will suggest possibilities that include new challenges and adventures.

[0377] "Example 3"

[0378] The emotion engine simulates suggested possibilities based on the emotions it recognizes. For example, if the user feels anxious, the emotion engine will simulate a life plan that involves a stable job. If the user feels excited, the emotion engine will simulate a life plan that includes new challenges.

[0379] The processing flow of each embodiment will be described below.

[0380] "Example 1"

[0381] Step 1: The AI ​​agent interacts with the user and reads their emotions from their tone of voice, facial expressions, and choice of words.

[0382] Step 2: The emotion engine analyzes the emotions it reads and determines the user's current emotional state.

[0383] "Example 2"

[0384] Step 1: The emotion engine considers future possibilities that suit the user based on the user's emotional state.

[0385] Step 2: The emotion engine presents the possibilities it has considered to the user.

[0386] "Example 3"

[0387] Step 1: The emotion engine simulates a life plan based on the user's emotional state and the possibilities they present.

[0388] Step 2: The emotion engine presents the simulated life plan to the user.

[0389] Example 1

[0390] 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."

[0391] Previous systems provided a means for users to input information such as their past and present career history, skills, and values, but lacked the ability to recognize users' emotions and generate feedback based on them. As a result, suggestions and feedback were uniform, making it difficult to provide appropriate advice tailored to each individual user's emotions and situation. Furthermore, systems lacked the means to specifically simulate users' future images and visualize their lives. This made it difficult for users to concretely understand their future possibilities and choose appropriate actions.

[0392] 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.

[0393] In this invention, the server includes: means for inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that proposes future possibilities that suit the user based on the input information; means for simulating the proposed possibilities and visualizing life; an emotion engine that recognizes emotions from the user's tone of voice, facial expressions, choice of words, etc.; a generative AI model that generates feedback based on the emotions recognized by the emotion engine; and means for providing the generated feedback to the user. This provides individualized feedback that takes the user's emotions into consideration, enabling the user to specifically understand their future possibilities and select appropriate actions.

[0394] "Means for inputting a user's past and present career history, skills, values, etc." refers to a device or software that provides an interface for a user to input information such as their work history, skill set, values, hobbies, and interests.

[0395] "Means for inputting the user's image of the future" refers to a device or software that provides an interface for the user to input information such as their future goals and desired career path.

[0396] An "AI agent" is a program or system that uses artificial intelligence to suggest future possibilities that suit the user based on information entered by the user.

[0397] A "life visualization tool" is a device or software that simulates proposed future possibilities and visually displays them to the user.

[0398] An "emotion engine" is a program or system that recognizes emotions from a user's tone of voice, facial expressions, choice of words, etc.

[0399] A "generative AI model" is a program or system that uses artificial intelligence to generate feedback based on emotions recognized by an emotion engine.

[0400] A "means for providing feedback" is a device or software for displaying or notifying the generated feedback to the user.

[0401] This invention is a system that allows users to input their past and present career history, skills, values, etc., suggests future possibilities, recognizes emotions, and provides feedback. Specific embodiments of this system are described below.

[0402] Entering user information

[0403] Users use a web browser or mobile application to enter information such as their work history, skill set, values, hobbies, and interests. This is done through a user interface using HTML and JavaScript. For example, a user might enter information such as "5 years of experience as a software engineer," "skills in Python, Java, and machine learning," "emphasis on teamwork," "reading, hiking," and "interest in data science."

[0404] Sending information

[0405] The terminal transmits the information entered by the user in real time to the server, which uses the HTTPS protocol for secure data transfer and stores the received information in a database.

[0406] emotion recognition

[0407] The server analyzes the received information and the user's comments using an emotion engine. The emotion engine uses voice recognition software (e.g., a voice recognition API) or image analysis software (e.g., a face recognition API) to analyze the user's tone of voice and facial expressions to recognize emotions. For example, if a user says, "I've been interested in data science lately, but I don't know where to start," the emotion engine recognizes that the user is excited.

[0408] Data analysis

[0409] The server analyzes the user's input information and emotion recognition results using a generative AI model (e.g., a natural language processing model). The generative AI model processes the data to generate appropriate feedback and advice based on the user's interests and emotions.

[0410] Generate feedback

[0411] The server uses generative AI models to generate feedback and advice for users. For example, if a user inputs that they are interested in data science and the emotion engine recognizes their excitement, the server will generate feedback such as, "Based on your interests, we recommend the following online courses."

[0412] Send Feedback

[0413] The server then sends the generated feedback to the device, again securely using the HTTPS protocol.

[0414] View Feedback

[0415] The terminal displays the feedback received from the server on the user interface, allowing the user to check the displayed feedback and decide on the next action to take.

[0416] Examples of concrete examples and prompts

[0417] As an example, a user logs into a system and enters the following information:

[0418] Work experience: 5 years of experience as a software engineer

[0419] Skillset: Python, Java, Machine Learning

[0420] Values: Teamwork

[0421] Hobbies: Reading, hiking

[0422] Interests: Data Science

[0423] A user might say, "I've recently become interested in data science, but I don't know where to start." The emotion engine recognizes the user's excitement, and the server generates feedback such as, "Based on your interests, we recommend the following online courses," and sends it to the device. The device then displays this feedback in the user interface, where the user can confirm it.

[0424] Example prompt sentence:

[0425] "Design a system where users can input their background, skills, values, hobbies, and interests, and the emotion engine can recognize their emotions. For example, if a user says, 'I've been interested in data science lately, but I don't know where to start,' the emotion engine should recognize that the user is excited and provide feedback recommending appropriate online courses."

[0426] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0427] Step 1:

[0428] Users use a web browser or mobile application to input information such as their work history, skill set, values, hobbies, and interests. The input information is sent to the server in real time by the device. Examples of input data include "5 years of experience as a software engineer," "skills in Python, Java, and machine learning," "emphasis on teamwork," "reading, hiking," and "interest in data science." The server then stores this information in a database.

[0429] Step 2:

[0430] The server receives the information entered by the user and stores it in a database. The stored information is used for subsequent processing. Specifically, the server receives the data securely using the HTTPS protocol and stores it in a database. The input data includes the user's background, skills, values, hobbies, interests, etc., and this data is later analyzed.

[0431] Step 3:

[0432] When a user expresses emotions through voice input or facial expressions, the device captures them and sends them to the server. The server uses an emotion engine to analyze the user's tone of voice and facial expressions to recognize emotions. For example, if a user says, "I've been interested in data science lately, but I don't know where to start," the emotion engine will recognize that the user is excited. The input data is voice and images, and the output is recognized emotional data.

[0433] Step 4:

[0434] The server uses a generative AI model to analyze the user's input information and emotion recognition results. The generative AI model processes the data to generate appropriate feedback and advice based on the user's interests and emotions. For example, if a user inputs that they are interested in data science and the emotion engine recognizes excitement, the generative AI model will generate feedback such as, "Based on your interests, we recommend the following online courses." The input data is the user's background, skills, values, hobbies, interests, and emotion data, and the output is the generated feedback.

[0435] Step 5:

[0436] The server sends the generated feedback to the device, also securely using the HTTPS protocol. The input data is the generated feedback, and the output is the data sent to the device.

[0437] Step 6:

[0438] The terminal displays the feedback received from the server on a user interface. The user can check the displayed feedback and decide on the next action. Specifically, the terminal visually displays the feedback so that the user can check it. The input data is the feedback from the server, and the output is the feedback displayed on the user interface.

[0439] (Application example 1)

[0440] 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."

[0441] Conventional systems can suggest future possibilities based on a user's background, skills, and values, but they cannot provide suggestions or warnings that take into account the user's emotional state. As a result, they cannot respond appropriately when the user is feeling anxious or stressed, and their psychological support is insufficient. Furthermore, since there is no function to detect abnormal emotional states and issue warnings, it is difficult to ensure the user's safety and sense of security.

[0442] 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.

[0443] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, an emotion engine that recognizes the user's emotions, means for the emotion engine to read emotions from the user's tone of voice, facial expressions, choice of words, etc., and means for issuing a warning when an abnormal emotional state is detected. This makes it possible to monitor the user's emotional state in real time and issue an appropriate warning when an abnormal emotional state is detected.

[0444] "Means for inputting users' past and present career history, skills, values, etc." refers to means that provide an interface for users to input information such as their work history, skill set, values, hobbies, and interests.

[0445] "Means for inputting the user's image of the future" refers to a means for providing an interface for the user to input information such as their future goals and desired career path.

[0446] An "AI agent" is an artificial intelligence system that suggests future possibilities that suit the user based on the information the user inputs.

[0447] "Means for simulating proposed possibilities and visualizing life" refers to a means for simulating and visually displaying a user's life plan based on future possibilities proposed by an AI agent.

[0448] The "emotion engine" is an analytical engine that reads emotions from the user's tone of voice, facial expressions, choice of words, etc.

[0449] "The means by which the emotion engine reads emotions from the user's tone of voice, facial expressions, choice of words, etc." refers to the means by which the emotion engine analyzes the user's audio and video data and recognizes the user's emotional state.

[0450] The "means for issuing a warning when an abnormal emotional state is detected" is a means for the emotion engine to monitor the emotional state of the user and issue a warning to the user when an abnormal emotional state is detected.

[0451] A system for carrying out this invention includes: means for inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing life; an emotion engine that recognizes the user's emotions; means for the emotion engine to read the user's emotions from the user's tone of voice, facial expressions, choice of words, etc.; and means for issuing a warning when an abnormal emotional state is detected.

[0452] System configuration

[0453] This system uses the following hardware and software:

[0454] Hardware: Smartphone camera and microphone

[0455] Software: OpenCV, Keras, SpeechRecognition, Transformers

[0456] Program processing

[0457] The server receives information such as career history, skills, and values ​​entered by the user via smartphone and stores it in a database. It then provides an interface for the user to enter their future goals and desired career path. Based on this information, the AI ​​agent suggests future possibilities that suit the user.

[0458] The proposed future possibilities are visually displayed through a simulation tool, visualized as the user's life plan. Furthermore, an emotion engine analyzes the user's tone of voice and facial expressions to monitor their emotional state in real time. The emotion engine uses OpenCV to detect the user's face from camera footage and recognizes emotions using a Keras model. It also converts audio from the microphone into text using the SpeechRecognition library, and analyzes the sentiment of the text using the Transformers library's emotion analysis pipeline.

[0459] If an abnormal emotional state is detected, the system will alert the user. For example, if a user says, "Thinking about my future makes me anxious," the emotion engine will recognize that the user is feeling anxious and issue an appropriate warning.

[0460] Specific examples

[0461] As a concrete example, if a user says, "I feel anxious when I think about my future," the system will act as follows:

[0462] 1. The user's face is detected from the camera footage and the emotion is recognized as "Fear."

[0463] 2. The audio from the microphone is converted into text, and the resulting text is, "Thinking about my future makes me anxious."

[0464] 3. This text is input into the sentiment analysis pipeline and is recognized as "NEGATIVE."

[0465] 4. The emotion is "Fear" or "Negative" and therefore raises a warning.

[0466] Example prompts to input to a generative AI model:

[0467] How would an emotion-aware security application behave if a user said, "Thinking about my future makes me anxious"?

[0468] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0469] Step 1:

[0470] Users use their smartphones to enter information about their past and present career history, skills, values, etc.

[0471] Input: Information about the user, such as their work history, skill set, values, hobbies, and interests.

[0472] Output: The input information is saved in the database.

[0473] How it works: The user enters information through the smartphone interface, the server receives the information, and stores it in a database.

[0474] Step 2:

[0475] The user enters their future goals and desired career path.

[0476] Input: The user's future goals and desired career path.

[0477] Output: The input information is saved in the database.

[0478] Specific operation: The user enters their future goals and desired career path through the smartphone interface, and the server receives the information and stores it in a database.

[0479] Step 3:

[0480] Based on the information entered, the server suggests future possibilities that suit the user.

[0481] Input: User's background, skills, values, and future goals stored in a database.

[0482] Output: A proposal of future possibilities that suit the user.

[0483] How it works: The server uses an AI agent to analyze the information stored in the database and suggest future jobs, companies, and next steps that suit the user.

[0484] Step 4:

[0485] It simulates proposed future possibilities and visualizes the user's life plan.

[0486] Input: Proposed future possibilities.

[0487] Output: A visual representation of the user's life plan.

[0488] Specific operation: The server uses a simulation tool to create a life plan for the user based on the proposed future possibilities and visually displays it on the smartphone screen.

[0489] Step 5:

[0490] The emotion engine analyzes the user's tone of voice and facial expressions to monitor their emotional state in real time.

[0491] Input: User's audio and video data.

[0492] Output: The user's emotional state.

[0493] How it works: The smartphone's camera and microphone are used to capture the user's voice and video, and the server uses OpenCV and Keras models to recognize emotions.

[0494] Step 6:

[0495] The emotion engine issues a warning if it detects an abnormal emotional state.

[0496] Input: The user's emotional state.

[0497] Output: A warning message.

[0498] Specific operation: The server uses the emotion engine to monitor the user's emotional state, and if an abnormal emotional state (e.g., fear, sad, negative) is detected, a warning message is displayed on the smartphone.

[0499] Example 2

[0500] 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."

[0501] Conventional systems can suggest future possibilities based on a user's past and present career history, skills, and values, but they cannot take the user's emotions into consideration when making suggestions, which makes it difficult to find the best future possibilities for the user. In addition, if the proposed future possibilities do not match the user's emotions, the user is less likely to accept the suggestions.

[0502] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting the user's past and present career, skills, values, etc., a means for inputting the user's image of the future, a means for recognizing the user's emotions based on the input information, a means using a generative AI model for proposing future possibilities suitable for the user based on the recognized emotions, and a means for simulating the proposed possibilities and visualizing the user's life. This makes it possible to propose optimal future possibilities taking the user's emotions into consideration.

[0503] A "user" is an individual who uses the system to input their future goals and aspirations and receive suggestions.

[0504] "Career" refers to historical information such as the user's past work experience and educational background.

[0505] "Skills" refers to the specialized knowledge and techniques that a user possesses.

[0506] "Values" are the beliefs and ideas that users consider important.

[0507] "Image of the future" refers to the goals and hopes that users have for the future.

[0508] "Means for recognizing emotions" refers to technology that analyzes information input by a user and identifies the user's emotions from that information.

[0509] A "generative AI model" is an artificial intelligence technology that suggests future possibilities that suit a user based on the user's input information and recognized emotions.

[0510] A "simulation tool" is a technology that visually displays a user's life based on proposed possible futures.

[0511] "Life plans" refer to specific plans and scenarios regarding the user's future life.

[0512] This invention is a system that allows a user to input their own future goals and hopes, recognizes their emotions based on the input, and suggests optimal future possibilities. Specific embodiments of this system will be described below.

[0513] System configuration

[0514] The system consists of a terminal that collects user input information, a server that analyzes the input information and recognizes emotions, a server that generates suggestions using a generative AI model, and a terminal that displays the suggestions to the user.

[0515] Hardware and software used

[0516] The terminals are general computing devices such as PCs and smartphones, which access web applications via a web browser and collect user input information.

[0517] The server is a powerful computer that receives and analyzes user input. The server has the following software installed:

[0518] Python: a programming language

[0519] TextBlob and VADER: Sentiment analysis libraries

[0520] Generative AI models (e.g., GPT-4)

[0521] Data processing and calculation

[0522] The user accesses the web application using a terminal and enters the following information:

[0523] Career goals (e.g., "I want to work as a data scientist in the future.")

[0524] Desired lifestyle (e.g., "I want to work in an environment where I can work remotely")

[0525] Future income goals (e.g., "I want to earn 10 million yen a year")

[0526] The terminal sends the information entered by the user in JSON format to the server using the HTTPS protocol to ensure data security.

[0527] The server parses the received JSON data and uses the emotion engine to recognize the user's emotion. For example, it analyzes emotions as follows:

[0528] Calculate positive / negative score of text using TextBlob

[0529] Deep dive into text sentiment scores using VADER

[0530] As a result of the analysis, it is recognized that the user is feeling "anxiety."

[0531] The server sends the following prompt to the generative AI model:

[0532] "The user's future goal is to become a data scientist and hopes to work in an environment that allows remote work. He also aims to earn 10 million yen a year. The user is currently feeling anxious. Please provide this user with specific advice on how to secure a stable job and income."

[0533] Based on this prompt, the generative AI model (GPT-4) generates the following suggestions:

[0534] "If you're aiming for a career as a data scientist, I recommend first learning the basics of data analysis and gaining experience at a stable company. More and more companies are offering remote work, so it's a good idea to look for remote work positions. To aim for an annual salary of 10 million yen, it's important to deepen your expertise and aim for a project manager or leadership role."

[0535] The server sends the suggestions received from the generative AI model to the user's device, which then displays them to the user, who can review the suggestions and use them to plan for the future.

[0536] In this way, it is possible to propose optimal future possibilities that take the user's emotions into consideration.

[0537] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0538] Step 1:

[0539] Users access the web application using their device and enter information such as their career goals, desired lifestyle, and future income goals. The entered information is saved in an input form on the device.

[0540] Step 2:

[0541] The terminal converts the information entered by the user into JSON format and sends it to the server using the HTTPS protocol. The input data includes information such as career goals, desired lifestyle, and future income goals.

