System

Abstract

A system is provided.SOLUTION: A system comprising: means for providing an interface for an entrepreneur to input an idea; means for analyzing the inputted idea using a generative AI model and generating relevant information and improvement proposals; means for displaying the generated information and improvement proposals to the entrepreneur; means for providing an interface for selecting and inputting items of a business plan; and means for providing an interface for the entrepreneur to confirm and correct the automatically generated draft.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] Entrepreneurs often spend a lot of time and effort in the process of concretizing their ideas and formulating a business plan. It can also be difficult to match them with the right technologists and creators, and fundraising requires designing an effective crowdfunding campaign and smooth communication with investors. While these elements are important for a startup's success, each presents its own challenges and can be a barrier, especially for inexperienced entrepreneurs. As a result, there has been no advanced system that efficiently supports the entire process of concretizing ideas, formulating a business plan, matching with technologists and creators, and fundraising. [Means for solving the problem]

[0005] The present invention provides a system that provides an interface for entrepreneurs to input and materialize their ideas, analyzes the ideas using a generative AI model, and generates related information and improvement proposals. It also provides an interface for selecting and inputting business plan items and has a function for automatically generating a draft business plan based on the input data. It also includes a function for extracting the necessary skill sets from the business plan, matching them with the profiles of engineers and creators on the platform, and generating and presenting a list of optimal matching candidates. It also provides an interface for inputting details of a crowdfunding campaign and has a function for proposing effective campaign content and marketing strategies using a generative AI model. This realizes a system that efficiently materializes entrepreneurs' ideas, develops business plans, matches engineers and creators, and raises funds.

[0006] An "entrepreneur" is someone who wants to start a new business.

[0007] An "idea" refers to a new idea or concept that an entrepreneur comes up with.

[0008] A "generative AI model" refers to an artificial intelligence model that analyzes information and generates text or suggestions based on a specified task.

[0009] A "business plan" is a document that contains the entrepreneur's business goals, strategies, and execution plans.

[0010] "Interface" refers to the screen and input methods that users use to interact with a system.

[0011] "Matching" refers to the process of matching projects with the right engineers and creators who have the necessary skill sets.

[0012] A "crowdfunding campaign" refers to an activity or project that raises funds from a large number of people via the Internet.

[0013] A "marketing strategy" refers to a policy or plan for effectively delivering products or services to consumers.

[0014] A "profile" refers to information that describes an individual's career history and skills.

[0015] A "database" refers to a system that allows for the centralized management, search, and use of large amounts of data.

[0016] A "skill set" refers to the set of abilities or techniques required to perform a particular project or task.

[0017] A "draft" refers to a rough draft or rough idea that is created before a formal document is released. [Brief explanation of the drawings]

[0018] [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. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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, a 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), and an APU (Accelerated Processing Unit).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. 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."

[0039] 1. System Overview

[0040] This is a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support fundraising. This system is implemented via a network that includes a server and user terminals.

[0041] 2. Idea input and analysis

[0042] The user (entrepreneur) enters their idea using an interface on their device. This interface includes a text input box. The entered text is sent to the server and analyzed by a generative AI model. The server extracts keywords and important topics from the idea and generates related information and improvement suggestions based on that information. The generated information is then sent to the device for the user to review and edit.

[0043] Examples:

[0044] The user enters "AI-based health management app."

[0045] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[0046] 3. Automatic generation of business plans

[0047] Users use the interface to select and input details of their business plan (market size, competitive analysis, SWOT analysis, etc.). This data is sent to the server, where it is analyzed by a generative AI model. The server then automatically generates a draft business plan based on the input data. This draft is then displayed on the device for the user to review and modify.

[0048] Examples:

[0049] Users input data on market size and competitive analysis.

[0050] The server generates a draft business plan based on this information and presents it to the user.

[0051] 4. Matching engineers and creators

[0052] The server extracts the required skill sets from the automatically generated business plan. The extracted skill sets are matched with the profiles of engineers and creators on the platform. The server generates a list of optimal candidates and presents them to the user. The user reviews and selects from the list of candidates, and communication begins.

[0053] Examples:

[0054] The server extracts skills such as "data analysis" and "mobile app development."