[0542] Step 3:

[0543] The server parses the received JSON data and uses an emotion engine to recognize the user's emotions. Specifically, it uses an emotion analysis library such as TextBlob or VADER to calculate the positive / negative score and emotion score of the text. The input data is the user's input information, and the output data is the recognized emotion (e.g., "anxiety").

[0544] Step 4:

[0545] The server generates a prompt sentence based on the recognized emotion. The prompt sentence includes the user's goals, desires, and recognized emotion. The generated prompt sentence is sent to the generative AI model. The input data are the user's goals, desires, and recognized emotion, and the output data is the generated prompt sentence.

[0546] Step 5:

[0547] The server sends a prompt to a generative AI model (e.g., GPT-4) to generate a specific suggestion for the user. The generative AI model generates a suggestion based on the prompt and returns it to the server. The input data is the prompt, and the output data is the generated suggestion.

[0548] Step 6:

[0549] The server sends the proposals received from the generative AI model to the user's device. The input data is the generated proposal, and the output data is the proposal displayed on the user's device.

[0550] Step 7:

[0551] The terminal displays the proposals received from the server to the user, who can then check the displayed proposals and use them for future planning. The input data is the proposal sent from the server, and the output data is the proposal displayed to the user.

[0552] (Application example 2)

[0553] 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."

[0554] Conventional future prediction systems have the problem of not being able to provide optimal suggestions for users because they suggest future possibilities without taking the user's emotional state into consideration. Furthermore, because the future possibilities generated based on the user's input information are not specific, it is difficult for users to understand the specific steps they need to take to realize the suggestions.

[0555] 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.

[0556] In this invention, the server includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an emotion engine that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing the user's life, and a means for recognizing the user's emotional state and suggesting appropriate future possibilities using a generative AI model. This makes it possible to suggest optimal future possibilities based on the user's emotional state, enabling the creation of a specific life plan.

[0557] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, beliefs, and values ​​into the system.

[0558] The "means for inputting the user's image of the future" is an interface that allows the user to input their future goals and hopes, ideal lifestyle, income goals, etc. into the system.

[0559] An "emotion engine" is an algorithm or software that recognizes a user's emotional state from input information or text and suggests appropriate future possibilities based on that emotion.

[0560] A "generative AI model" is an artificial intelligence model that generates future possibilities based on the user's input information and emotional state.

[0561] "Means for simulating proposed possibilities and visualizing life" refers to software or an interface that simulates generated future possibilities as specific scenarios and presents them visually to the user.

[0562] A system for implementing this invention includes means for inputting a user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an emotion engine, a generative AI model, and means for simulating proposed possibilities and visualizing life.

[0563] System configuration

[0564] The system uses the following hardware and software:

[0565] Hardware: Smartphones, servers

[0566] Software: Python, OpenAI API, Emotion Recognition Library

[0567] Program processing

[0568] The server receives past and present career history, skills, values, and future image input by the user via a smartphone. This input information is acquired through the user interface.

[0569] The emotion engine then analyzes the user's input and recognizes their emotional state. The emotion engine uses the Emotion Recognition library to extract emotions from the text.

[0570] The generative AI model then generates future possibilities based on the emotional state recognized by the emotion engine and the user's input information. The generative AI model uses the OpenAI API and inputs prompt statements to generate appropriate future scenarios.

[0571] The generated future possibilities are visualized as specific scenarios using simulation tools, allowing users to concretely understand the proposed future possibilities.

[0572] Specific examples

[0573] For example, if the user types:

[0574] Career goal: "To become a data scientist"

[0575] Desired lifestyle: "Remote work"

[0576] Future income goal: "10 million yen annual income"

[0577] In this case, the emotion engine recognizes the user's emotional state from the input information and inputs the following prompt sentence into the generative AI model:

[0578] User Sentiment: Excitement

[0579] Career goal: To become a data scientist

[0580] Desired lifestyle: Remote work

[0581] Future income goal: 10 million yen per year

[0582] Suggest appropriate future possibilities.

[0583] Based on this prompt, the generative AI model proposes possible future scenarios that fit the user, and the proposed scenarios are visualized and presented to the user through a simulation tool.

[0584] In this way, users can concretely understand optimal future possibilities based on their emotional state and identify concrete steps to realize them.

[0585] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0586] Step 1:

[0587] Users use their smartphones to input their past and present career history, skills, values, and vision for the future. Specifically, users input their career goals, desired lifestyle, future income goals, etc. This input information is sent to the server via the smartphone's user interface. The input data is stored on the server in text format.

[0588] Step 2:

[0589] The server analyzes the received user input. Specifically, it processes the user's input as text data and passes it to the emotion engine. The emotion engine uses the Emotion Recognition library to recognize the user's emotional state from the text data. For example, if a user inputs "I want to be a data scientist," the emotion engine extracts the emotion "excited" from the text.

[0590] Step 3:

[0591] The server inputs a prompt sentence into the generative AI model based on the emotional state recognized by the emotion engine and the user's input information. Specifically, it generates the following prompt sentence:

[0592] User Sentiment: Excitement

[0593] Career goal: To become a data scientist

[0594] Desired lifestyle: Remote work

[0595] Future income goal: 10 million yen per year

[0596] Suggest appropriate future possibilities.

[0597] This prompt is then fed into a generative AI model using the OpenAI API.

[0598] Step 4:

[0599] The generative AI model generates future possibilities that fit the user based on the input prompt. Specifically, the generative AI model analyzes the prompt and generates future scenarios based on the user's emotional state and goals. The generated scenarios are returned to the server in text format.

[0600] Step 5:

[0601] The server receives the future scenario returned by the generative AI model and visualizes it as a specific scenario using simulation tools. Specifically, it simulates the user's life plan based on the generated scenario and generates data for visual display. This data is presented to the user in the form of graphs, charts, timelines, etc.

[0602] Step 6:

[0603] Users can view visualized future scenarios on their smartphones. Specifically, they can view graphs, charts, and timelines displayed on their smartphone screens to gain a concrete understanding of their own future possibilities. Based on the proposed scenarios, users can then create specific action plans.

[0604] Example 3

[0605] 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."

[0606] Conventional career path and life plan suggestion systems make suggestions based on the user's past and present information, but they have the problem of not being able to make suggestions or simulations that take into account the user's emotional state.In addition, there is a lack of a way to visually confirm the future life of the suggested career path or life plan, making it difficult for users to intuitively understand the effectiveness of the suggestions.

[0607] 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.

[0608] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing the user's life, means for analyzing the user's emotions and simulating the proposed possibilities based on the emotions, and means for displaying the simulation results in graphs and charts. This enables proposals and simulations that take the user's emotional state into consideration, and allows the user to visually confirm the future life of the proposed career path and life plan.

[0609] "User" refers to an individual who uses the system to propose and simulate their own career path and life plan.

[0610] "Career" refers to a user's past work experience, educational background, qualifications, etc.

[0611] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by the user.

[0612] "Values" refer to the beliefs, ways of thinking, and lifestyle standards that users consider important.

[0613] "Image of the future" refers to the hopes, goals, and visions that users have for the future.

[0614] An "AI agent" is a program that analyzes information entered by the user and suggests optimal career paths and life plans.

[0615] "Simulation" refers to the process of predicting and visually displaying a user's future life based on proposed career paths and life plans.

[0616] "Sentiment analysis" refers to the process of determining a user's emotional state from their input and adjusting suggestions and simulations accordingly.

[0617] "Graphs and charts" refer to diagrams that visually display the results of a simulation.

[0618] "Means" refers to a method, device, or program used to achieve a specific function.

[0619] This invention is a system that inputs a user's past and present career history, skills, values, etc., and proposes and simulates future career paths and life plans. Specific embodiments of this system are described below.

[0620] System configuration

[0621] The system consists of three main elements: a server, a terminal, and a user. The server receives input information from users, analyzes it, and generates proposals. The terminal is a device through which users input information and displays proposals and simulation results. Users are individuals who use the system to propose and simulate their own career paths and life plans.

[0622] Hardware and software used

[0623] Server: Use a server with high-performance computing capabilities. Specifically, you can use cloud services (e.g., Amazon Web Services, Microsoft® Azure®).

[0624] Database: Use a relational database such as MySQL or PostgreSQL.

[0625] AI agents: Use natural language processing libraries (e.g., NLTK, spaCy) and machine learning models (e.g., TensorFlow, PyTorch) implemented in Python.

[0626] Sentiment analysis engine: Uses an emotion recognition library (e.g., IBM Watson®, Microsoft Azure Emotion API).

[0627] Data visualization libraries: Use Matplotlib, Plotly, etc. to display simulation results in graphs and charts.

[0628] Program processing

[0629] The server receives the information entered by the user and stores it in a database. The server then sends the stored information to an AI agent, which uses natural language processing libraries and machine learning models to analyze the information entered by the user and generate an optimal career path or life plan.

[0630] The generated proposals are sent to the terminal via the server and displayed to the user. The user can then check the proposed career path and life plan. The server then runs a simulation based on the proposals to predict the user's future life. The simulation results are visually displayed in graphs and charts.

[0631] The emotion analysis engine determines the user's emotional state from their input and adjusts the suggestions and simulations accordingly. For example, if the user is feeling anxious, it will simulate a life plan that involves a stable job. Conversely, if the user is excited, it will simulate a life plan that includes new challenges.

[0632] Specific examples

[0633] Consider a scenario where a user enters, "I want to pursue a career as a data scientist." The server receives this information and sends it to an AI agent. The AI ​​agent analyzes the user's skill set (e.g., Python, machine learning, data analysis) and values ​​(e.g., stability, challenge) and suggests suitable jobs and companies (e.g., data scientist positions at major IT companies).

[0634] The system then simulates the user's future income and lifestyle based on the proposed career path, displaying graphs of the user's annual income and living expenses if they were to work as a data scientist, for example.

[0635] The emotion engine recognizes emotions from the text entered by the user, and if the user is feeling anxious, it simulates a life plan that involves a stable job. Conversely, if the user is excited, it simulates a life plan that includes new challenges.

[0636] Prompt Sentence Examples

[0637] "I want to advance my career as a data scientist. I have skills in Python and machine learning, but I'm looking for job stability. What career path is right for me?"

[0638] By inputting this prompt sentence into the generative AI model, it is possible to propose the optimal career path and life plan for the user. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0639] Step 1:

[0640] The user enters information

[0641] Users enter information such as their skill set, values, current occupation, and interests through the system interface. The information is sent to the server in text format. Specifically, users enter information into input fields on a web form or mobile app and click the "Submit" button.

[0642] Step 2:

[0643] The server receives the input information

[0644] The server receives the information sent by the user as an HTTP POST request. The received information is parsed in JSON format. The server temporarily stores the parsed information in memory.

[0645] Step 3:

[0646] The server saves the input information in a database

[0647] The server stores the received information in a database. Specifically, it executes an SQL query to store the information in a relational database (e.g., MySQL, PostgreSQL). Once the input information is stored in the database, it becomes available for further processing.

[0648] Step 4:

[0649] The server sends input information to the AI ​​agent.

[0650] The server sends the stored information to the AI ​​agent via a REST API in JSON format, which is implemented in Python and prepares to parse the received information.

[0651] Step 5:

[0652] The AI ​​agent analyzes the input information

[0653] The AI ​​agent uses natural language processing libraries (e.g., NLTK, spaCy) and machine learning models (e.g., TensorFlow, PyTorch) to analyze the user's input. Specifically, it tokenizes the input and analyzes the meaning of each token. The analysis results are output as data that extracts the user's skill set and values.

[0654] Step 6:

[0655] The AI ​​agent generates recommendations based on the analysis results.

[0656] Based on the analysis results, the AI ​​agent generates the optimal career path and life plan for the user. The generated proposals are returned to the server in JSON format. Specifically, it suggests suitable jobs and companies based on the user's skill set and values.

[0657] Step 7:

[0658] The server sends the proposal to the device

[0659] The server sends the proposal received from the AI ​​agent to the terminal. The proposal is sent as an HTTP response, and is passed to the terminal in JSON format. The terminal is the user's device (e.g., PC, smartphone).

[0660] Step 8:

[0661] The device displays the suggestions to the user

[0662] The device displays the received proposals to the user. Specifically, the proposals are displayed in HTML or UI components of the mobile app. The user can then check the proposed career path or life plan.

[0663] Step 9:

[0664] The server runs the simulation based on the proposal.

[0665] The server simulates the user's future life based on the proposed career path and life plan. The simulation includes a function to predict the user's future income and lifestyle. Specifically, it executes a simulation algorithm and generates a prediction result.

[0666] Step 10:

[0667] The server sends the simulation results to the device.

[0668] The server sends the simulation results to the terminal as an HTTP response, and the results are passed to the terminal in JSON format. The simulation results are displayed in graphs and charts.

[0669] Step 11:

[0670] The terminal displays the simulation results to the user.

[0671] The terminal displays the simulation results to the user. Specifically, the simulation results are visually displayed in graphs and charts, allowing the user to check their future income and lifestyle.

[0672] Step 12:

[0673] Emotion engine analyzes user emotions

[0674] The emotion engine analyzes the text and voice data entered by the user to determine the user's emotional state. Specifically, it uses an emotion recognition library (e.g., IBM Watson, Microsoft Azure Emotion API) to analyze the emotional state. The analysis results are output as data indicating the user's emotional state.

[0675] Step 13:

[0676] Emotion engine runs emotion-based simulations

[0677] The emotion engine simulates the proposed possibilities based on the user's emotional state. Specifically, it executes a simulation algorithm according to the user's emotional state and generates results. For example, if the user is feeling anxious, it will simulate a life plan if the user has a stable job.

[0678] Step 14:

[0679] The server sends the emotion-based simulation results to the device.

[0680] The server sends the simulation results received from the emotion engine to the device as an HTTP response, and the results are passed to the device in JSON format.

[0681] Step 15:

[0682] The device displays the emotion-based simulation results to the user.

[0683] The device displays the emotion-based simulation results to the user. Specifically, the simulation results are visually displayed in graphs and charts. The user can then check the life plan that corresponds to their own emotional state.

[0684] (Application example 3)

[0685] 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."

[0686] Conventional career path and life plan suggestion systems make suggestions based on the user's skill set and values, but they are unable to take the user's emotional state into account, which can result in the system failing to make the best suggestions for the user. It is also difficult for users to concretely imagine the future life of the proposed career path or life plan, making it difficult for them to decide whether to accept the suggestion. Furthermore, there is a lack of a way to visually display the simulation results in an easy-to-understand manner, making it difficult for users to concretely understand their future life.

[0687] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0688] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing life, means for inputting the user's emotional state, an emotion engine that adjusts the proposed possibilities based on the emotional state, means for analyzing the input information using a generative AI model, and means for displaying the simulation results in graphs and charts. This makes it possible to propose optimal career paths and life plans that take the user's emotional state into consideration, making it easier to concretely imagine the proposed future life.

[0689] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, beliefs, and values ​​into the system.

[0690] The "means for inputting the user's image of the future" is an interface that allows the user to input information such as their future goals and desired lifestyle into the system.

[0691] "An AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests optimal career paths and life plans.

[0692] "A means for simulating proposed possibilities and visualizing life" is a system for simulating future life based on proposed career paths and life plans and visually displaying the results.

[0693] "Means for inputting user's emotional state" refers to an interface that allows a user to input their current emotional state (e.g., anxiety, excitement, joy, etc.) into the system.

[0694] The "emotion engine that adjusts suggested possibilities based on emotional state" is a system for adjusting suggested career paths and life plans taking into account the user's emotional state.

[0695] "Means for analyzing input information using a generative AI model" refers to a system that uses a generative AI model to analyze information entered by a user and generate optimal suggestions.

[0696] "Means for displaying simulation results in graphs and charts" refers to a system that generates graphs and charts to visually display the results of a simulation in an easy-to-understand manner.

[0697] As an embodiment of the present invention, the following system can be constructed.

[0698] System Configuration

[0699] The system includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing life, a means for inputting the user's emotional state, an emotion engine that adjusts the suggested possibilities based on the emotional state, a means for analyzing the input information using a generative AI model, and a means for displaying the simulation results in graphs and charts.

[0700] Hardware and software used

[0701] Hardware: Smartphone

[0702] Software: Python, OpenAI API, Matplotlib

[0703] Data processing and calculation

[0704] The server receives information entered by the user on their smartphone, such as their past and present career history, skills, values, future image, and emotional state. This information is then analyzed using a generative AI model. Specifically, the server uses the OpenAI API to analyze the user's input and propose optimal career paths and life plans.

[0705] The suggested career paths and life plans are adjusted by an emotion engine based on the user's emotional state: for example, if the user is anxious, it will suggest a stable career, and if the user is excited, it will suggest a plan that includes new challenges.

[0706] The simulation tool simulates future life based on proposed career paths and life plans, and visualizes the results in graphs and charts. Matplotlib is used to visually display future income and lifestyle.

[0707] Specific examples

[0708] If a user has the skills of "programming" and "data analysis," and values ​​"stability" and "challenge," and inputs that their emotional state is "anxious," the AI ​​will suggest a stable occupation (e.g., data scientist) and simulate future income based on that occupation.

[0709] Prompt Sentence Examples

[0710] User Skill Set: Programming, Data Analysis

[0711] Values: Stability, Challenge

[0712] Emotional state: Anxiety

[0713] Please suggest the best career path and life plan for you.

[0714] In this way, users can more easily visualize their future possibilities and choose the most suitable career path and life plan.

[0715] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0716] Step 1:

[0717] Users use their smartphones to input information such as their past and present career history, skills, values, future image, and emotional state, which then collects detailed user profile information. The input information is then sent to the server.