[0055] The server matches the profiles of engineers and creators who possess these skills and provides the list to the user.

[0056] The user selects the appropriate candidate from the list and sends a message.

[0057] 5. Crowdfunding and Investor Communication

[0058] Users enter details of their crowdfunding campaign into the interface, including the title, description, target amount, and duration. The server uses a generative AI model to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server then recommends suitable projects based on the investor's areas of interest and investment history, providing an interface for smooth communication between users and investors.

[0059] Examples:

[0060] The user enters the crowdfunding details and submits.

[0061] The server uses the generative AI model to propose effective campaign content and present it to the user.

[0062] The user edits and publishes the campaign page based on the proposal.

[0063] Investors can review the recommended projects and submit questions.

[0064] The server uses generative AI models to generate fast and relevant responses and send them to investors.

[0065] As a result, the present invention can efficiently support a series of processes from realizing an entrepreneur's idea to raising funds.

[0066] The processing flow will be explained below.

[0067] Idea input and analysis

[0068] Step 1:

[0069] The terminal (user) enters an idea in the text box and clicks the send button.

[0070] Step 2:

[0071] The server receives the input text data and sends it to a natural language processing (NLP) engine.

[0072] Step 3:

[0073] The server uses an NLP engine to break down input ideas into keywords and key topics.

[0074] Step 4:

[0075] The server generates relevant information and improvement suggestions based on the analyzed keywords and topics.

[0076] Step 5:

[0077] The server transmits the generated information and improvement suggestions to the user's terminal.

[0078] Step 6:

[0079] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[0080] Automatic generation of business plans

[0081] Step 1:

[0082] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[0083] Step 2:

[0084] The server receives the details and data entered and sends them to the generative AI model.

[0085] Step 3:

[0086] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[0087] Step 4:

[0088] The server transmits the generated draft business plan to the user's terminal.

[0089] Step 5:

[0090] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[0091] Matching engineers and creators

[0092] Step 1:

[0093] The server extracts the required skill sets from the automatically generated business plan.

[0094] Step 2:

[0095] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[0096] Step 3:

[0097] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[0098] Step 4:

[0099] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[0100] Step 5:

[0101] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[0102] Step 6:

[0103] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0104] Crowdfunding and communication with investors

[0105] Step 1:

[0106] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[0107] Step 2:

[0108] The server receives the entered campaign details and sends them to the generative AI model.

[0109] Step 3:

[0110] The server uses generative AI models to suggest effective campaign content and marketing strategies.

[0111] Step 4:

[0112] The server transmits the proposed campaign content to the user's terminal.

[0113] Step 5:

[0114] The terminal (user) edits and publishes the campaign page based on the proposal content.

[0115] Step 6:

[0116] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[0117] Step 7:

[0118] The terminal (investor) reviews the recommended projects and sends questions.

[0119] Step 8:

[0120] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0121] Step 9:

[0122] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[0123] Example 1

[0124] Next, a description will be given of 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."

[0125] The process of entrepreneurs concretizing new business ideas, formulating business plans, matching with engineers and creators, and finally raising funds requires a lot of time and expertise. For this reason, entrepreneurs are seeking support systems to efficiently move through these processes. However, many current systems only support each process individually, and there is a lack of systems that consistently support the entire process. To solve this problem, a system is needed that provides comprehensive support from concretizing ideas to raising funds.

[0126] 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.

[0127] In this invention, the server includes a means for providing a user interface for entrepreneurs to input ideas, a means for analyzing the input idea using a generative AI model and generating related information and improvement suggestions, a means for displaying the generated information and improvement suggestions to the entrepreneur, a means for providing a user interface for selecting and inputting business plan items, a means for automatically generating a draft business plan based on the input data, a means for providing a user interface for the entrepreneur to review and modify the automatically generated draft, and a system for extracting necessary skill sets from the business plan, matching the skill sets with the profiles of engineers and creators on the platform to generate a list of matching candidates, providing a user interface for inputting details of the crowdfunding campaign, proposing effective campaign content and marketing strategies using a generative AI model, and creating a campaign page based on the input and proposed content, thereby enabling entrepreneurs to efficiently proceed through the entire process from idea realization to fundraising.

[0128] An "entrepreneur" refers to an individual or organization that has a new business idea and is trying to materialize it and develop it into a business.