[0718] Step 2:

[0719] The server inputs the received user information into the generative AI model. Specifically, it uses the OpenAI API to analyze information such as the user's skill set, values, and emotional state. As a result of the analysis, an optimal career path and life plan for the user is generated. The input is the user's profile information, and the output is a proposed career path or life plan.

[0720] Step 3:

[0721] The server inputs the generated career path or life plan into the emotion engine, which adjusts the proposal based on the user's emotional state. For example, if the user is feeling anxious, it will suggest a stable job, and if the user is excited, it will suggest a plan that includes new challenges. The input is the proposed career path or life plan and the user's emotional state, and the output is the adjusted career path or life plan.

[0722] Step 4:

[0723] The server inputs the adjusted career path and life plan into the simulation tool. The simulation tool simulates future life and predicts income and lifestyle. Specifically, Matplotlib is used to visualize future income and lifestyle in graphs and charts. The input is the adjusted career path and life plan, and the output is graphs and charts of the simulation results.

[0724] Step 5:

[0725] The server sends the generated graphs and charts to a smartphone. The user can visually check the simulation results on the smartphone screen. This makes it easier for the user to visualize the proposed career path and life plan. The input is the graphs and charts of the simulation results, and the output is the visual information displayed on the user's smartphone screen.

[0726] 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.

[0727] 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 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.

[0728] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0729] 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.

[0730] [Second embodiment]

[0731] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0732] 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.

[0733] 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).

[0734] 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.

[0735] 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.

[0736] 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).

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0743] "Example 1"

[0744] The system of the present invention provides a means for users to input their past and current career history, skills, values, etc. Specifically, the system allows users to input their own information through a user interface. For example, users can input their work history, skill set, values, hobbies, interests, etc.

[0745] "Example 2"

[0746] Next, we provide a means for users to input their future vision. Specifically, we allow users to input their future goals and aspirations. For example, users can input their career goals, desired lifestyle, future income goals, etc.

[0747] "Example 3"

[0748] We provide an AI agent that suggests future possibilities that suit the user based on the information entered. Specifically, the AI ​​agent analyzes the information entered by the user and, based on that, suggests the most suitable career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values. "Example 4"

[0749] Finally, the system provides a means to simulate the proposed possibilities and visualize the user's life. Specifically, the system simulates and visualizes the user's future life based on the career path and life plan proposed by the system. For example, the system can simulate the user's future income and lifestyle based on the proposed career path and display them in graphs and charts.

[0750] The processing flow of each embodiment will be described below.

[0751] "Example 1"

[0752] Step 1: The user enters their past and current career history, skills, values, etc. through the system's user interface. For example, the user enters their work history, skill set, values, hobbies, interests, etc.

[0753] "Example 2"

[0754] Step 1: The user inputs their own image of the future through the system's user interface. For example, the user inputs their career goals, desired lifestyle, future income goals, etc.

[0755] "Example 3"

[0756] Step 1: The AI ​​agent analyzes the user's input.

[0757] Step 2: The AI ​​agent uses the analysis results to suggest the optimal career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values.

[0758] "Example 4"

[0759] Step 1: The system simulates the user's future life based on the career path and life plan suggested by the system.

[0760] Step 2: Visualize the simulation results. For example, you can simulate the user's future income and lifestyle based on the proposed career path and display it in graphs and charts.

[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] Conventional systems provided a way for users to input information such as their past and present career history, skills, and values, but lacked the means to propose specific future possibilities based on this information, or to simulate and visualize these proposals. Furthermore, there was no established process for efficiently analyzing the data entered by users and generating appropriate responses using a generative AI model. This made it difficult to provide specific and useful advice to users.

[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: a means for inputting the user's past and present career history, skills, values, etc.; a means for inputting the user's image of the future; an AI agent that proposes future possibilities suitable for the user based on the input information; a means for simulating the proposed possibilities and visualizing life; a means for receiving the data input by the user and storing it in a database; a means for analyzing the stored data and inputting prompt sentences to the generative AI model; and a means for the generative AI model to generate responses and return the responses to the user. This makes it possible to propose specific future possibilities based on the user's input information and simulate and visualize the proposals. Furthermore, the generative AI model can be used to generate appropriate responses and provide specific and useful advice to the user.

[0766] "User" refers to an individual who uses the system to input their information and receive future opportunities and advice.

[0767] "Career" refers to the user's past job history, educational background, etc.

[0768] "Skills" refers to the skills, abilities, and expertise that a user possesses.

[0769] "Values" refer to the beliefs and ideas that users consider important.

[0770] "Image of the future" refers to the hopes, goals, and visions that users have for the future.

[0771] An "AI agent" refers to an artificial intelligence system that suggests future possibilities based on user input.

[0772] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[0773] "Database" means a digital storage system for storing and managing information entered by users.

[0774] A "generative AI model" refers to an artificial intelligence model that generates responses based on user input information.

[0775] "Prompt" refers to a textual instruction that is input to a generative AI model.

[0776] "Response" refers to the advice or suggestions that the generative AI model generates based on the prompt.

[0777] This invention is a system that allows users to input their past and present career history, skills, values, etc., and then suggests and simulates future possibilities based on that information. Specific embodiments of this system are described below.

[0778] First, a user accesses a user interface provided through a web browser. This interface is built using web technologies such as HTML, CSS, and JavaScript. The user then enters information such as work history, skill set, values, hobbies, and interests into an input form.

[0779] When the user completes the input and clicks the submit button, the device sends the input data as an HTTP request to the server. This request contains data in JSON format. The server receives the HTTP request sent from the device, analyzes the received data, and stores it in a database. The database can be MySQL or MongoDB.

[0780] The server analyzes the stored data to extract information such as the user's work history, skill set, values, hobbies, and interests. The analysis is performed using programming languages ​​such as Python and Node.js. Based on the analysis results, the server generates a prompt. The generated prompt is then input into a generative AI model (e.g., OpenAI's GPT-4).

[0781] The generative AI model generates a response based on the input prompt. The response may include career advice or suggestions for skill improvement for the user. The server receives the response from the generative AI model and returns it to the user's device. The user can view the response in their web browser.

[0782] For example, if a user enters "5 years of experience as a software engineer" as their work history and "Python, JavaScript, React" as their skill set, the server stores this information in the database and then inputs the following prompt to the generative AI model:

[0783] Example prompt sentence:

[0784] User's work experience: 5 years of experience as a software engineer

[0785] User skill set: Python, JavaScript, React

[0786] User values: Emphasize teamwork

[0787] User's hobbies: programming, reading

[0788] User Interest: Latest Trends in AI Technology

[0789] Based on this prompt, the generative AI model generates career advice and skill improvement suggestions tailored to the user, such as, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[0790] In this way, users can receive specific and useful advice based on their own information.

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

[0792] Step 1:

[0793] The user enters information

[0794] Users access the user interface provided through a web browser and enter information such as their work history, skill set, values, hobbies, and interests into an input form. Examples of input data include "5 years of experience as a software engineer," "Python, JavaScript, React," "emphasis on teamwork," "programming, reading," and "latest trends in AI technology."

[0795] Step 2:

[0796] The device sends the input data to the server

[0797] When the user clicks the submit button, the terminal sends the input data as an HTTP request to the server. This request contains data in JSON format. The input data is information entered by the user, such as work history, skill set, values, hobbies, and interests. The terminal sends this data to the server.

[0798] Step 3:

[0799] The server receives the data and stores it in the database

[0800] The server receives HTTP requests sent from the terminal. It analyzes the received data and stores it in a database. Databases such as MySQL and MongoDB are used. The input data includes information such as the user's work history, skill set, values, hobbies, and interests, and this is stored in the database. For example, the following data is stored in a MySQL database:

[0801] sql

[0802] INSERT INTO user_data (Work history, Skill set, Values, Hobbies, Interests) VALUES ('5 years of experience as a software engineer', '["Python", "JavaScript", "React"]', 'Values ​​teamwork', '["Programming", "Reading"]', 'The latest trends in AI technology');

[0803] Step 4:

[0804] The server analyzes the stored data

[0805] The server analyzes the user information stored in the database. Programming languages ​​such as Python and Node.js are used for the analysis. As a result of the analysis, the user's work history, skill set, values, hobbies, interests, etc. are extracted. The input data is the user information stored in the database, and the output data is the user's work history, skill set, values, hobbies, interests, etc. extracted by the analysis.

[0806] Step 5:

[0807] The server inputs a prompt to the generative AI model.

[0808] The server generates a prompt sentence based on the analysis results. The generated prompt sentence is input into the generative AI model. The input data is the user information extracted as the analysis result, and the output data is the generated prompt sentence. For example, the following prompt sentence is generated:

[0809] User's work experience: 5 years of experience as a software engineer

[0810] User skill set: Python, JavaScript, React

[0811] User values: Emphasize teamwork

[0812] User's hobbies: programming, reading

[0813] User Interest: Latest Trends in AI Technology

[0814] Step 6:

[0815] A generative AI model generates a response

[0816] The generative AI model generates a response based on the input prompt. The response can include career advice or suggestions for skill improvement for the user. The input data is the generated prompt, and the output data is the response generated by the generative AI model. For example, the generated advice might be, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[0817] Step 7:

[0818] The server returns the generated response to the user

[0819] The server receives the response from the generative AI model and returns it to the user's device. The user can view the response on a web browser. The input data is the response from the generative AI model, and the output data is the response displayed on the user's device.

[0820] (Application example 1)

[0821] 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."

[0822] Previous systems provided a way for users to input their past and current career history, skills, values, etc., but lacked the functionality to recommend the most suitable content to users. This made it difficult for users to find content that matched their interests and skills. Furthermore, there was no way to calculate the similarity of recommended content and present the most suitable content. This resulted in low user satisfaction and limited the usefulness of the system.

[0823] 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.

[0824] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user. This allows users to easily find content that matches their interests and skills, improving the utility value of the system.

[0825] "Means for inputting users' past and present career history, skills, values, etc." refers to means that provide an interface for users to input information such as their work history, skill set, values, hobbies, and interests.

[0826] "Means for inputting the user's image of the future" refers to a means for providing an interface for the user to input information such as their future goals and desired career path.

[0827] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the best future job type, company, and next step goal for the user.

[0828] "Means for simulating proposed possibilities and visualizing life" refers to a means for simulating and visually displaying a user's life plan based on future possibilities proposed by an AI agent.

[0829] "Means for recommending optimal content based on information entered by the user" refers to a means for analyzing information entered by the user, such as career history, skills, values, hobbies, and interests, and then recommending the most appropriate content for the user, such as movies, books, music, and news articles, based on that information.

[0830] The "means for calculating the similarity of the recommended content" refers to an algorithm or software for calculating the similarity between the recommended content and the user's input information.

[0831] The "means for presenting the most similar content to the user" refers to a means for selecting the most suitable content for the user based on the calculated similarity and presenting it to the user.

[0832] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user.

[0833] System configuration

[0834] The server provides an interface, which may include a smartphone application or a web interface, for users to enter information about their work history, skill set, values, hobbies, interests, etc. The information entered by the user is sent to the server and stored in a database.

[0835] The server then uses an AI agent to suggest future jobs, companies, and next steps based on the user's input. This AI agent uses a generative AI model to analyze the user's information and suggest optimal future possibilities.

[0836] Furthermore, the server provides a means for simulating and visually displaying the user's life plan based on the proposed future possibilities, so that the user can easily understand the future scenario concretely.

[0837] Content recommendation function

[0838] To recommend optimal content based on user input, the server analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends the most suitable content for the user, such as movies, books, music, and news articles. This recommendation method uses a generative AI model to compare the user's information with information in a content database and select the most suitable content.

[0839] To calculate the similarity of the recommended content, the server uses an algorithm such as cosine similarity, which calculates the similarity between the user's input information and the content description, and presents the most similar content to the user.

[0840] Hardware and software used

[0841] This system is realized using smartphones, servers, databases, generative AI models, and software such as TfidfVectorizer and cosine_similarity. The smartphone provides the user interface, while the server processes and stores data. The generative AI model is used to analyze user information and recommend optimal content.

[0842] Specific examples

[0843] For example, if a user enters the following information:

[0844] Work Experience: Data Scientist

[0845] Skillset: Python, Data Analysis, Machine Learning

[0846] Values: Data-driven decision making

[0847] Hobbies: Reading, watching movies

[0848] Interests: Big Data, AI

[0849] In this case, the server will recommend the book "The Future of AI."

[0850] Prompt Sentence Examples

[0851] Enter the user's work experience, skillset, values, hobbies, and interests. For example, enter "Work experience: Data Scientist, Skill set: Python, Data analysis, Machine learning, Values: Data-driven decision-making, Hobbies: Reading, Watching movies, Interests: Big data, AI."

[0852] In this way, a system can be realized that recommends optimal content to users.

[0853] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0854] Step 1:

[0855] Users use a smartphone or web interface to enter information such as their work history, skill set, values, hobbies, and interests. The entered information is sent to a server and stored in a database. The input data is in text format and includes the user's past and present work history, skills, values, etc.

[0856] Step 2:

[0857] The server uses a generative AI model to suggest future jobs, companies, and desired next steps based on the information entered by the user. The generative AI model analyzes the user's input data and suggests optimal future possibilities. This analysis uses natural language processing technology, which converts the user's input data into a feature vector. The output is the future jobs, companies, and desired next steps suggested to the user.

[0858] Step 3:

[0859] The server simulates and visually displays the user's life plan based on the proposed future possibilities. The simulation means, which allows the user to concretely understand future scenarios, includes visual elements such as graphs and charts. The input is the proposed data from the generative AI model, and the output is a visually displayed life plan.

[0860] Step 4:

[0861] The server uses a generative AI model to recommend optimal content based on user input. It analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends content such as movies, books, music, and news articles that are optimal for the user. The input is the user's input data, and the output is a list of recommended content.

[0862] Step 5:

[0863] The server uses an algorithm such as cosine similarity to calculate the similarity between the user's input information and the content description. The input is the user's feature vector and the content's feature vector, and the output is a similarity score.

[0864] Step 6:

[0865] The server selects the most suitable content for the user based on the calculated similarity and presents it to the user. The most similar content is presented to the user. The input is the similarity score, and the output is the optimal content to be presented to the user.

[0866] In this way, a system for recommending optimal content to a user is realized.

[0867] Example 2

[0868] 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."

[0869] In conventional systems, it was difficult for users to input a specific image of their future and receive appropriate suggestions based on that. Furthermore, there was a lack of means to utilize generative AI models based on the user's future goals and aspirations, resulting in a lack of accuracy and specificity in the suggestions made to users. This made it difficult for users to specifically understand and plan for their future possibilities.

[0870] 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.

[0871] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing life, means for sending prompt sentences to the generative AI model based on the image of the future input by the user, and means for the generative AI model to generate responses and present them to the user. This allows the user to specifically input their image of the future and receive highly accurate suggestions based on it using the generative AI model.

[0872] A "user" is an individual who uses the system to input information about their past and present, as well as an image of their future, and receives suggestions.

[0873] "Career" refers to the user's career history, including occupations and educational background.

[0874] "Skills" refer to the skills and abilities that users possess.

[0875] "Values" refer to the beliefs and ideas that users consider important.

[0876] "Image of the future" refers to the goals and hopes that users want to achieve in the future.

[0877] An "AI agent" is a program that suggests future possibilities that suit the user based on the information they input.

[0878] "Simulation" is the process of virtually trying out proposed future possibilities and visualizing the results.

[0879] "Generative AI model" refers to an artificial intelligence model for generating responses based on user input.

[0880] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[0881] "Response" refers to the output that a generative AI model generates based on a prompt.

[0882] This invention is a system that allows users to input specific images of their future and receive highly accurate proposals based on those images using a generative AI model. Specific embodiments of this system are described below.

[0883] Hardware and software used

[0884] Hardware: Servers, user devices (PCs, smartphones, etc.)

[0885] Software: web browsers, server-side applications (e.g., Node.js), databases (e.g., MySQL), generative AI models (e.g., GPT-4)

[0886] System configuration

[0887] 1. User input:

[0888] Users open a web browser on a device such as a PC or smartphone, access the system's URL, and enter their past and present career history, skills, values, and image of the future into a form displayed on the system's web page.

[0889] 2. Means of data transmission:

[0890] When the user clicks the submit button on the form, the device sends the entered data to the server as an HTTP POST request.

[0891] 3. Data storage means:

[0892] The server processes the received data and saves it to a database. For example, the server receives the data using Node.js and saves it by executing an "INSERT" query in a MySQL database.

[0893] 4. How to send prompts to the generative AI model:

[0894] The server sends prompts to the generative AI model based on the stored data. For example, the server might generate a prompt such as, "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and send it to GPT-4.

[0895] 5. How the generative AI model generates responses:

[0896] The generative AI model generates a response based on the prompt and returns it to the server. For example, GPT-4 might generate a response like, "To succeed as a data scientist, it's important to master the following skills..." and return it to the server.

[0897] 6. Response Presentation Method:

[0898] The server sends the generated response to the user's terminal, where the user can view the generated response on their web browser.

[0899] Specific examples

[0900] User input: "Future career goal: Data scientist, Desired lifestyle: Remote work, Future income goal: Annual income of 10 million yen"

[0901] Prompt for the generative AI model: "The user's career goal is to become a data scientist. Their desired lifestyle is remote work, and their future income goal is to earn 10 million yen a year. Based on this, please suggest steps the user can take to achieve this goal."