[0129] A "user interface" is an interface through which a user interacts with a system, and includes input forms, buttons, and other operational elements.

[0130] A "generative AI model" is an artificial intelligence model that generates and analyzes text based on given data, and examples include models that perform natural language processing.

[0131] "Related information" refers to supplementary information or references provided by the generative AI model based on ideas and data input by the user.

[0132] "Improvement suggestions" refers to the generative AI model analyzing input data and providing suggestions and advice to improve an idea or plan.

[0133] A business plan is a document that details the direction and strategy of a business, and includes items such as market size, competitive analysis, and SWOT analysis.

[0134] "Draft" refers to an early version or preliminary document of a business plan automatically generated by a generative AI model.

[0135] A "skill set" refers to the skills, knowledge, and experience required to accomplish a specific task or project.

[0136] "Technologist" refers to an individual or organization with specialized knowledge or skills in a particular technical field.

[0137] "Creator" refers to a professional individual or organization that produces creative works or content.

[0138] "Profile" refers to information that describes the background, skills, and achievements of an engineer or creator.

[0139] The "matching candidate list" refers to a list of the most suitable engineers and creators selected by the generative AI model based on skill sets.

[0140] "Crowdfunding" refers to a method of raising funds from an unspecified number of supporters via the Internet.

[0141] "Campaign page" refers to a webpage that provides detailed information about crowdfunding and introduces the project.

[0142] This invention relates to a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support them in raising funds. This system is realized via a network that includes a server and user terminals.

[0143] System Configuration

[0144] 1. User idea input

[0145] Users access the system using a device (e.g., a PC or tablet). They input their ideas through the interface and click the "Submit" button. This input is sent to the server as an HTTP request.

[0146] Examples:

[0147] The user enters "AI-based health management app."

[0148] 2. Receiving and analyzing ideas

[0149] The server receives ideas submitted by users and analyzes them with a generative AI model (e.g., GPT-4). The model extracts keywords and important topics from the ideas and generates related information and improvement suggestions.

[0150] Examples:

[0151] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[0152] 3. Sending and displaying analysis results

[0153] The server converts the generated analysis results into JSON format and sends it to the user's device as an HTTP response. The user's device receives this response and displays the analysis results on its interface. The user can check the displayed analysis results and modify the text as necessary.

[0154] 4. Enter details of your business plan

[0155] Users input details of their business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) into the interface, and this data is sent to a server where a generative AI model analyzes it.

[0156] Examples:

[0157] Users input data on market size and competitive analysis.

[0158] 5. Automatic generation of business plans

[0159] The server automatically generates a draft business plan using a generative AI model based on the input data. This draft is displayed on the user's device, where the user can review and revise it.

[0160] 6. Matching engineers and creators

[0161] The server extracts the required skill sets from the business plan and matches them with the profiles of engineers and creators on the platform. A list of the best candidates is generated and presented to the user. The user selects the appropriate candidate from the list and communication begins.

[0162] Examples:

[0163] The server extracts skills such as "data analysis" and "mobile app development," matches the profiles of engineers and creators who possess these skills, and provides the list to the user.

[0164] The user selects the appropriate candidate from the list and sends a message.

[0165] 7. Enter your crowdfunding campaign details

[0166] Users input details of their crowdfunding campaign (e.g., title, description, target amount, duration, etc.) into the interface, and the server provides this information to a generative AI model that then suggests effective campaign content and marketing strategies.

[0167] Examples:

[0168] Users enter and submit their details to launch a crowdfunding campaign aimed at "developing a new AI health management app."

[0169] The server uses a generative AI model to propose effective campaign content, and users edit and publish campaign pages based on that content.

[0170] 8. Support for communication with investors

[0171] When an investor reviews a recommended project and submits a question, the server uses a generative AI model to analyze the question and generate a quick and appropriate answer, which is then sent to the investor for smooth communication.

[0172] This system allows entrepreneurs to efficiently go through the entire process from concretizing their ideas to raising funds.

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] Step 1:

[0175] The user enters an idea into the device's interface and clicks the "Submit" button, which causes the device to send the user-entered text as an HTTP request to the server.

[0176] Input: User's idea text.

[0177] Output: HTTP request to the server.

[0178] Specific operation: The user writes "Health management app using AI" in the text input box and clicks the "Send" button.

[0179] Step 2:

[0180] The server receives an HTTP request sent by a user, extracts text data from the request body, and provides this text data as input to a generative AI model to begin analysis.

[0181] Input: Idea text included in the request from the device.

[0182] Output: Analysis results (keywords, related information, improvement suggestions).

[0183] Specific operation: The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions.

[0184] Step 3:

[0185] The server converts the generated analysis results into JSON format and sends them as an HTTP response to the user's device. The user's device receives this response and displays the analysis results on its interface.

[0186] Input: Parsed result by the server.

[0187] Output: Analysis results displayed on the user's terminal.

[0188] Specific operation: The user terminal displays the analysis results on a graphical user interface (GUI) so that the user can check and correct them.

[0189] Step 4:

[0190] The user enters the details of the business plan (market size, competitive analysis, SWOT analysis, etc.) into the interface on the terminal and clicks the "Submit" button. This operation causes the terminal to send the detailed data to the server as an HTTP request.

[0191] Input: Detailed information about the business plan provided by the user.

[0192] Output: HTTP request to the server.

[0193] Specific operation: The user inputs "market size," "competitive analysis," "SWOT analysis," etc.

[0194] Step 5:

[0195] The server receives the detailed item data submitted by the user and provides this data as input to the generative AI model, which then automatically generates a draft business plan and returns it to the server.

[0196] Input: Business plan details included in the request from the device.

[0197] Output: A generated draft business plan.

[0198] Specific operation: The server automatically generates a business plan draft and sends the data converted into JSON format to the user's terminal.

[0199] Step 6:

[0200] The user terminal displays the received draft of the business plan on the interface, and the user can check the displayed content and make corrections as necessary.

[0201] Input: A draft business plan sent from the server.

[0202] Output: User-confirmed and revised business plan.

[0203] What happens: The user reviews and, if necessary, corrects the draft.

[0204] Step 7:

[0205] The server extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform, generating a list of the most suitable candidates and sending it to the user's device.

[0206] Input: Thurber's draft business plan.

[0207] Output: A list of the best candidates.

[0208] Specific operation: The server extracts required skill sets such as "data analysis" and "mobile app development" and generates a list of matching candidates.

[0209] Step 8:

[0210] The user checks the candidate list on the interface and selects the appropriate candidate. After selecting, the user enters a message and clicks the "Send" button. This message is sent to the server and distributed to the appropriate candidate.

[0211] Input: User selection result and message.

[0212] Output: Message delivery to candidates.

[0213] Specific behavior: The user selects a technician from a list of candidates and sends a message.

[0214] Step 9:

[0215] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) into the interface and clicks the "Submit" button, which causes the device to send the details to the server.

[0216] Input: Crowdfunding details entered by the user.

[0217] Output: HTTP request to the server.

[0218] Specific behavior: User enters details for "Developing a new AI health management app."

[0219] Step 10:

[0220] The server provides the received detailed data to the generative AI model, which then proposes effective campaign content and marketing strategies. These proposals are then sent to the user, who then edits and publishes the campaign page based on the proposals.

[0221] Input: Crowdfunding details data from the server.

[0222] Output: Proposal of effective campaign content and marketing strategy.

[0223] Specific operation: The server analyzes using the generative AI model and sends campaign content suggestions to the user.

[0224] Step 11:

[0225] When an investor reviews a recommended project and submits a question, the server analyzes the question using a generative AI model to generate a quick and appropriate answer, which is then sent to the investor, ensuring smooth communication.

[0226] Input: Investor questions.

[0227] Output: The answer from the generative AI model.

[0228] Specific operation: The server analyzes the investor's question, generates an appropriate answer, and sends it.

[0229] (Application example 1)

[0230] Next, a description will be given of Application 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."

[0231] It is necessary to smoothly support the entire process of entrepreneurs' efforts to materialize new ideas, efficiently formulate business plans, match them with appropriate engineers and creators, and effectively raise funds. These processes also require the provision of relevant information and optimization of marketing strategies through appropriate keyword extraction and prompt sentence generation.

[0232] 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.