[0902] In this way, the system allows users to input specific images of their future, and the generative AI model generates responses based on those images. This system allows users to concretely understand and plan for their future possibilities.

[0903] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] A user accesses the system using a terminal.

[0906] A user opens a web browser using a device such as a PC or smartphone, and enters the system's URL to access it. For example, a user accesses "https: / / example.com" using Google Chrome (registered trademark). The input is the URL, and the output is the system's web page.

[0907] Step 2:

[0908] The user inputs an image of the future.

[0909] Users enter their past and present career history, skills, values, and future vision into a form displayed on the system's web page. For example, they enter "I want to become a data scientist" as their "career goal," "remote work" as their desired lifestyle, and "annual income of 10 million yen" as their future income goal. The input is the user's information, and the output is the data entered into the form.

[0910] Step 3:

[0911] The terminal sends the input data to the server.

[0912] When a user clicks the submit button on a form, the terminal sends the entered data to the server as an HTTP POST request. For example, when a user clicks the "Submit" button, the data is sent to "https: / / example.com / submit". The input is the form data, and the output is an HTTP request to the server.

[0913] Step 4:

[0914] The server receives the data and stores it in a database.

[0915] The server processes the received data and stores it in a database. For example, the server receives the data using Node.js and executes an "INSERT" query in a MySQL database to store the data. The input is the data from the HTTP request and the output is the record stored in the database.

[0916] Step 5:

[0917] The server sends a prompt to the generative AI model.

[0918] The server sends prompts to the generative AI model based on the stored data. For example, the server generates a prompt such as "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and sends it to the generative AI model. The input is the database record, and the output is the generated prompt.

[0919] Step 6:

[0920] The generative AI model generates a response and returns it to the server.

[0921] The generative AI model generates a response based on the prompt sentence and returns it to the server. For example, the generative AI model generates a response such as "To succeed as a data scientist, it is important to master the following skills..." and returns it to the server. The input is the prompt sentence, and the output is the generated response.

[0922] Step 7:

[0923] The server sends a response to the user terminal.

[0924] The server sends the generated response to the user terminal. For example, the server sends the generated response as an HTTP response to the user's web browser. The input is the generated response, and the output is the HTTP response to the user terminal.

[0925] Step 8:

[0926] The user confirms the response.

[0927] The user sees the generated response in their web browser. For example, the user reads the message "To be successful as a data scientist, it is important that you master the following skills..." The input is the HTTP response and the output is the user's understanding.

[0928] (Application example 2)

[0929] 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."

[0930] Conventional systems lack a means for users to specifically input their future goals and aspirations and then provide personalized content based on those goals. This makes it difficult to efficiently provide information and resources that match the user's vision of the future. Furthermore, there is a need for a system that can generate specific content based on the user's future goals, thereby increasing the user's motivation and helping them achieve their goals.

[0931] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing life, a means for generating relevant content based on the user's future goals and hopes, and a means for providing the generated content to the user. This makes it possible to provide personalized content that matches the user's vision of the future.

[0932] "User" refers to any individual or entity that uses the System.

[0933] "Past and current experience" refers to information such as the user's work history, educational background, and skills.

[0934] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by the user.

[0935] "Values" refers to the beliefs, ethics, and lifestyles that users consider important.

[0936] "Image of the future" refers to the goals that users want to achieve in the future, their desired lifestyle, income goals, etc.

[0937] An "AI agent" refers to an artificial intelligence system that analyzes information input by the user and suggests future possibilities.

[0938] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[0939] "Life visualization tools" refers to tools and technologies that allow users to visually display future scenarios.

[0940] "Content" refers to information, videos, articles, podcasts, and other media provided to users.

[0941] "Generation means" refers to the technology or algorithms used to create relevant content based on user input.

[0942] "Means of delivery" refers to the technology and methods used to deliver the generated content to users.

[0943] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for generating relevant content based on the user's future goals and hopes, and means for providing the generated content to the user.

[0944] System configuration

[0945] 1. User input method:

[0946] Users use devices such as smartphones or computers to input their past and present career history, skills, values, and vision for the future, and this information is sent to a server.

[0947] 2. AI Agents:

[0948] The server receives the information sent by the user and analyzes it using an AI agent, which uses a generative AI model to suggest future possibilities for the user.

[0949] 3. Simulation methods:

[0950] The server runs a simulation based on the proposed future possibilities and visualizes the user's life, and the results of this simulation are displayed on the user's device.

[0951] 4. Content Generation Methods:

[0952] The server generates relevant content based on the user's future goals and aspirations, using generative AI models in the process to provide the most relevant information to the user.

[0953] 5. Content Delivery Method:

[0954] The server delivers the generated content to the user's device, where the user can view the content via their smartphone or PC.

[0955] Hardware and software used

[0956] Hardware: smartphones, PCs, servers

[0957] Software: Python, OpenAI API

[0958] Data processing and calculation

[0959] The server receives the data sent by the user and performs the following processing.

[0960] 1. Data analysis: Analyze the user's background, skills, values, and future vision.

[0961] 2. Prompt generation: Generate prompts based on the user's goals.

[0962] 3. Content generation: Use generative AI models to generate personalized content based on prompts.

[0963] Specific examples

[0964] For example, if a user enters the goals "become a data scientist," "achieve remote work," and "earn 10 million yen a year," the following prompt sentences will be generated:

[0965] Example prompt sentence:

[0966] The user's career goal is to become a data scientist, their desired lifestyle is to work remotely, and their future income goal is to earn 10 million yen a year. Please suggest content related to this.

[0967] By inputting this prompt into a generative AI model, the system can provide users with the most appropriate content, such as learning resources for becoming a data scientist, tips for remote work, or a career path to earning 10 million yen a year.

[0968] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0969] Step 1:

[0970] Users use devices such as smartphones or PCs to input their past and present career history, skills, values, and vision for the future. The input information is sent from the device to a server. Specifically, the user enters information into an input form and presses the send button, which sends the data to the server.

[0971] Step 2:

[0972] The server receives the data sent by the user and stores it in a database. The stored data includes the user's career history, skills, values, and future image. Specifically, the server analyzes the received data, converts it into an appropriate format, and stores it in the database.

[0973] Step 3:

[0974] The server generates prompts based on the stored data to suggest future possibilities for the user. The generated prompts are created based on the user's goals and wishes. Specifically, the server analyzes the user's input data and constructs prompts suitable for the generative AI model.

[0975] Step 4:

[0976] The server uses the generated prompt sentence to send a request to the generative AI model, which then generates personalized content based on the prompt sentence. Specifically, the server uses the OpenAI API to send the prompt sentence and receive the generated content.

[0977] Step 5:

[0978] The server analyzes the generated content and converts it into a format for providing to the user. Specifically, the server converts the generated content into an appropriate format and arranges it in a form that is easy for the user to view.

[0979] Step 6:

[0980] The server delivers the prepared content to the user's device, who can then view it via a smartphone or PC. Specifically, the server sends the content to the user's device, allowing the user to view the content through an application.

[0981] Step 7:

[0982] The user browses the provided content and obtains information and resources for achieving future goals. Specifically, the user browses the content through the application and obtains the necessary information.

[0983] Example 3

[0984] 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."

[0985] Conventional career path and life plan suggestion systems have difficulty fully analyzing the information entered by users and making optimal suggestions for each individual user. Furthermore, they lacked a way to visually understand the future impact of the suggested career path or life plan, making it difficult for users to visualize the specifics of the suggestions. This led to problems such as insufficient decision-making when planning their own future.

[0986] 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.

[0987] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing a life, natural language processing means for analyzing the user's input information, machine learning means for proposing optimal career paths and life plans based on the analysis results, means for simulating and visualizing future life based on the proposed career paths and life plans, and visualization means for displaying the simulation results in graphs and charts.This allows the user to be proposed optimal career paths and life plans based on their own skill sets and values, and to visually understand the impact of these on their future.

[0988] "User" refers to an individual who uses the system to plan their own career path or life plan.

[0989] "Career" refers to the user's past job history, educational background, etc.

[0990] "Skills" refers to the specialized knowledge and techniques possessed by the user.

[0991] "Values" refer to the beliefs and ideas that users consider important.

[0992] "Image of the future" refers to the hopes and goals that users have for the future.

[0993] An "AI agent" is software that analyzes information entered by the user and suggests optimal career paths and life plans.

[0994] "Simulation" refers to the process of predicting a user's future life based on suggested career paths and life plans.

[0995] "Visualization" refers to displaying simulation results in a visual format such as a graph or chart.

[0996] "Natural language processing means" refers to technology for analyzing text data entered by a user.

[0997] "Machine learning methods" refer to algorithms that suggest optimal career paths and life plans based on past data.

[0998] "Graphs and charts" refer to diagrams that visually display the results of a simulation.

[0999] This invention is a system that inputs a user's past and present career history, skills, values, etc., and based on that, proposes future career paths and life plans, and then simulates and visualizes the proposals. Specific embodiments of this system are described below.

[1000] System configuration

[1001] Hardware and software configuration:

[1002] Server: Receives data, analyzes, simulates, and visualizes it. The server must have a powerful processor and ample memory.

[1003] Device: The device where a user enters information and sees results, such as a computer, tablet, or smartphone.

[1004] Natural language processing libraries: Use Python NLP libraries such as spaCy and NLTK.

[1005] Machine learning libraries: Use scikit-learn or TensorFlow.

[1006] Visualization tools: Use Matplotlib or Plotly.

[1007] Program processing

[1008] Data collection and analysis:

[1009] The user uses the device to input information such as their skill set, values, and interests. For example, the user inputs a skill set such as "programming (Python, Java) and data analysis" or values ​​such as "work-life balance and social contribution." The device then sends the input information to the server. The server then analyzes the received data using a natural language processing library (e.g., spaCy or NLTK).

[1010] Career path and life plan suggestions:

[1011] The server then uses the analysis results to suggest the best career path or life plan for the user. For example, it might suggest jobs such as data scientist or software engineer at an edtech company based on the user's skill set and values. It then uses machine learning libraries (such as scikit-learn and TensorFlow) to compare the results with past data to determine the best option.

[1012] Simulation and visualization:

[1013] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib or Plotly). The server sends the generated graphs and charts to the device, which then displays them to the user.

[1014] Specific examples

[1015] The user enters the following information:

[1016] Skill set: Programming (Python, Java), Data analysis

[1017] Values: Work-life balance, social contribution

[1018] Interests: Environmental protection, education

[1019] The AI ​​agent analyzes this information and makes suggestions such as:

[1020] Suitable jobs: Data scientist, software engineer at an edtech company

[1021] Suitable companies: Environmental startups, educational nonprofits

[1022] It also simulates your future income and lifestyle based on your proposed career path, displaying graphs like the one below:

[1023] Income trend graph

[1024] A chart showing lifestyle changes

[1025] Example prompt sentence:

[1026] "Please suggest suitable jobs and companies based on the user's skill set and values. The user's skill set is programming (Python, Java) and data analysis. Their values ​​are work-life balance and social contribution. Their interests are environmental protection and education."

[1027] In this way, the user is presented with an optimal career path and life plan based on their own skill set and values, and is able to visually understand the impact of these on the future. The flow of the identification process in Example 3 will be described with reference to FIG.

[1028] Step 1:

[1029] The user uses the device to input information such as their skill set, values, and interests. For example, the user might input a skill set such as "programming (Python, Java) and data analysis" or values ​​such as "work-life balance and social contribution." The input information is saved in the input form on the device.

[1030] Input: Information about the user's skill set, values, interests, etc.

[1031] Output: User information stored on the device

[1032] Step 2:

[1033] The device converts the entered user information into JSON format and sends it to the server using an HTTP POST request, which then stores the received data in a database.

[1034] Input: User information stored on the device

[1035] Output: User information sent to the server

[1036] Step 3:

[1037] The server passes the stored data to an AI agent, which uses a natural language processing library (e.g., spaCy or NLTK) to tokenize the text data and analyze the user's skill set and values. For example, it analyzes the skill set "Programming (Python, Java)" and identifies related job titles.

[1038] Input: User information stored on the server

[1039] Output: Analyzed user's skill set and values

[1040] Step 4:

[1041] The AI ​​agent applies machine learning models using scikit-learn and TensorFlow to suggest optimal career paths and life plans for users, such as jobs like "data scientist" or "software engineer at an edtech company."

[1042] Input: Parsed user's skill set and values

[1043] Output: Suggested career path or life plan

[1044] Step 5:

[1045] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib and Plotly).

[1046] Input: Proposed career path or life plan

[1047] Output: Graphs and charts of simulation results

[1048] Step 6:

[1049] The server sends the generated graphs and charts to the terminal, which then displays the received graphs and charts to the user. For example, it displays a graph showing changes in income or lifestyle.

[1050] Input: Graphs and charts of simulation results

[1051] Output: Graphs and charts displayed on the terminal

[1052] (Application example 3)

[1053] 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."

[1054] Conventional career planning systems can suggest future possibilities based on a user's past and present career history, skills, and values, but they lack the means to specifically simulate and visualize future income based on the proposed career path. This makes it difficult for users to understand the specific economic impact of the proposed career path, making it difficult for them to make decisions.

[1055] 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 inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the proposed career path and visualizing it in a graph. This makes it easier for the user to understand the specific economic impact of the proposed career path, enabling more appropriate decision-making.

[1056] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, and values ​​into the system.

[1057] The "means for inputting the user's image of the future" is an interface that allows the user to input information such as their future goals and desired lifestyle into the system.

[1058] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the optimal career path and life plan.

[1059] "Means to simulate proposed possibilities and visualize life" is a function that simulates the user's future life based on proposed career paths and life plans and displays them in graphs and charts.

[1060] "Means for simulating future income based on a proposed career path and visualizing it in a graph" is a function for predicting future income based on a proposed career path and displaying the results in a graph.

[1061] A system for carrying out this invention includes means for inputting a user's past and present career history, skills, values, etc.; means for inputting an image of the user's future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the suggested career path and visualizing it in a graph.

[1062] 1. Program Generation

[1063] The program for this system can be implemented using Python. Specifically, we will build an AI agent to analyze user input data and propose optimal career paths. Furthermore, we will add a function to simulate future income based on the proposed career paths and visualize the results in a graph.

[1064] 2. Explanation of program processing

[1065] The server receives and analyzes information entered by the user, such as their career history, skills, and values. This analysis is performed using natural language processing and machine learning algorithms. Specific software used is the Python libraries Numpy and Pandas, and the machine learning library Scikit-learn.

[1066] Based on the analysis results, the AI ​​agent will suggest the most suitable career path for the user. This suggestion is based on the user's skill set and values. For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the AI ​​agent will suggest "software engineer."

[1067] Next, future earnings are simulated based on the proposed career path. The simulation uses data such as earnings growth rates and industry average salaries. These data can be obtained from external databases or APIs. The simulation results are visualized in graphs using Matplotlib.

[1068] 3. Adding concrete examples

[1069] For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the AI ​​agent will suggest "software engineer" and simulate their future income and display it in a graph.

[1070] Prompt Sentence Examples

[1071] Create a Python program that suggests the optimal career path based on the user's skills and values, simulates future income based on that career path, and visualizes it in a graph. The user's skills are "programming" and "data analysis," and their values ​​are "innovation" and "stability."

[1072] In this way, users can better understand the specific financial implications of proposed career paths and make better decisions.

[1073] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1074] Step 1:

[1075] Users use a terminal to input information such as their past and present career history, skills, and values. The input information is then sent to the server. The input data includes work history, educational background, specialized knowledge, skills, and values.

[1076] Step 2:

[1077] The server receives input data sent by the user and stores it in a database. The stored data is used for subsequent analysis. Specifically, the data is formatted using the Python Pandas library and converted into an analyzable format.

[1078] Step 3:

[1079] The server analyzes the stored data using natural language processing and machine learning algorithms. Specifically, it uses the Scikit-learn library to cluster the user's skill set and values ​​and generate a model to suggest the optimal career path. Based on the input data, it identifies the most suitable job type and career path for the user.

[1080] Step 4:

[1081] The server then suggests the most suitable career path for the user based on the analysis results. The suggested career path is sent to the terminal and displayed to the user. For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the server will suggest "software engineer."

[1082] Step 5:

[1083] The server simulates future income based on the proposed career path. The simulation uses data such as income growth rate and industry average salary. This data is obtained from external databases and APIs. Specifically, the server uses the Numpy library to calculate income growth and predict future income.

[1084] Step 6:

[1085] The server visualizes the simulation results in graphs using the Matplotlib library. The graphs are then sent to the terminal and displayed to the user. For example, a graph could show how the user's future income will change based on the proposed career path.

[1086] Step 7:

[1087] Users can use their devices to check the proposed career paths and simulation results and consider their future life plans. This makes it easier for users to understand the specific economic impact of the proposed career paths, enabling them to make more appropriate decisions.

[1088] 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.

[1089] "Example 1"

[1090] In one embodiment of the present invention, the AI ​​agent includes an emotion engine that recognizes a user's emotions. The emotion engine reads emotions from the user's tone of voice, facial expressions, and choice of words. For example, if the user says, "Thinking about my future makes me anxious," the emotion engine recognizes that the user is feeling anxious.

[1091] "Example 2"

[1092] The emotion engine suggests future possibilities that suit the user based on the emotions it recognizes. For example, if the user is feeling anxious, the emotion engine will suggest possibilities that include a stable job and a steady income. If the user is excited, the emotion engine will suggest possibilities that include new challenges and adventures.