[0233] In this invention, the server includes: means for providing an interface for entrepreneurs to input ideas; means for analyzing the input ideas using a generative AI model and generating related information and improvement proposals; means for displaying the generated information and improvement proposals to the entrepreneur; means for providing an interface for selecting and inputting business plan items; means for automatically generating a business plan draft based on the input data; means for providing an interface for the entrepreneur to review and modify the automatically generated draft; means for summarizing the idea and extracting keywords using an AI model; and means for generating additional information and proposals using the suggested keywords as prompts. This enables entrepreneurs to efficiently materialize their ideas, develop business plans, match with appropriate engineers and creators, and effectively raise funds.

[0234] An "interface" is a screen or operating means used by a user to input or receive information.

[0235] A "generative AI model" is an algorithm that uses natural language processing and machine learning to analyze text data and generate relevant information and suggestions.

[0236] "Analysis" is the process of analyzing input data and extracting its contents and related information.

[0237] "Related information" is additional data or knowledge related to the ideas or data entered.

[0238] "Improvement proposals" are specific advice or suggestions for further improvement based on the ideas and data entered.

[0239] A business plan is a written plan that includes business goals, strategies, market and competitive analysis, financial forecasts, etc.

[0240] "Selection" is the act of choosing the appropriate option from multiple options.

[0241] "Input" is the act of sending information or data to a system.

[0242] "Auto-generation" is the process by which a system automatically generates a specific form of output based on user input data.

[0243] A "draft" is an early document or plan developed toward a final version.

[0244] "Keywords" are important words or phrases in the text data.

[0245] A "prompt sentence" is a guided sentence that generates a response to text or a question entered by the user.

[0246] "Matching" is the process of finding the best match based on certain criteria.

[0247] "Crowdfunding" is a method of raising small amounts of money from a large number of people via the Internet.

[0248] A "marketing strategy" is a plan or method for appropriately delivering products or services to the market and promoting sales.

[0249] This invention is a system that helps entrepreneurs materialize their ideas, develop business plans, match them with engineers and creators, and ultimately support them in raising funds. This system is realized through an application installed on a smartphone or head-mounted display (HMD).

[0250] The server first provides an interface for users to input their ideas. When users input their ideas using a text input box on their device, the text is sent to the server. The server then uses a generative AI model (e.g., Hugging Face's BART model) to analyze the input ideas and extract summaries and keywords. It then uses an AI model (e.g., OpenAI's GPT-3) to generate related information and improvement suggestions.

[0251] The generated information and suggestions are sent to the user's device, where the user can review and edit them. For example, if a user types in "health management app using AI," the server will extract keywords such as "AI," "health management," and "app" and provide the user with related information and suggestions.

[0252] The server then provides an interface for the user to select and input details of the business plan (market size, competitive analysis, etc.). Once the user has entered these items, the data is sent to the server, which automatically generates a draft business plan using a generative AI model. The generated draft is displayed on the user's device for review and revision.

[0253] The server then extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform. A list of the most suitable candidates is generated and presented to the user. The user can then review the list and begin communicating with the appropriate candidates.

[0254] To raise funds, the server provides an interface for users to enter details of their crowdfunding campaign. Once users enter the title, description, target amount, etc., the generative AI model is used to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server also recommends appropriate projects based on investors' areas of interest and investment history, providing an interface for smooth communication between users and investors.

[0255] Examples of specific prompts include:

[0256] Idea analysis prompt:

[0257] Analyze and provide keywords for the following idea:

[0258] Health management app

[0259] ·Automatically generate business plan prompt:

[0260] Create a business plan draft for a startup based on the following details:

[0261] Idea Summary: Development of a health management app using AI

[0262] Market Size: $100 million

[0263] Competitor Analysis: Multiple Existing Applications

[0264] In this way, users can efficiently materialize their ideas, develop business plans, match with suitable engineers and creators, and effectively raise funds.

[0265] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0266] Step 1:

[0267] The user inputs their idea using a smartphone or HMD. The input text is sent from the device to the server. At this time, the user enters a specific idea, such as "a health management app using AI," into the input box.

[0268] Step 2:

[0269] The server passes the received text data to a generative AI model (Hugging Face's BART model) to analyze the idea. The server extracts a summary of the idea and keywords (e.g., "AI," "health management," "app") and generates related information. The generated information and suggestions are sent to the device.

[0270] Step 3:

[0271] The user checks the analysis results and suggestions displayed on the device. They make any necessary changes or corrections and resubmit the new content. For example, the user might make a correction such as "Add a function to measure the effectiveness of AI health management."

[0272] Step 4:

[0273] The server provides an interface for selecting and inputting items in the business plan based on the content resubmitted by the user. The user inputs detailed data such as market size and competitive analysis and transmits it to the server.

[0274] Step 5:

[0275] The server sends the received data to a generative AI model (OpenAI's GPT-3) that automatically generates a draft business plan. The draft business plan is generated based on specific input data, such as "market size: $100 million" and "competitive analysis: many existing apps." The generated draft is then sent to the device.

[0276] Step 6:

[0277] The user checks the draft business plan on the device and makes any necessary revisions, such as "narrowing the target market to young people aged 20-30." The revised content is then sent back to the server.

[0278] Step 7:

[0279] The server extracts the necessary skill sets from the final business plan and matches them with engineers and creators. It compares the profile information on the platform with the skill sets and generates a list of optimal candidates. The generated candidate list is sent to the device.

[0280] Step 8:

[0281] The user checks the list of candidates displayed on the device and selects the appropriate engineers and creators. Communication with the selected candidates takes place through a dedicated interface.

[0282] Step 9:

[0283] The server provides an interface for the user to enter details of the crowdfunding campaign (title, description, goal amount, etc.), which the user enters and submits to the server.

[0284] Step 10:

[0285] The server passes the received detailed information to the generative AI model, which then proposes effective campaign content and marketing strategies. For example, specific proposals such as "target market should utilize social media and campaign duration should be three months" are generated and sent to the user's device.

[0286] Step 11:

[0287] Users edit and publish crowdfunding campaign pages based on the proposed content, and the server simultaneously recommends suitable projects and generates prompts based on the investor's areas of interest and investment history.

[0288] Step 12:

[0289] Investors review recommended projects and send questions. The server uses a generative AI model to generate quick and appropriate answers and sends them to the investors, ensuring smooth communication between entrepreneurs and investors.

[0290] 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.

[0291] This invention is an entrepreneurship support system that combines an emotion engine and analyzes the user's emotional state to materialize ideas, formulate business plans, match engineers and creators, and optimize crowdfunding. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[0292] Idea input and analysis

[0293] 1. Enter your idea

[0294] Users input their ideas using the interface on their devices. The input field has a text box where users can freely describe their ideas.

[0295] 2. Sentiment Analysis and Recommendation Generation

[0296] The server receives the input idea text and sends it to the emotion engine.

[0297] The emotion engine uses natural language processing (NLP) to analyze the linguistic expressions contained in ideas and recognize the user's emotional state.

[0298] The server uses a generative AI model to analyze the emotional information obtained from the emotion engine and the keywords and important topics of the ideas.

[0299] The server generates relevant information and improvement suggestions, dynamically adjusting the content according to the user's emotional state.

[0300] Improvement suggestions based on the generated information and emotions are displayed on the user's device, and the user can confirm and correct them.

[0301] Automatic generation of business plans and emotional personalization

[0302] 1. Enter business plan items

[0303] The user uses the interface to select business plan details (market size, competitive analysis, SWOT analysis, etc.) and enter the required information.

[0304] 2. Automatic draft generation

[0305] The server receives the details entered and sends them to the generative AI model.

[0306] The server uses a generative AI model to automatically generate a draft business plan and personalizes suggested revisions based on the user's emotional state.

[0307] The automatically generated draft and suggested revisions are displayed on the user's terminal.

[0308] Matching engineers and creators

[0309] 1. Skill set extraction and matching

[0310] The server extracts the required skill sets from the automatically generated business plan and searches the platform's database of engineer and creator profiles.

[0311] A list of candidates matching the skill set is generated and sent to the user's terminal.

[0312] 2. Initiating communication

[0313] The user reviews the list of candidates presented and selects the appropriate engineers and creators.

[0314] Users send messages to selected engineers and creators, requesting their cooperation.