[1093] "Example 3"

[1094] The emotion engine simulates suggested possibilities based on the emotions it recognizes. For example, if the user feels anxious, the emotion engine will simulate a life plan that involves a stable job. If the user feels excited, the emotion engine will simulate a life plan that includes new challenges.

[1095] The processing flow of each embodiment will be described below.

[1096] "Example 1"

[1097] Step 1: The AI ​​agent interacts with the user and reads their emotions from their tone of voice, facial expressions, and choice of words.

[1098] Step 2: The emotion engine analyzes the emotions it reads and determines the user's current emotional state.

[1099] "Example 2"

[1100] Step 1: The emotion engine considers future possibilities that suit the user based on the user's emotional state.

[1101] Step 2: The emotion engine presents the possibilities it has considered to the user.

[1102] "Example 3"

[1103] Step 1: The emotion engine simulates a life plan based on the user's emotional state and the possibilities they present.

[1104] Step 2: The emotion engine presents the simulated life plan to the user.

[1105] Example 1

[1106] 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."

[1107] Previous systems provided a means for users to input information such as their past and present career history, skills, and values, but lacked the ability to recognize users' emotions and generate feedback based on them. As a result, suggestions and feedback were uniform, making it difficult to provide appropriate advice tailored to each individual user's emotions and situation. Furthermore, systems lacked the means to specifically simulate users' future images and visualize their lives. This made it difficult for users to concretely understand their future possibilities and choose appropriate actions.

[1108] 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.

[1109] In this invention, the server includes: means for inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that proposes future possibilities that suit the user based on the input information; means for simulating the proposed possibilities and visualizing life; an emotion engine that recognizes emotions from the user's tone of voice, facial expressions, choice of words, etc.; a generative AI model that generates feedback based on the emotions recognized by the emotion engine; and means for providing the generated feedback to the user. This provides individualized feedback that takes the user's emotions into consideration, enabling the user to specifically understand their future possibilities and select appropriate actions.

[1110] "Means for inputting a user's past and present career history, skills, values, etc." refers to a device or software that provides an interface for a user to input information such as their work history, skill set, values, hobbies, and interests.

[1111] "Means for inputting the user's image of the future" refers to a device or software that provides an interface for the user to input information such as their future goals and desired career path.

[1112] An "AI agent" is a program or system that uses artificial intelligence to suggest future possibilities that suit the user based on information entered by the user.

[1113] A "life visualization tool" is a device or software that simulates proposed future possibilities and visually displays them to the user.

[1114] An "emotion engine" is a program or system that recognizes emotions from a user's tone of voice, facial expressions, choice of words, etc.

[1115] A "generative AI model" is a program or system that uses artificial intelligence to generate feedback based on emotions recognized by an emotion engine.

[1116] A "means for providing feedback" is a device or software for displaying or notifying the generated feedback to the user.

[1117] This invention is a system that allows users to input their past and present career history, skills, values, etc., suggests future possibilities, recognizes emotions, and provides feedback. Specific embodiments of this system are described below.

[1118] Entering user information

[1119] Users use a web browser or mobile application to enter information such as their work history, skill set, values, hobbies, and interests. This is done through a user interface using HTML and JavaScript. For example, a user might enter information such as "5 years of experience as a software engineer," "skills in Python, Java, and machine learning," "emphasis on teamwork," "reading, hiking," and "interest in data science."

[1120] Sending information

[1121] The terminal transmits the information entered by the user in real time to the server, which uses the HTTPS protocol for secure data transfer and stores the received information in a database.

[1122] emotion recognition

[1123] The server analyzes the received information and the user's comments using an emotion engine. The emotion engine uses voice recognition software (e.g., a voice recognition API) or image analysis software (e.g., a face recognition API) to analyze the user's tone of voice and facial expressions to recognize emotions. For example, if a user says, "I've been interested in data science lately, but I don't know where to start," the emotion engine recognizes that the user is excited.

[1124] Data analysis

[1125] The server analyzes the user's input information and emotion recognition results using a generative AI model (e.g., a natural language processing model). The generative AI model processes the data to generate appropriate feedback and advice based on the user's interests and emotions.

[1126] Generate feedback

[1127] The server uses generative AI models to generate feedback and advice for users. For example, if a user inputs that they are interested in data science and the emotion engine recognizes their excitement, the server will generate feedback such as, "Based on your interests, we recommend the following online courses."

[1128] Send Feedback

[1129] The server then sends the generated feedback to the device, again securely using the HTTPS protocol.

[1130] View Feedback

[1131] The terminal displays the feedback received from the server on the user interface, allowing the user to check the displayed feedback and decide on the next action to take.

[1132] Examples of concrete examples and prompts

[1133] As an example, a user logs into a system and enters the following information:

[1134] Work experience: 5 years of experience as a software engineer

[1135] Skillset: Python, Java, Machine Learning

[1136] Values: Teamwork

[1137] Hobbies: Reading, hiking

[1138] Interests: Data Science

[1139] A user might say, "I've recently become interested in data science, but I don't know where to start." The emotion engine recognizes the user's excitement, and the server generates feedback such as, "Based on your interests, we recommend the following online courses," and sends it to the device. The device then displays this feedback in the user interface, where the user can confirm it.

[1140] Example prompt sentence:

[1141] "Design a system where users can input their background, skills, values, hobbies, and interests, and the emotion engine can recognize their emotions. For example, if a user says, 'I've been interested in data science lately, but I don't know where to start,' the emotion engine should recognize that the user is excited and provide feedback recommending appropriate online courses."

[1142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1143] Step 1:

[1144] Users use a web browser or mobile application to input information such as their work history, skill set, values, hobbies, and interests. The input information is sent to the server in real time by the device. Examples of input data include "5 years of experience as a software engineer," "skills in Python, Java, and machine learning," "emphasis on teamwork," "reading, hiking," and "interest in data science." The server then stores this information in a database.

[1145] Step 2:

[1146] The server receives the information entered by the user and stores it in a database. The stored information is used for subsequent processing. Specifically, the server receives the data securely using the HTTPS protocol and stores it in a database. The input data includes the user's background, skills, values, hobbies, interests, etc., and this data is later analyzed.

[1147] Step 3:

[1148] When a user expresses emotions through voice input or facial expressions, the device captures them and sends them to the server. The server uses an emotion engine to analyze the user's tone of voice and facial expressions to recognize emotions. For example, if a user says, "I've been interested in data science lately, but I don't know where to start," the emotion engine will recognize that the user is excited. The input data is voice and images, and the output is recognized emotional data.

[1149] Step 4:

[1150] The server uses a generative AI model to analyze the user's input information and emotion recognition results. The generative AI model processes the data to generate appropriate feedback and advice based on the user's interests and emotions. For example, if a user inputs that they are interested in data science and the emotion engine recognizes excitement, the generative AI model will generate feedback such as, "Based on your interests, we recommend the following online courses." The input data is the user's background, skills, values, hobbies, interests, and emotion data, and the output is the generated feedback.

[1151] Step 5:

[1152] The server sends the generated feedback to the device, also securely using the HTTPS protocol. The input data is the generated feedback, and the output is the data sent to the device.

[1153] Step 6:

[1154] The terminal displays the feedback received from the server on a user interface. The user can check the displayed feedback and decide on the next action. Specifically, the terminal visually displays the feedback so that the user can check it. The input data is the feedback from the server, and the output is the feedback displayed on the user interface.

[1155] (Application example 1)

[1156] 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."

[1157] Conventional systems can suggest future possibilities based on a user's background, skills, and values, but they cannot provide suggestions or warnings that take into account the user's emotional state. As a result, they cannot respond appropriately when the user is feeling anxious or stressed, and their psychological support is insufficient. Furthermore, since there is no function to detect abnormal emotional states and issue warnings, it is difficult to ensure the user's safety and sense of security.

[1158] 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.

[1159] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, an emotion engine that recognizes the user's emotions, means for the emotion engine to read emotions from the user's tone of voice, facial expressions, choice of words, etc., and means for issuing a warning when an abnormal emotional state is detected. This makes it possible to monitor the user's emotional state in real time and issue an appropriate warning when an abnormal emotional state is detected.

[1160] "Means for inputting users' past and present career history, skills, values, etc." refers to means that provide an interface for users to input information such as their work history, skill set, values, hobbies, and interests.

[1161] "Means for inputting the user's image of the future" refers to a means for providing an interface for the user to input information such as their future goals and desired career path.

[1162] An "AI agent" is an artificial intelligence system that suggests future possibilities that suit the user based on the information the user inputs.

[1163] "Means for simulating proposed possibilities and visualizing life" refers to a means for simulating and visually displaying a user's life plan based on future possibilities proposed by an AI agent.

[1164] The "emotion engine" is an analytical engine that reads emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1165] "The means by which the emotion engine reads emotions from the user's tone of voice, facial expressions, choice of words, etc." refers to the means by which the emotion engine analyzes the user's audio and video data and recognizes the user's emotional state.

[1166] The "means for issuing a warning when an abnormal emotional state is detected" is a means for the emotion engine to monitor the emotional state of the user and issue a warning to the user when an abnormal emotional state is detected.

[1167] A system for carrying out this invention includes: means for inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing life; an emotion engine that recognizes the user's emotions; means for the emotion engine to read the user's emotions from the user's tone of voice, facial expressions, choice of words, etc.; and means for issuing a warning when an abnormal emotional state is detected.

[1168] System configuration

[1169] This system uses the following hardware and software:

[1170] Hardware: Smartphone camera and microphone

[1171] Software: OpenCV, Keras, SpeechRecognition, Transformers

[1172] Program processing

[1173] The server receives information such as career history, skills, and values ​​entered by the user via smartphone and stores it in a database. It then provides an interface for the user to enter their future goals and desired career path. Based on this information, the AI ​​agent suggests future possibilities that suit the user.

[1174] The proposed future possibilities are visually displayed through a simulation tool, visualized as the user's life plan. Furthermore, an emotion engine analyzes the user's tone of voice and facial expressions to monitor their emotional state in real time. The emotion engine uses OpenCV to detect the user's face from camera footage and recognizes emotions using a Keras model. It also converts audio from the microphone into text using the SpeechRecognition library, and analyzes the sentiment of the text using the Transformers library's emotion analysis pipeline.

[1175] If an abnormal emotional state is detected, the system will alert the user. For example, if a user says, "Thinking about my future makes me anxious," the emotion engine will recognize that the user is feeling anxious and issue an appropriate warning.

[1176] Specific examples

[1177] As a concrete example, if a user says, "I feel anxious when I think about my future," the system will act as follows:

[1178] 1. The user's face is detected from the camera footage and the emotion is recognized as "Fear."

[1179] 2. The audio from the microphone is converted into text, and the resulting text is, "Thinking about my future makes me anxious."

[1180] 3. This text is input into the sentiment analysis pipeline and is recognized as "NEGATIVE."

[1181] 4. The emotion is "Fear" or "Negative" and therefore raises a warning.

[1182] Example prompts to input to a generative AI model:

[1183] How would an emotion-aware security application behave if a user said, "Thinking about my future makes me anxious"?

[1184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1185] Step 1:

[1186] Users use their smartphones to enter information about their past and present career history, skills, values, etc.

[1187] Input: Information about the user, such as their work history, skill set, values, hobbies, and interests.

[1188] Output: The input information is saved in the database.

[1189] How it works: The user enters information through the smartphone interface, the server receives the information, and stores it in a database.

[1190] Step 2:

[1191] The user enters their future goals and desired career path.

[1192] Input: The user's future goals and desired career path.

[1193] Output: The input information is saved in the database.

[1194] Specific operation: The user enters their future goals and desired career path through the smartphone interface, and the server receives the information and stores it in a database.

[1195] Step 3:

[1196] Based on the information entered, the server suggests future possibilities that suit the user.

[1197] Input: User's background, skills, values, and future goals stored in a database.

[1198] Output: A proposal of future possibilities that suit the user.

[1199] How it works: The server uses an AI agent to analyze the information stored in the database and suggest future jobs, companies, and next steps that suit the user.

[1200] Step 4:

[1201] It simulates proposed future possibilities and visualizes the user's life plan.

[1202] Input: Proposed future possibilities.

[1203] Output: A visual representation of the user's life plan.

[1204] Specific operation: The server uses a simulation tool to create a life plan for the user based on the proposed future possibilities and visually displays it on the smartphone screen.

[1205] Step 5:

[1206] The emotion engine analyzes the user's tone of voice and facial expressions to monitor their emotional state in real time.

[1207] Input: User's audio and video data.

[1208] Output: The user's emotional state.

[1209] How it works: The smartphone's camera and microphone are used to capture the user's voice and video, and the server uses OpenCV and Keras models to recognize emotions.

[1210] Step 6:

[1211] The emotion engine issues a warning if it detects an abnormal emotional state.

[1212] Input: The user's emotional state.

[1213] Output: A warning message.

[1214] Specific operation: The server uses the emotion engine to monitor the user's emotional state, and if an abnormal emotional state (e.g., fear, sad, negative) is detected, a warning message is displayed on the smartphone.

[1215] Example 2

[1216] 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."

[1217] Conventional systems can suggest future possibilities based on a user's past and present career history, skills, and values, but they cannot take the user's emotions into consideration when making suggestions, which makes it difficult to find the best future possibilities for the user. In addition, if the proposed future possibilities do not match the user's emotions, the user is less likely to accept the suggestions.

[1218] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting the user's past and present career, skills, values, etc., a means for inputting the user's image of the future, a means for recognizing the user's emotions based on the input information, a means using a generative AI model for proposing future possibilities suitable for the user based on the recognized emotions, and a means for simulating the proposed possibilities and visualizing the user's life. This makes it possible to propose optimal future possibilities taking the user's emotions into consideration.

[1219] A "user" is an individual who uses the system to input their future goals and aspirations and receive suggestions.

[1220] "Career" refers to historical information such as the user's past work experience and educational background.

[1221] "Skills" refers to the specialized knowledge and techniques that a user possesses.

[1222] "Values" are the beliefs and ideas that users consider important.

[1223] "Image of the future" refers to the goals and hopes that users have for the future.

[1224] "Means for recognizing emotions" refers to technology that analyzes information input by a user and identifies the user's emotions from that information.

[1225] A "generative AI model" is an artificial intelligence technology that suggests future possibilities that suit a user based on the user's input information and recognized emotions.

[1226] A "simulation tool" is a technology that visually displays a user's life based on proposed possible futures.

[1227] "Life plans" refer to specific plans and scenarios regarding the user's future life.

[1228] This invention is a system that allows a user to input their own future goals and hopes, recognizes their emotions based on the input, and suggests optimal future possibilities. Specific embodiments of this system will be described below.

[1229] System configuration

[1230] The system consists of a terminal that collects user input information, a server that analyzes the input information and recognizes emotions, a server that generates suggestions using a generative AI model, and a terminal that displays the suggestions to the user.

[1231] Hardware and software used

[1232] The terminals are general computing devices such as PCs and smartphones, which access web applications via a web browser and collect user input information.

[1233] The server is a powerful computer that receives and analyzes user input. The server has the following software installed:

[1234] Python: a programming language

[1235] TextBlob and VADER: Sentiment analysis libraries

[1236] Generative AI models (e.g., GPT-4)

[1237] Data processing and calculation

[1238] The user accesses the web application using a terminal and enters the following information:

[1239] Career goals (e.g., "I want to work as a data scientist in the future.")

[1240] Desired lifestyle (e.g., "I want to work in an environment where I can work remotely")

[1241] Future income goals (e.g., "I want to earn 10 million yen a year")

[1242] The terminal sends the information entered by the user in JSON format to the server using the HTTPS protocol to ensure data security.

[1243] The server parses the received JSON data and uses the emotion engine to recognize the user's emotion. For example, it analyzes emotions as follows:

[1244] Calculate positive / negative score of text using TextBlob

[1245] Deep dive into text sentiment scores using VADER

[1246] As a result of the analysis, it is recognized that the user is feeling "anxiety."

[1247] The server sends the following prompt to the generative AI model:

[1248] "The user's future goal is to become a data scientist and hopes to work in an environment that allows remote work. He also aims to earn 10 million yen a year. The user is currently feeling anxious. Please provide this user with specific advice on how to secure a stable job and income."

[1249] Based on this prompt, the generative AI model (GPT-4) generates the following suggestions:

[1250] "If you're aiming for a career as a data scientist, I recommend first learning the basics of data analysis and gaining experience at a stable company. More and more companies are offering remote work, so it's a good idea to look for remote work positions. To aim for an annual salary of 10 million yen, it's important to deepen your expertise and aim for a project manager or leadership role."

[1251] The server sends the suggestions received from the generative AI model to the user's device, which then displays them to the user, who can review the suggestions and use them to plan for the future.

[1252] In this way, it is possible to propose optimal future possibilities that take the user's emotions into consideration.

[1253] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1254] Step 1:

[1255] Users access the web application using their device and enter information such as their career goals, desired lifestyle, and future income goals. The entered information is saved in an input form on the device.

[1256] Step 2:

[1257] The terminal converts the information entered by the user into JSON format and sends it to the server using the HTTPS protocol. The input data includes information such as career goals, desired lifestyle, and future income goals.

[1258] Step 3:

[1259] The server parses the received JSON data and uses an emotion engine to recognize the user's emotions. Specifically, it uses an emotion analysis library such as TextBlob or VADER to calculate the positive / negative score and emotion score of the text. The input data is the user's input information, and the output data is the recognized emotion (e.g., "anxiety").

[1260] Step 4:

[1261] The server generates a prompt sentence based on the recognized emotion. The prompt sentence includes the user's goals, desires, and recognized emotion. The generated prompt sentence is sent to the generative AI model. The input data are the user's goals, desires, and recognized emotion, and the output data is the generated prompt sentence.

[1262] Step 5:

[1263] The server sends a prompt to a generative AI model (e.g., GPT-4) to generate a specific suggestion for the user. The generative AI model generates a suggestion based on the prompt and returns it to the server. The input data is the prompt, and the output data is the generated suggestion.

[1264] Step 6:

[1265] The server sends the proposals received from the generative AI model to the user's device. The input data is the generated proposal, and the output data is the proposal displayed on the user's device.

[1266] Step 7:

[1267] The terminal displays the proposals received from the server to the user, who can then check the displayed proposals and use them for future planning. The input data is the proposal sent from the server, and the output data is the proposal displayed to the user.

[1268] (Application example 2)

[1269] 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."

[1270] Conventional future prediction systems have the problem of not being able to provide optimal suggestions for users because they suggest future possibilities without taking the user's emotional state into consideration. Furthermore, because the future possibilities generated based on the user's input information are not specific, it is difficult for users to understand the specific steps they need to take to realize the suggestions.

[1271] 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.

[1272] In this invention, the server includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an emotion engine that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing the user's life, and a means for recognizing the user's emotional state and suggesting appropriate future possibilities using a generative AI model. This makes it possible to suggest optimal future possibilities based on the user's emotional state, enabling the creation of a specific life plan.

[1273] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, beliefs, and values ​​into the system.

[1274] The "means for inputting the user's image of the future" is an interface that allows the user to input their future goals and hopes, ideal lifestyle, income goals, etc. into the system.

[1275] An "emotion engine" is an algorithm or software that recognizes a user's emotional state from input information or text and suggests appropriate future possibilities based on that emotion.

[1276] A "generative AI model" is an artificial intelligence model that generates future possibilities based on the user's input information and emotional state.

[1277] "Means for simulating proposed possibilities and visualizing life" refers to software or an interface that simulates generated future possibilities as specific scenarios and presents them visually to the user.

[1278] A system for implementing this invention includes means for inputting a user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an emotion engine, a generative AI model, and means for simulating proposed possibilities and visualizing life.

[1279] System configuration

[1280] The system uses the following hardware and software:

[1281] Hardware: Smartphones, servers

[1282] Software: Python, OpenAI API, Emotion Recognition Library

[1283] Program processing

[1284] The server receives past and present career history, skills, values, and future image input by the user via a smartphone. This input information is acquired through the user interface.

[1285] The emotion engine then analyzes the user's input and recognizes their emotional state. The emotion engine uses the Emotion Recognition library to extract emotions from the text.

[1286] The generative AI model then generates future possibilities based on the emotional state recognized by the emotion engine and the user's input information. The generative AI model uses the OpenAI API and inputs prompt statements to generate appropriate future scenarios.

[1287] The generated future possibilities are visualized as specific scenarios using simulation tools, allowing users to concretely understand the proposed future possibilities.

[1288] Specific examples

[1289] For example, if the user types:

[1290] Career goal: "To become a data scientist"

[1291] Desired lifestyle: "Remote work"

[1292] Future income goal: "10 million yen annual income"

[1293] In this case, the emotion engine recognizes the user's emotional state from the input information and inputs the following prompt sentence into the generative AI model:

[1294] User Sentiment: Excitement

[1295] Career goal: To become a data scientist

[1296] Desired lifestyle: Remote work

[1297] Future income goal: 10 million yen per year

[1298] Suggest appropriate future possibilities.

[1299] Based on this prompt, the generative AI model proposes possible future scenarios that fit the user, and the proposed scenarios are visualized and presented to the user through a simulation tool.

[1300] In this way, users can concretely understand optimal future possibilities based on their emotional state and identify concrete steps to realize them.

[1301] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1302] Step 1:

[1303] Users use their smartphones to input their past and present career history, skills, values, and vision for the future. Specifically, users input their career goals, desired lifestyle, future income goals, etc. This input information is sent to the server via the smartphone's user interface. The input data is stored on the server in text format.

[1304] Step 2:

[1305] The server analyzes the received user input. Specifically, it processes the user's input as text data and passes it to the emotion engine. The emotion engine uses the Emotion Recognition library to recognize the user's emotional state from the text data. For example, if a user inputs "I want to be a data scientist," the emotion engine extracts the emotion "excited" from the text.

[1306] Step 3:

[1307] The server inputs a prompt sentence into the generative AI model based on the emotional state recognized by the emotion engine and the user's input information. Specifically, it generates the following prompt sentence:

[1308] User Sentiment: Excitement

[1309] Career goal: To become a data scientist

[1310] Desired lifestyle: Remote work

[1311] Future income goal: 10 million yen per year

[1312] Suggest appropriate future possibilities.

[1313] This prompt is then fed into a generative AI model using the OpenAI API.

[1314] Step 4:

[1315] The generative AI model generates future possibilities that fit the user based on the input prompt. Specifically, the generative AI model analyzes the prompt and generates future scenarios based on the user's emotional state and goals. The generated scenarios are returned to the server in text format.

[1316] Step 5:

[1317] The server receives the future scenario returned by the generative AI model and visualizes it as a specific scenario using simulation tools. Specifically, it simulates the user's life plan based on the generated scenario and generates data for visual display. This data is presented to the user in the form of graphs, charts, timelines, etc.

[1318] Step 6:

[1319] Users can view visualized future scenarios on their smartphones. Specifically, they can view graphs, charts, and timelines displayed on their smartphone screens to gain a concrete understanding of their own future possibilities. Based on the proposed scenarios, users can then create specific action plans.

[1320] Example 3

[1321] 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."

[1322] Conventional career path and life plan suggestion systems make suggestions based on the user's past and present information, but they have the problem of not being able to make suggestions or simulations that take into account the user's emotional state.In addition, there is a lack of a way to visually confirm the future life of the suggested career path or life plan, making it difficult for users to intuitively understand the effectiveness of the suggestions.

[1323] 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.

[1324] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing the user's life, means for analyzing the user's emotions and simulating the proposed possibilities based on the emotions, and means for displaying the simulation results in graphs and charts. This enables proposals and simulations that take the user's emotional state into consideration, and allows the user to visually confirm the future life of the proposed career path and life plan.

[1325] "User" refers to an individual who uses the system to propose and simulate their own career path and life plan.

[1326] "Career" refers to a user's past work experience, educational background, qualifications, etc.

[1327] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by the user.

[1328] "Values" refer to the beliefs, ways of thinking, and lifestyle standards that users consider important.

[1329] "Image of the future" refers to the hopes, goals, and visions that users have for the future.

[1330] An "AI agent" is a program that analyzes information entered by the user and suggests optimal career paths and life plans.

[1331] "Simulation" refers to the process of predicting and visually displaying a user's future life based on proposed career paths and life plans.

[1332] "Sentiment analysis" refers to the process of determining a user's emotional state from their input and adjusting suggestions and simulations accordingly.

[1333] "Graphs and charts" refer to diagrams that visually display the results of a simulation.

[1334] "Means" refers to a method, device, or program used to achieve a specific function.

[1335] This invention is a system that inputs a user's past and present career history, skills, values, etc., and proposes and simulates future career paths and life plans. Specific embodiments of this system are described below.

[1336] System configuration

[1337] The system consists of three main elements: a server, a terminal, and a user. The server receives input information from users, analyzes it, and generates proposals. The terminal is a device through which users input information and displays proposals and simulation results. Users are individuals who use the system to propose and simulate their own career paths and life plans.

[1338] Hardware and software used

[1339] Server: Use a server with high-performance computing capabilities. Specifically, you can use cloud services (e.g., Amazon Web Services, Microsoft Azure).

[1340] Database: Use a relational database such as MySQL or PostgreSQL.

[1341] AI agents: Use natural language processing libraries (e.g., NLTK, spaCy) and machine learning models (e.g., TensorFlow, PyTorch) implemented in Python.

[1342] Sentiment analysis engine: Uses an emotion recognition library (e.g., IBM Watson, Microsoft Azure Emotion API).

[1343] Data visualization libraries: Use Matplotlib, Plotly, etc. to display simulation results in graphs and charts.

[1344] Program processing

[1345] The server receives the information entered by the user and stores it in a database. The server then sends the stored information to an AI agent, which uses natural language processing libraries and machine learning models to analyze the information entered by the user and generate an optimal career path or life plan.

[1346] The generated proposals are sent to the terminal via the server and displayed to the user. The user can then check the proposed career path and life plan. The server then runs a simulation based on the proposals to predict the user's future life. The simulation results are visually displayed in graphs and charts.

[1347] The emotion analysis engine determines the user's emotional state from their input and adjusts the suggestions and simulations accordingly. For example, if the user is feeling anxious, it will simulate a life plan that involves a stable job. Conversely, if the user is excited, it will simulate a life plan that includes new challenges.

[1348] Specific examples

[1349] Consider a scenario where a user enters, "I want to pursue a career as a data scientist." The server receives this information and sends it to an AI agent. The AI ​​agent analyzes the user's skill set (e.g., Python, machine learning, data analysis) and values ​​(e.g., stability, challenge) and suggests suitable jobs and companies (e.g., data scientist positions at major IT companies).

[1350] The system then simulates the user's future income and lifestyle based on the proposed career path, displaying graphs of the user's annual income and living expenses if they were to work as a data scientist, for example.

[1351] The emotion engine recognizes emotions from the text entered by the user, and if the user is feeling anxious, it simulates a life plan that involves a stable job. Conversely, if the user is excited, it simulates a life plan that includes new challenges.

[1352] Prompt Sentence Examples

[1353] "I want to advance my career as a data scientist. I have skills in Python and machine learning, but I'm looking for job stability. What career path is right for me?"

[1354] By inputting this prompt sentence into the generative AI model, it is possible to propose the optimal career path and life plan for the user. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1355] Step 1:

[1356] The user enters information

[1357] Users enter information such as their skill set, values, current occupation, and interests through the system interface. The information is sent to the server in text format. Specifically, users enter information into input fields on a web form or mobile app and click the "Submit" button.

[1358] Step 2:

[1359] The server receives the input information

[1360] The server receives the information sent by the user as an HTTP POST request. The received information is parsed in JSON format. The server temporarily stores the parsed information in memory.

[1361] Step 3:

[1362] The server saves the input information in a database

[1363] The server stores the received information in a database. Specifically, it executes an SQL query to store the information in a relational database (e.g., MySQL, PostgreSQL). Once the input information is stored in the database, it becomes available for further processing.

[1364] Step 4:

[1365] The server sends input information to the AI ​​agent.

[1366] The server sends the stored information to the AI ​​agent via a REST API in JSON format, which is implemented in Python and prepares to parse the received information.

[1367] Step 5:

[1368] The AI ​​agent analyzes the input information

[1369] The AI ​​agent uses natural language processing libraries (e.g., NLTK, spaCy) and machine learning models (e.g., TensorFlow, PyTorch) to analyze the user's input. Specifically, it tokenizes the input and analyzes the meaning of each token. The analysis results are output as data that extracts the user's skill set and values.

[1370] Step 6:

[1371] The AI ​​agent generates recommendations based on the analysis results.

[1372] Based on the analysis results, the AI ​​agent generates the optimal career path and life plan for the user. The generated proposals are returned to the server in JSON format. Specifically, it suggests suitable jobs and companies based on the user's skill set and values.

[1373] Step 7:

[1374] The server sends the proposal to the device

[1375] The server sends the proposal received from the AI ​​agent to the terminal. The proposal is sent as an HTTP response, and is passed to the terminal in JSON format. The terminal is the user's device (e.g., PC, smartphone).

[1376] Step 8:

[1377] The device displays the suggestions to the user

[1378] The device displays the received proposals to the user. Specifically, the proposals are displayed in HTML or UI components of the mobile app. The user can then check the proposed career path or life plan.

[1379] Step 9:

[1380] The server runs the simulation based on the proposal.

[1381] The server simulates the user's future life based on the proposed career path and life plan. The simulation includes a function to predict the user's future income and lifestyle. Specifically, it executes a simulation algorithm and generates a prediction result.

[1382] Step 10:

[1383] The server sends the simulation results to the device.

[1384] The server sends the simulation results to the terminal as an HTTP response, and the results are passed to the terminal in JSON format. The simulation results are displayed in graphs and charts.

[1385] Step 11:

[1386] The terminal displays the simulation results to the user.

[1387] The terminal displays the simulation results to the user. Specifically, the simulation results are visually displayed in graphs and charts, allowing the user to check their future income and lifestyle.

[1388] Step 12:

[1389] Emotion engine analyzes user emotions

[1390] The emotion engine analyzes the text and voice data entered by the user to determine the user's emotional state. Specifically, it uses an emotion recognition library (e.g., IBM Watson, Microsoft Azure Emotion API) to analyze the emotional state. The analysis results are output as data indicating the user's emotional state.

[1391] Step 13:

[1392] Emotion engine runs emotion-based simulations

[1393] The emotion engine simulates the proposed possibilities based on the user's emotional state. Specifically, it executes a simulation algorithm according to the user's emotional state and generates results. For example, if the user is feeling anxious, it will simulate a life plan if the user has a stable job.

[1394] Step 14:

[1395] The server sends the emotion-based simulation results to the device.

[1396] The server sends the simulation results received from the emotion engine to the device as an HTTP response, and the results are passed to the device in JSON format.

[1397] Step 15:

[1398] The device displays the emotion-based simulation results to the user.

[1399] The device displays the emotion-based simulation results to the user. Specifically, the simulation results are visually displayed in graphs and charts. The user can then check the life plan that corresponds to their own emotional state.

[1400] (Application example 3)

[1401] 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."

[1402] Conventional career path and life plan suggestion systems make suggestions based on the user's skill set and values, but they are unable to take the user's emotional state into account, which can result in the system failing to make the best suggestions for the user. It is also difficult for users to concretely imagine the future life of the proposed career path or life plan, making it difficult for them to decide whether to accept the suggestion. Furthermore, there is a lack of a way to visually display the simulation results in an easy-to-understand manner, making it difficult for users to concretely understand their future life.

[1403] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1404] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing life, means for inputting the user's emotional state, an emotion engine that adjusts the proposed possibilities based on the emotional state, means for analyzing the input information using a generative AI model, and means for displaying the simulation results in graphs and charts. This makes it possible to propose optimal career paths and life plans that take the user's emotional state into consideration, making it easier to concretely imagine the proposed future life.

[1405] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, beliefs, and values ​​into the system.

[1406] The "means for inputting the user's image of the future" is an interface that allows the user to input information such as their future goals and desired lifestyle into the system.

[1407] "An AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests optimal career paths and life plans.

[1408] "A means for simulating proposed possibilities and visualizing life" is a system for simulating future life based on proposed career paths and life plans and visually displaying the results.

[1409] "Means for inputting user's emotional state" refers to an interface that allows a user to input their current emotional state (e.g., anxiety, excitement, joy, etc.) into the system.

[1410] The "emotion engine that adjusts suggested possibilities based on emotional state" is a system for adjusting suggested career paths and life plans taking into account the user's emotional state.

[1411] "Means for analyzing input information using a generative AI model" refers to a system that uses a generative AI model to analyze information entered by a user and generate optimal suggestions.

[1412] "Means for displaying simulation results in graphs and charts" refers to a system that generates graphs and charts to visually display the results of a simulation in an easy-to-understand manner.

[1413] As an embodiment of the present invention, the following system can be constructed.

[1414] System Configuration

[1415] The system includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing life, a means for inputting the user's emotional state, an emotion engine that adjusts the suggested possibilities based on the emotional state, a means for analyzing the input information using a generative AI model, and a means for displaying the simulation results in graphs and charts.

[1416] Hardware and software used

[1417] Hardware: Smartphone

[1418] Software: Python, OpenAI API, Matplotlib

[1419] Data processing and calculation

[1420] The server receives information entered by the user on their smartphone, such as their past and present career history, skills, values, future image, and emotional state. This information is then analyzed using a generative AI model. Specifically, the server uses the OpenAI API to analyze the user's input and propose optimal career paths and life plans.

[1421] The suggested career paths and life plans are adjusted by an emotion engine based on the user's emotional state: for example, if the user is anxious, it will suggest a stable career, and if the user is excited, it will suggest a plan that includes new challenges.

[1422] The simulation tool simulates future life based on proposed career paths and life plans, and visualizes the results in graphs and charts. Matplotlib is used to visually display future income and lifestyle.

[1423] Specific examples

[1424] If a user has the skills of "programming" and "data analysis," and values ​​"stability" and "challenge," and inputs that their emotional state is "anxious," the AI ​​will suggest a stable occupation (e.g., data scientist) and simulate future income based on that occupation.

[1425] Prompt Sentence Examples

[1426] User Skill Set: Programming, Data Analysis

[1427] Values: Stability, Challenge

[1428] Emotional state: Anxiety

[1429] Please suggest the best career path and life plan for you.

[1430] In this way, users can more easily visualize their future possibilities and choose the most suitable career path and life plan.