[0315] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0316] Crowdfunding and communication with investors

[0317] 1. Enter campaign details and submit proposal

[0318] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) and submits it.

[0319] The server receives the entered campaign details and sends them to the generative AI model.

[0320] Using generative AI models, it suggests effective campaign content and marketing strategies, adjusting them according to the user's emotional state.

[0321] Based on the proposal, the user edits and publishes the campaign page.

[0322] 2. Investor Recommendations and Q&A

[0323] The server recommends suitable crowdfunding projects based on investors' areas of interest and past investment history.

[0324] Investors can review the recommended projects and submit questions.

[0325] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0326] The generated answers are retransmitted to the user's terminal and provided to the investor.

[0327] Examples:

[0328] When a user inputs an idea for an AI-based health management app, the server analyzes the text using an emotion engine and recognizes the user's emotional state, such as excitement or anxiety. Based on that emotional state, the generative AI model generates and provides the user with suggestions for improvement, particularly those with positive directions or encouraging messages. Through this process, the user can feel more at ease as they work to bring their idea to fruition.

[0329] The processing flow will be explained below.

[0330] Idea input and analysis

[0331] Step 1:

[0332] The terminal (user) enters an idea in the text box and clicks the send button.

[0333] Step 2:

[0334] The server receives the input text data and sends it to the emotion engine.

[0335] Step 3:

[0336] The emotion engine analyzes the linguistic expressions in the text and recognizes the user's emotional state (e.g., excitement, joy, anxiety, sadness, etc.).

[0337] Step 4:

[0338] The server sends the emotional information obtained from the emotion engine, along with the idea keywords and important topics, to the generative AI model.

[0339] Step 5:

[0340] The generative AI model generates relevant information and improvement suggestions based on emotional information and keywords, dynamically adjusting the suggestions according to the user's emotional state.

[0341] Step 6:

[0342] The server transmits improvement suggestions based on the generated information and emotions to the user's terminal.

[0343] Step 7:

[0344] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[0345] Automatic generation of business plans and emotional personalization

[0346] Step 1:

[0347] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[0348] Step 2:

[0349] The server receives the details and data entered and sends them to the generative AI model.

[0350] Step 3:

[0351] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[0352] Step 4:

[0353] The server takes into account the user's emotional state and personalizes the suggested corrections needed, for example suggesting more detailed explanations for a user in an anxious state.

[0354] Step 5:

[0355] The server transmits the generated business plan draft and proposed revisions to the user's terminal.

[0356] Step 6:

[0357] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[0358] Matching engineers and creators

[0359] Step 1:

[0360] The server extracts the required skill sets from the automatically generated business plan.

[0361] Step 2:

[0362] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[0363] Step 3:

[0364] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[0365] Step 4:

[0366] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[0367] Step 5:

[0368] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[0369] Step 6:

[0370] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0371] Crowdfunding and communication with investors

[0372] Step 1:

[0373] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[0374] Step 2:

[0375] The server receives the entered campaign details and sends them to the generative AI model.

[0376] Step 3:

[0377] The server uses a generative AI model to propose effective campaign content and marketing strategies, taking into account the user's emotional state.

[0378] Step 4:

[0379] The server transmits the proposed campaign content to the user's terminal.

[0380] Step 5:

[0381] The terminal (user) edits and publishes the campaign page based on the proposal content.

[0382] Step 6:

[0383] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[0384] Step 7:

[0385] The terminal (investor) reviews the recommended projects and sends questions if necessary.

[0386] Step 8:

[0387] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0388] Step 9:

[0389] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[0390] Example 2

[0391] Next, a description will be given of 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."

[0392] Conventional entrepreneurship support systems provide improvement suggestions and business plans without considering the user's emotional state, making it difficult for users to receive appropriate feedback. Furthermore, it is difficult to address individual users' emotional states and specific needs when matching with engineers and creators or optimizing crowdfunding. Therefore, there is a need for improved user experience and more effective and personalized support.