[1431] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1432] Step 1:

[1433] Users use their smartphones to input information such as their past and present career history, skills, values, future image, and emotional state, which then collects detailed user profile information. The input information is then sent to the server.

[1434] Step 2:

[1435] The server inputs the received user information into the generative AI model. Specifically, it uses the OpenAI API to analyze information such as the user's skill set, values, and emotional state. As a result of the analysis, an optimal career path and life plan for the user is generated. The input is the user's profile information, and the output is a proposed career path or life plan.

[1436] Step 3:

[1437] The server inputs the generated career path or life plan into the emotion engine, which adjusts the proposal based on the user's emotional state. For example, if the user is feeling anxious, it will suggest a stable job, and if the user is excited, it will suggest a plan that includes new challenges. The input is the proposed career path or life plan and the user's emotional state, and the output is the adjusted career path or life plan.

[1438] Step 4:

[1439] The server inputs the adjusted career path and life plan into the simulation tool. The simulation tool simulates future life and predicts income and lifestyle. Specifically, Matplotlib is used to visualize future income and lifestyle in graphs and charts. The input is the adjusted career path and life plan, and the output is graphs and charts of the simulation results.

[1440] Step 5:

[1441] The server sends the generated graphs and charts to a smartphone. The user can visually check the simulation results on the smartphone screen. This makes it easier for the user to visualize the proposed career path and life plan. The input is the graphs and charts of the simulation results, and the output is the visual information displayed on the user's smartphone screen.

[1442] 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.

[1443] 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 a voice, text data indicating a text, and image data indicating an image are also input.

[1444] The data generation model 58 performs inference on the input inference data according to the instructions given by the prompts, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1445] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1446] 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.

[1447] [Third embodiment]

[1448] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1449] 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.

[1450] 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).

[1451] 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.

[1452] 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.

[1453] 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).

[1454] 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.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1460] "Example 1"

[1461] The system of the present invention provides a means for users to input their past and current career history, skills, values, etc. Specifically, the system allows users to input their own information through a user interface. For example, users can input their work history, skill set, values, hobbies, interests, etc.

[1462] "Example 2"

[1463] Next, we provide a means for users to input their future vision. Specifically, we allow users to input their future goals and aspirations. For example, users can input their career goals, desired lifestyle, future income goals, etc.

[1464] "Example 3"

[1465] We provide an AI agent that suggests future possibilities that suit the user based on the information entered. Specifically, the AI ​​agent analyzes the information entered by the user and, based on that, suggests the most suitable career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values. "Example 4"

[1466] Finally, the system provides a means to simulate the proposed possibilities and visualize the user's life. Specifically, the system simulates and visualizes the user's future life based on the career path and life plan proposed by the system. For example, the system can simulate the user's future income and lifestyle based on the proposed career path and display them in graphs and charts.

[1467] The processing flow of each embodiment will be described below.

[1468] "Example 1"

[1469] Step 1: The user enters their past and current career history, skills, values, etc. through the system's user interface. For example, the user enters their work history, skill set, values, hobbies, interests, etc.

[1470] "Example 2"

[1471] Step 1: The user inputs their own image of the future through the system's user interface. For example, the user inputs their career goals, desired lifestyle, future income goals, etc.

[1472] "Example 3"

[1473] Step 1: The AI ​​agent analyzes the user's input.

[1474] Step 2: The AI ​​agent uses the analysis results to suggest the optimal career path and life plan for the user. For example, the AI ​​agent can suggest suitable jobs and companies based on the user's skill set and values.

[1475] "Example 4"

[1476] Step 1: The system simulates the user's future life based on the career path and life plan suggested by the system.

[1477] Step 2: Visualize the simulation results. For example, you can simulate the user's future income and lifestyle based on the proposed career path and display it in graphs and charts.

[1478] Example 1

[1479] 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."

[1480] Conventional systems provided a way for users to input information such as their past and present career history, skills, and values, but lacked the means to propose specific future possibilities based on this information, or to simulate and visualize these proposals. Furthermore, there was no established process for efficiently analyzing the data entered by users and generating appropriate responses using a generative AI model. This made it difficult to provide specific and useful advice to users.

[1481] 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.

[1482] In this invention, the server includes: a means for inputting the user's past and present career history, skills, values, etc.; a means for inputting the user's image of the future; an AI agent that proposes future possibilities suitable for the user based on the input information; a means for simulating the proposed possibilities and visualizing life; a means for receiving the data input by the user and storing it in a database; a means for analyzing the stored data and inputting prompt sentences to the generative AI model; and a means for the generative AI model to generate responses and return the responses to the user. This makes it possible to propose specific future possibilities based on the user's input information and simulate and visualize the proposals. Furthermore, the generative AI model can be used to generate appropriate responses and provide specific and useful advice to the user.

[1483] "User" refers to an individual who uses the system to input their information and receive future opportunities and advice.

[1484] "Career" refers to the user's past job history, educational background, etc.

[1485] "Skills" refers to the skills, abilities, and expertise that a user possesses.

[1486] "Values" refer to the beliefs and ideas that users consider important.

[1487] "Image of the future" refers to the hopes, goals, and visions that users have for the future.

[1488] An "AI agent" refers to an artificial intelligence system that suggests future possibilities based on user input.

[1489] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[1490] "Database" means a digital storage system for storing and managing information entered by users.

[1491] A "generative AI model" refers to an artificial intelligence model that generates responses based on user input information.

[1492] "Prompt" refers to a textual instruction that is input to a generative AI model.

[1493] "Response" refers to the advice or suggestions that the generative AI model generates based on the prompt.

[1494] This invention is a system that allows users to input their past and present career history, skills, values, etc., and then suggests and simulates future possibilities based on that information. Specific embodiments of this system are described below.

[1495] First, a user accesses a user interface provided through a web browser. This interface is built using web technologies such as HTML, CSS, and JavaScript. The user then enters information such as work history, skill set, values, hobbies, and interests into an input form.

[1496] When the user completes the input and clicks the submit button, the device sends the input data as an HTTP request to the server. This request contains data in JSON format. The server receives the HTTP request sent from the device, analyzes the received data, and stores it in a database. The database can be MySQL or MongoDB.

[1497] The server analyzes the stored data to extract information such as the user's work history, skill set, values, hobbies, and interests. The analysis is performed using programming languages ​​such as Python and Node.js. Based on the analysis results, the server generates a prompt. The generated prompt is then input into a generative AI model (e.g., OpenAI's GPT-4).

[1498] The generative AI model generates a response based on the input prompt. The response may include career advice or suggestions for skill improvement for the user. The server receives the response from the generative AI model and returns it to the user's device. The user can view the response in their web browser.

[1499] For example, if a user enters "5 years of experience as a software engineer" as their work history and "Python, JavaScript, React" as their skill set, the server stores this information in the database and then inputs the following prompt to the generative AI model:

[1500] Example prompt sentence:

[1501] User's work experience: 5 years of experience as a software engineer

[1502] User skill set: Python, JavaScript, React

[1503] User values: Emphasize teamwork

[1504] User's hobbies: programming, reading

[1505] User Interest: Latest Trends in AI Technology

[1506] Based on this prompt, the generative AI model generates career advice and skill improvement suggestions tailored to the user, such as, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[1507] In this way, users can receive specific and useful advice based on their own information.

[1508] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1509] Step 1:

[1510] The user enters information

[1511] Users access the user interface provided through a web browser and enter information such as their work history, skill set, values, hobbies, and interests into an input form. Examples of input data include "5 years of experience as a software engineer," "Python, JavaScript, React," "emphasis on teamwork," "programming, reading," and "latest trends in AI technology."

[1512] Step 2:

[1513] The device sends the input data to the server

[1514] When the user clicks the submit button, the terminal sends the input data as an HTTP request to the server. This request contains data in JSON format. The input data is information entered by the user, such as work history, skill set, values, hobbies, and interests. The terminal sends this data to the server.

[1515] Step 3:

[1516] The server receives the data and stores it in the database

[1517] The server receives HTTP requests sent from the terminal. It analyzes the received data and stores it in a database. Databases such as MySQL and MongoDB are used. The input data includes information such as the user's work history, skill set, values, hobbies, and interests, and this is stored in the database. For example, the following data is stored in a MySQL database:

[1518] sql

[1519] INSERT INTO user_data (Work history, Skill set, Values, Hobbies, Interests) VALUES ('5 years of experience as a software engineer', '["Python", "JavaScript", "React"]', 'Values ​​teamwork', '["Programming", "Reading"]', 'The latest trends in AI technology');

[1520] Step 4:

[1521] The server analyzes the stored data

[1522] The server analyzes the user information stored in the database. Programming languages ​​such as Python and Node.js are used for the analysis. As a result of the analysis, the user's work history, skill set, values, hobbies, interests, etc. are extracted. The input data is the user information stored in the database, and the output data is the user's work history, skill set, values, hobbies, interests, etc. extracted by the analysis.

[1523] Step 5:

[1524] The server inputs a prompt to the generative AI model.

[1525] The server generates a prompt sentence based on the analysis results. The generated prompt sentence is input into the generative AI model. The input data is the user information extracted as the analysis result, and the output data is the generated prompt sentence. For example, the following prompt sentence is generated:

[1526] User's work experience: 5 years of experience as a software engineer

[1527] User skill set: Python, JavaScript, React

[1528] User values: Emphasize teamwork

[1529] User's hobbies: programming, reading

[1530] User Interest: Latest Trends in AI Technology

[1531] Step 6:

[1532] A generative AI model generates a response

[1533] The generative AI model generates a response based on the input prompt. The response can include career advice or suggestions for skill improvement for the user. The input data is the generated prompt, and the output data is the response generated by the generative AI model. For example, the generated advice might be, "Based on your skill set and interests, we recommend you take the latest online courses on AI technology."

[1534] Step 7:

[1535] The server returns the generated response to the user

[1536] The server receives the response from the generative AI model and returns it to the user's device. The user can view the response on a web browser. The input data is the response from the generative AI model, and the output data is the response displayed on the user's device.

[1537] (Application example 1)

[1538] 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."

[1539] Previous systems provided a way for users to input their past and current career history, skills, values, etc., but lacked the functionality to recommend the most suitable content to users. This made it difficult for users to find content that matched their interests and skills. Furthermore, there was no way to calculate the similarity of recommended content and present the most suitable content. This resulted in low user satisfaction and limited the usefulness of the system.

[1540] 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.

[1541] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user. This allows users to easily find content that matches their interests and skills, improving the utility value of the system.

[1542] "Means for inputting users' past and present career history, skills, values, etc." refers to means that provide an interface for users to input information such as their work history, skill set, values, hobbies, and interests.

[1543] "Means for inputting the user's image of the future" refers to a means for providing an interface for the user to input information such as their future goals and desired career path.

[1544] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the best future job type, company, and next step goal for the user.

[1545] "Means for simulating proposed possibilities and visualizing life" refers to a means for simulating and visually displaying a user's life plan based on future possibilities proposed by an AI agent.

[1546] "Means for recommending optimal content based on information entered by the user" refers to a means for analyzing information entered by the user, such as career history, skills, values, hobbies, and interests, and then recommending the most appropriate content for the user, such as movies, books, music, and news articles, based on that information.

[1547] The "means for calculating the similarity of the recommended content" refers to an algorithm or software for calculating the similarity between the recommended content and the user's input information.

[1548] The "means for presenting the most similar content to the user" refers to a means for selecting the most suitable content for the user based on the calculated similarity and presenting it to the user.

[1549] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for recommending optimal content based on the user's input information, means for calculating the similarity of the recommended content, and means for presenting the most similar content to the user.

[1550] System configuration

[1551] The server provides an interface, which may include a smartphone application or a web interface, for users to enter information about their work history, skill set, values, hobbies, interests, etc. The information entered by the user is sent to the server and stored in a database.

[1552] The server then uses an AI agent to suggest future jobs, companies, and next steps based on the user's input. This AI agent uses a generative AI model to analyze the user's information and suggest optimal future possibilities.

[1553] Furthermore, the server provides a means for simulating and visually displaying the user's life plan based on the proposed future possibilities, so that the user can easily understand the future scenario concretely.

[1554] Content recommendation function

[1555] To recommend optimal content based on user input, the server analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends the most suitable content for the user, such as movies, books, music, and news articles. This recommendation method uses a generative AI model to compare the user's information with information in a content database and select the most suitable content.

[1556] To calculate the similarity of the recommended content, the server uses an algorithm such as cosine similarity, which calculates the similarity between the user's input information and the content description, and presents the most similar content to the user.

[1557] Hardware and software used

[1558] This system is realized using smartphones, servers, databases, generative AI models, and software such as TfidfVectorizer and cosine_similarity. The smartphone provides the user interface, while the server processes and stores data. The generative AI model is used to analyze user information and recommend optimal content.

[1559] Specific examples

[1560] For example, if a user enters the following information:

[1561] Work Experience: Data Scientist

[1562] Skillset: Python, Data Analysis, Machine Learning

[1563] Values: Data-driven decision making

[1564] Hobbies: Reading, watching movies

[1565] Interests: Big Data, AI

[1566] In this case, the server will recommend the book "The Future of AI."

[1567] Prompt Sentence Examples

[1568] Enter the user's work experience, skillset, values, hobbies, and interests. For example, enter "Work experience: Data Scientist, Skill set: Python, Data analysis, Machine learning, Values: Data-driven decision-making, Hobbies: Reading, Watching movies, Interests: Big data, AI."

[1569] In this way, a system can be realized that recommends optimal content to users.

[1570] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1571] Step 1:

[1572] Users use a smartphone or web interface to enter information such as their work history, skill set, values, hobbies, and interests. The entered information is sent to a server and stored in a database. The input data is in text format and includes the user's past and present work history, skills, values, etc.

[1573] Step 2:

[1574] The server uses a generative AI model to suggest future jobs, companies, and desired next steps based on the information entered by the user. The generative AI model analyzes the user's input data and suggests optimal future possibilities. This analysis uses natural language processing technology, which converts the user's input data into a feature vector. The output is the future jobs, companies, and desired next steps suggested to the user.

[1575] Step 3:

[1576] The server simulates and visually displays the user's life plan based on the proposed future possibilities. The simulation means, which allows the user to concretely understand future scenarios, includes visual elements such as graphs and charts. The input is the proposed data from the generative AI model, and the output is a visually displayed life plan.

[1577] Step 4:

[1578] The server uses a generative AI model to recommend optimal content based on user input. It analyzes information such as the user's background, skills, values, hobbies, and interests, and then recommends content such as movies, books, music, and news articles that are optimal for the user. The input is the user's input data, and the output is a list of recommended content.

[1579] Step 5:

[1580] The server uses an algorithm such as cosine similarity to calculate the similarity between the user's input information and the content description. The input is the user's feature vector and the content's feature vector, and the output is a similarity score.

[1581] Step 6:

[1582] The server selects the most suitable content for the user based on the calculated similarity and presents it to the user. The most similar content is presented to the user. The input is the similarity score, and the output is the optimal content to be presented to the user.

[1583] In this way, a system for recommending optimal content to a user is realized.

[1584] Example 2

[1585] 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."

[1586] In conventional systems, it was difficult for users to input a specific image of their future and receive appropriate suggestions based on that. Furthermore, there was a lack of means to utilize generative AI models based on the user's future goals and aspirations, resulting in a lack of accuracy and specificity in the suggestions made to users. This made it difficult for users to specifically understand and plan for their future possibilities.

[1587] 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.

[1588] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing life, means for sending prompt sentences to the generative AI model based on the image of the future input by the user, and means for the generative AI model to generate responses and present them to the user. This allows the user to specifically input their image of the future and receive highly accurate suggestions based on it using the generative AI model.

[1589] A "user" is an individual who uses the system to input information about their past and present, as well as an image of their future, and receives suggestions.

[1590] "Career" refers to the user's career history, including occupations and educational background.

[1591] "Skills" refer to the skills and abilities that users possess.

[1592] "Values" refer to the beliefs and ideas that users consider important.

[1593] "Image of the future" refers to the goals and hopes that users want to achieve in the future.

[1594] An "AI agent" is a program that suggests future possibilities that suit the user based on the information they input.

[1595] "Simulation" is the process of virtually trying out proposed future possibilities and visualizing the results.

[1596] "Generative AI model" refers to an artificial intelligence model for generating responses based on user input.

[1597] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[1598] "Response" refers to the output that a generative AI model generates based on a prompt.

[1599] This invention is a system that allows users to input specific images of their future and receive highly accurate proposals based on those images using a generative AI model. Specific embodiments of this system are described below.

[1600] Hardware and software used

[1601] Hardware: Servers, user devices (PCs, smartphones, etc.)

[1602] Software: web browsers, server-side applications (e.g., Node.js), databases (e.g., MySQL), generative AI models (e.g., GPT-4)

[1603] System configuration

[1604] 1. User input:

[1605] Users open a web browser on a device such as a PC or smartphone, access the system's URL, and enter their past and present career history, skills, values, and image of the future into a form displayed on the system's web page.

[1606] 2. Means of data transmission:

[1607] When the user clicks the submit button on the form, the device sends the entered data to the server as an HTTP POST request.

[1608] 3. Data storage means:

[1609] The server processes the received data and saves it to a database. For example, the server receives the data using Node.js and saves it by executing an "INSERT" query in a MySQL database.

[1610] 4. How to send prompts to the generative AI model:

[1611] The server sends prompts to the generative AI model based on the stored data. For example, the server might generate a prompt such as, "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and send it to GPT-4.

[1612] 5. How the generative AI model generates responses:

[1613] The generative AI model generates a response based on the prompt and returns it to the server. For example, GPT-4 might generate a response like, "To succeed as a data scientist, it's important to master the following skills..." and return it to the server.

[1614] 6. Response Presentation Method:

[1615] The server sends the generated response to the user's terminal, where the user can view the generated response on their web browser.

[1616] Specific examples

[1617] User input: "Future career goal: Data scientist, Desired lifestyle: Remote work, Future income goal: Annual income of 10 million yen"

[1618] Prompt for the generative AI model: "The user's career goal is to become a data scientist. Their desired lifestyle is remote work, and their future income goal is to earn 10 million yen a year. Based on this, please suggest steps the user can take to achieve this goal."

[1619] In this way, the system allows users to input specific images of their future, and the generative AI model generates responses based on those images. This system allows users to concretely understand and plan for their future possibilities.

[1620] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1621] Step 1:

[1622] A user accesses the system using a terminal.

[1623] A user opens a web browser on a device such as a PC or smartphone and enters the system's URL to access it. For example, a user accesses "https: / / example.com" using Google Chrome. The input is the URL, and the output is the system's web page.

[1624] Step 2:

[1625] The user inputs an image of the future.

[1626] Users enter their past and present career history, skills, values, and future vision into a form displayed on the system's web page. For example, they enter "I want to become a data scientist" as their "career goal," "remote work" as their desired lifestyle, and "annual income of 10 million yen" as their future income goal. The input is the user's information, and the output is the data entered into the form.

[1627] Step 3:

[1628] The terminal sends the input data to the server.

[1629] When a user clicks the submit button on a form, the terminal sends the entered data to the server as an HTTP POST request. For example, when a user clicks the "Submit" button, the data is sent to "https: / / example.com / submit". The input is the form data, and the output is an HTTP request to the server.

[1630] Step 4:

[1631] The server receives the data and stores it in a database.

[1632] The server processes the received data and stores it in a database. For example, the server receives the data using Node.js and executes an "INSERT" query in a MySQL database to store the data. The input is the data from the HTTP request and the output is the record stored in the database.

[1633] Step 5:

[1634] The server sends a prompt to the generative AI model.

[1635] The server sends prompts to the generative AI model based on the stored data. For example, the server generates a prompt such as "The user's career goal is to become a data scientist. Based on this, please predict their future lifestyle." and sends it to the generative AI model. The input is the database record, and the output is the generated prompt.

[1636] Step 6:

[1637] The generative AI model generates a response and returns it to the server.

[1638] The generative AI model generates a response based on the prompt sentence and returns it to the server. For example, the generative AI model generates a response such as "To succeed as a data scientist, it is important to master the following skills..." and returns it to the server. The input is the prompt sentence, and the output is the generated response.

[1639] Step 7:

[1640] The server sends a response to the user terminal.

[1641] The server sends the generated response to the user terminal. For example, the server sends the generated response as an HTTP response to the user's web browser. The input is the generated response, and the output is the HTTP response to the user terminal.

[1642] Step 8:

[1643] The user confirms the response.

[1644] The user sees the generated response in their web browser. For example, the user reads the message "To be successful as a data scientist, it is important that you master the following skills..." The input is the HTTP response and the output is the user's understanding.

[1645] (Application example 2)

[1646] 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."

[1647] Conventional systems lack a means for users to specifically input their future goals and aspirations and then provide personalized content based on those goals. This makes it difficult to efficiently provide information and resources that match the user's vision of the future. Furthermore, there is a need for a system that can generate specific content based on the user's future goals, thereby increasing the user's motivation and helping them achieve their goals.

[1648] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting the user's past and present career history, skills, values, etc., a means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, a means for simulating the suggested possibilities and visualizing life, a means for generating relevant content based on the user's future goals and hopes, and a means for providing the generated content to the user. This makes it possible to provide personalized content that matches the user's vision of the future.

[1649] "User" refers to any individual or entity that uses the System.

[1650] "Past and current experience" refers to information such as the user's work history, educational background, and skills.

[1651] "Skills" refers to the specialized knowledge, techniques, and abilities possessed by the user.

[1652] "Values" refers to the beliefs, ethics, and lifestyles that users consider important.

[1653] "Image of the future" refers to the goals that users want to achieve in the future, their desired lifestyle, income goals, etc.

[1654] An "AI agent" refers to an artificial intelligence system that analyzes information input by the user and suggests future possibilities.

[1655] "Simulation" refers to the process of virtually recreating proposed future possibilities and visually presenting them to the user.

[1656] "Life visualization tools" refers to tools and technologies that allow users to visually display future scenarios.

[1657] "Content" refers to information, videos, articles, podcasts, and other media provided to users.

[1658] "Generation means" refers to the technology or algorithms used to create relevant content based on user input.

[1659] "Means of delivery" refers to the technology and methods used to deliver the generated content to users.

[1660] A system for implementing this invention includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that suggests future possibilities that suit the user based on the input information, means for simulating the suggested possibilities and visualizing life, means for generating relevant content based on the user's future goals and hopes, and means for providing the generated content to the user.

[1661] System configuration

[1662] 1. User input method:

[1663] Users use devices such as smartphones or computers to input their past and present career history, skills, values, and vision for the future, and this information is sent to a server.

[1664] 2. AI Agents:

[1665] The server receives the information sent by the user and analyzes it using an AI agent, which uses a generative AI model to suggest future possibilities for the user.

[1666] 3. Simulation methods:

[1667] The server runs a simulation based on the proposed future possibilities and visualizes the user's life, and the results of this simulation are displayed on the user's device.

[1668] 4. Content Generation Methods:

[1669] The server generates relevant content based on the user's future goals and aspirations, using generative AI models in the process to provide the most relevant information to the user.

[1670] 5. Content Delivery Method:

[1671] The server delivers the generated content to the user's device, where the user can view the content via their smartphone or PC.

[1672] Hardware and software used

[1673] Hardware: smartphones, PCs, servers

[1674] Software: Python, OpenAI API

[1675] Data processing and calculation

[1676] The server receives the data sent by the user and performs the following processing.

[1677] 1. Data analysis: Analyze the user's background, skills, values, and future vision.

[1678] 2. Prompt generation: Generate prompts based on the user's goals.

[1679] 3. Content generation: Use generative AI models to generate personalized content based on prompts.

[1680] Specific examples

[1681] For example, if a user enters the goals "become a data scientist," "achieve remote work," and "earn 10 million yen a year," the following prompt sentences will be generated:

[1682] Example prompt sentence:

[1683] The user's career goal is to become a data scientist, their desired lifestyle is to work remotely, and their future income goal is to earn 10 million yen a year. Please suggest content related to this.

[1684] By inputting this prompt into a generative AI model, the system can provide users with the most appropriate content, such as learning resources for becoming a data scientist, tips for remote work, or a career path to earning 10 million yen a year.

[1685] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1686] Step 1:

[1687] Users use devices such as smartphones or PCs to input their past and present career history, skills, values, and vision for the future. The input information is sent from the device to a server. Specifically, the user enters information into an input form and presses the send button, which sends the data to the server.

[1688] Step 2:

[1689] The server receives the data sent by the user and stores it in a database. The stored data includes the user's career history, skills, values, and future image. Specifically, the server analyzes the received data, converts it into an appropriate format, and stores it in the database.

[1690] Step 3:

[1691] The server generates prompts based on the stored data to suggest future possibilities for the user. The generated prompts are created based on the user's goals and wishes. Specifically, the server analyzes the user's input data and constructs prompts suitable for the generative AI model.

[1692] Step 4:

[1693] The server uses the generated prompt sentence to send a request to the generative AI model, which then generates personalized content based on the prompt sentence. Specifically, the server uses the OpenAI API to send the prompt sentence and receive the generated content.

[1694] Step 5:

[1695] The server analyzes the generated content and converts it into a format for providing to the user. Specifically, the server converts the generated content into an appropriate format and arranges it in a form that is easy for the user to view.

[1696] Step 6:

[1697] The server delivers the prepared content to the user's device, who can then view it via a smartphone or PC. Specifically, the server sends the content to the user's device, allowing the user to view the content through an application.

[1698] Step 7:

[1699] The user browses the provided content and obtains information and resources for achieving future goals. Specifically, the user browses the content through the application and obtains the necessary information.

[1700] Example 3

[1701] 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."

[1702] Conventional career path and life plan suggestion systems have difficulty fully analyzing the information entered by users and making optimal suggestions for each individual user. Furthermore, they lacked a way to visually understand the future impact of the suggested career path or life plan, making it difficult for users to visualize the specifics of the suggestions. This led to problems such as insufficient decision-making when planning their own future.

[1703] 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.

[1704] In this invention, the server includes means for inputting the user's past and present career history, skills, values, etc., means for inputting the user's image of the future, an AI agent that proposes future possibilities that suit the user based on the input information, means for simulating the proposed possibilities and visualizing a life, natural language processing means for analyzing the user's input information, machine learning means for proposing optimal career paths and life plans based on the analysis results, means for simulating and visualizing future life based on the proposed career paths and life plans, and visualization means for displaying the simulation results in graphs and charts.This allows the user to be proposed optimal career paths and life plans based on their own skill sets and values, and to visually understand the impact of these on their future.

[1705] "User" refers to an individual who uses the system to plan their own career path or life plan.

[1706] "Career" refers to the user's past job history, educational background, etc.

[1707] "Skills" refers to the specialized knowledge and techniques possessed by the user.

[1708] "Values" refer to the beliefs and ideas that users consider important.

[1709] "Image of the future" refers to the hopes and goals that users have for the future.

[1710] An "AI agent" is software that analyzes information entered by the user and suggests optimal career paths and life plans.

[1711] "Simulation" refers to the process of predicting a user's future life based on suggested career paths and life plans.

[1712] "Visualization" refers to displaying simulation results in a visual format such as a graph or chart.

[1713] "Natural language processing means" refers to technology for analyzing text data entered by a user.

[1714] "Machine learning methods" refer to algorithms that suggest optimal career paths and life plans based on past data.

[1715] "Graphs and charts" refer to diagrams that visually display the results of a simulation.

[1716] This invention is a system that inputs a user's past and present career history, skills, values, etc., and based on that, proposes future career paths and life plans, and then simulates and visualizes the proposals. Specific embodiments of this system are described below.

[1717] System configuration

[1718] Hardware and software configuration:

[1719] Server: Receives data, analyzes, simulates, and visualizes it. The server must have a powerful processor and ample memory.

[1720] Device: The device where a user enters information and sees results, such as a computer, tablet, or smartphone.

[1721] Natural language processing libraries: Use Python NLP libraries such as spaCy and NLTK.

[1722] Machine learning libraries: Use scikit-learn or TensorFlow.

[1723] Visualization tools: Use Matplotlib or Plotly.

[1724] Program processing

[1725] Data collection and analysis:

[1726] The user uses the device to input information such as their skill set, values, and interests. For example, the user inputs a skill set such as "programming (Python, Java) and data analysis" or values ​​such as "work-life balance and social contribution." The device then sends the input information to the server. The server then analyzes the received data using a natural language processing library (e.g., spaCy or NLTK).

[1727] Career path and life plan suggestions:

[1728] The server then uses the analysis results to suggest the best career path or life plan for the user. For example, it might suggest jobs such as data scientist or software engineer at an edtech company based on the user's skill set and values. It then uses machine learning libraries (such as scikit-learn and TensorFlow) to compare the results with past data to determine the best option.

[1729] Simulation and visualization:

[1730] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib or Plotly). The server sends the generated graphs and charts to the device, which then displays them to the user.

[1731] Specific examples

[1732] The user enters the following information:

[1733] Skill set: Programming (Python, Java), Data analysis

[1734] Values: Work-life balance, social contribution

[1735] Interests: Environmental protection, education

[1736] The AI ​​agent analyzes this information and makes suggestions such as:

[1737] Suitable jobs: Data scientist, software engineer at an edtech company

[1738] Suitable companies: Environmental startups, educational nonprofits

[1739] It also simulates your future income and lifestyle based on your proposed career path, displaying graphs like the one below:

[1740] Income trend graph

[1741] A chart showing lifestyle changes

[1742] Example prompt sentence:

[1743] "Please suggest suitable jobs and companies based on the user's skill set and values. The user's skill set is programming (Python, Java) and data analysis. Their values ​​are work-life balance and social contribution. Their interests are environmental protection and education."

[1744] In this way, the user is presented with an optimal career path and life plan based on their own skill set and values, and is able to visually understand the impact of these on the future. The flow of the identification process in Example 3 will be described with reference to FIG.

[1745] Step 1:

[1746] The user uses the device to input information such as their skill set, values, and interests. For example, the user might input a skill set such as "programming (Python, Java) and data analysis" or values ​​such as "work-life balance and social contribution." The input information is saved in the input form on the device.

[1747] Input: Information about the user's skill set, values, interests, etc.

[1748] Output: User information stored on the device

[1749] Step 2:

[1750] The device converts the entered user information into JSON format and sends it to the server using an HTTP POST request, which then stores the received data in a database.

[1751] Input: User information stored on the device

[1752] Output: User information sent to the server

[1753] Step 3:

[1754] The server passes the stored data to an AI agent, which uses a natural language processing library (e.g., spaCy or NLTK) to tokenize the text data and analyze the user's skill set and values. For example, it analyzes the skill set "Programming (Python, Java)" and identifies related job titles.

[1755] Input: User information stored on the server

[1756] Output: Analyzed user's skill set and values

[1757] Step 4:

[1758] The AI ​​agent applies machine learning models using scikit-learn and TensorFlow to suggest optimal career paths and life plans for users, such as jobs like "data scientist" or "software engineer at an edtech company."

[1759] Input: Parsed user's skill set and values

[1760] Output: Suggested career path or life plan

[1761] Step 5:

[1762] The server simulates the user's future life based on the proposed career path and life plan. For example, it predicts future income and lifestyle. The simulation results are displayed as graphs and charts using visualization tools (e.g., Matplotlib and Plotly).

[1763] Input: Proposed career path or life plan

[1764] Output: Graphs and charts of simulation results

[1765] Step 6:

[1766] The server sends the generated graphs and charts to the terminal, which then displays the received graphs and charts to the user. For example, it displays a graph showing changes in income or lifestyle.

[1767] Input: Graphs and charts of simulation results

[1768] Output: Graphs and charts displayed on the terminal

[1769] (Application example 3)

[1770] 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."

[1771] Conventional career planning systems can suggest future possibilities based on a user's past and present career history, skills, and values, but they lack the means to specifically simulate and visualize future income based on the proposed career path. This makes it difficult for users to understand the specific economic impact of the proposed career path, making it difficult for them to make decisions.

[1772] 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 inputting the user's past and present career history, skills, values, etc.; means for inputting the user's image of the future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the proposed career path and visualizing it in a graph. This makes it easier for the user to understand the specific economic impact of the proposed career path, enabling more appropriate decision-making.

[1773] "Means for inputting the user's past and present career history, skills, values, etc." refers to an interface that allows users to input information such as their work history, educational background, specialized knowledge, skills, and values ​​into the system.

[1774] The "means for inputting the user's image of the future" is an interface that allows the user to input information such as their future goals and desired lifestyle into the system.

[1775] "AI agent that suggests future possibilities that suit the user based on the information entered" is an artificial intelligence system that analyzes the information entered by the user and suggests the optimal career path and life plan.

[1776] "Means to simulate proposed possibilities and visualize life" is a function that simulates the user's future life based on proposed career paths and life plans and displays them in graphs and charts.

[1777] "Means for simulating future income based on a proposed career path and visualizing it in a graph" is a function for predicting future income based on a proposed career path and displaying the results in a graph.

[1778] A system for carrying out this invention includes means for inputting a user's past and present career history, skills, values, etc.; means for inputting an image of the user's future; an AI agent that suggests future possibilities that suit the user based on the input information; means for simulating the suggested possibilities and visualizing the user's life; and means for simulating future income based on the suggested career path and visualizing it in a graph.

[1779] 1. Program Generation

[1780] The program for this system can be implemented using Python. Specifically, we will build an AI agent to analyze user input data and propose optimal career paths. Furthermore, we will add a function to simulate future income based on the proposed career paths and visualize the results in a graph.

[1781] 2. Explanation of program processing

[1782] The server receives and analyzes information entered by the user, such as their career history, skills, and values. This analysis is performed using natural language processing and machine learning algorithms. Specific software used is the Python libraries Numpy and Pandas, and the machine learning library Scikit-learn.

[1783] Based on the analysis results, the AI ​​agent will suggest the most suitable career path for the user. This suggestion is based on the user's skill set and values. For example, if a user has the skills of "programming" and "data analysis" and inputs "innovation" and "stability" as their values, the AI ​​agent will suggest "software engineer."

[1784] Next, future earnings are simulated based on the proposed career path. The simulation uses da...

Claims

1. A means for users to input their past and current careers, skills, values, etc. A means for inputting a future image of the user; An AI agent that proposes future possibilities suitable for the user based on the input information of the user; A means for simulating possibilities proposed by the AI ​​agent and visualizing the user's life; A means for a generative AI model to generate a response based on the user's life visualized by the means for visualizing the life, and to return the response to the user; A system including:

2. The system of claim 1 , wherein the AI ​​agent suggests job types, companies, and targeted next steps as future possibilities suitable for the user.

3. The system of claim 1 , wherein the life visualization means creates a life plan for the user based on the proposed possibilities.

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