[0393] 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. In this invention, the server includes: means for providing an interface for users to input ideas; means for analyzing the input ideas using a generative AI model and generating improvement suggestions based on related information and sentiment analysis; means for displaying the generated information and improvement suggestions to the user; means for providing an interface for selecting and inputting items of a business plan; means for automatically generating a draft of a business plan based on the input data; means for providing an interface for the user to check and modify the automatically generated draft; means for extracting required skill sets from the business plan; means for matching the profiles of engineers and creators on the platform with the skill sets and generating a list of matching candidates; means for presenting the list of matching candidates to the user; means for managing communication with the engineers and creators selected by the user and storing records; means for providing an interface for inputting details of the crowdfunding campaign; means for proposing effective campaign content and marketing strategies using a generative AI model; means for creating a campaign page based on the input and proposed content; means for recommending appropriate projects based on the investor's areas of interest and past investment history; and means for quickly and appropriately generating answers to questions from investors. This will enable personalized support based on the user's emotional state, effective matching with engineers and creators, and optimization of crowdfunding.

[0394] A "user" is a person who uses the entrepreneurial support system to input ideas and develop business plans.

[0395] An "interface" is a screen or operating means through which a user inputs data into a system.

[0396] A "generative AI model" is an artificial intelligence model that analyzes data entered by the user and generates improvement suggestions and information.

[0397] "Emotion analysis" is a technology that recognizes and analyzes the emotional state of a user from the text they enter.

[0398] "Improvement suggestions" are specific advice for improvements or corrections provided by the generative AI model in response to input ideas or data.

[0399] A business plan is a strategy or plan for starting a business or promoting a new venture, and includes market size, competitive analysis, and SWOT analysis.

[0400] A "draft" is a draft of an early stage business plan.

[0401] A "skill set" is a list of skills and abilities required for a particular task or project.

[0402] An "engineer" is a specialist who has the specialized knowledge and skills required for a system or project.

[0403] A "creator" is someone with specialized skills in design and content production.

[0404] The "matching candidate list" is a list of suitable engineers and creators selected based on their skill sets.

[0405] "Crowdfunding" is a method of raising funds from a large number of investors via the Internet.

[0406] A "campaign page" is a webpage created for crowdfunding that lists campaign details, target amount, and description.

[0407] "Investor" means a person who provides funds to a crowdfunding campaign.

[0408] This invention is an entrepreneurship support system that combines an emotion engine and realizes the realization of users' ideas, business plan formulation, matching of engineers and creators, and optimization of crowdfunding via a network. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[0409] Idea input and analysis

[0410] A user inputs an idea using an interface on the user device. For example, they can enter "Idea for a health management app using AI" in a text box. The server then receives the input idea text and sends it to an emotion engine. The emotion engine (e.g., a specific platform using natural language processing) analyzes the linguistic expression and recognizes the user's emotional state as "excited" or "anxious," etc.

[0411] The server then uses a generative AI model (e.g., OpenAI GPT-4) to analyze the emotional information and keywords and important topics of the ideas, generating relevant information and improvement suggestions. The generated information and suggestions are dynamically adjusted according to the user's emotional state. Finally, this information is displayed on the user's device, where the user can review and modify it.

[0412] Automatic generation of business plans and emotional personalization

[0413] The user uses the interface to input details of the business plan, such as market size, competitive analysis, and SWOT analysis. The server receives these details and sends them to the generative AI model, which then automatically generates a draft of the business plan and personalizes suggested revisions based on the user's emotional state. The proposal and draft are then displayed on the user's device for review and revision.

[0414] Matching engineers and creators

[0415] The server extracts the required skill sets from the automatically generated business plan. It then searches the platform's database of engineer and creator profiles to generate a list of candidates that match the skill sets. This list is sent to the user's device, where the user reviews the presented list of candidates and selects the appropriate engineer or creator. After selection, the user sends a message requesting cooperation. The server manages message sending and receiving in real time and stores the necessary records in a database.

[0416] Crowdfunding and communication with investors

[0417] The user inputs details of their crowdfunding campaign (e.g., title, description, target amount, and duration). The server then receives the campaign details and sends them to a generative AI model. The generative AI model then suggests effective campaign content and marketing strategies, adjusting the content based on the user's emotional state. The user can then create and publish a campaign page based on the suggested content.

[0418] In addition, the server recommends suitable projects based on the investor's areas of interest and past investment history, and the investor can review the recommended projects. If the investor has a question, the server sends it to the generative AI model to generate an appropriate answer. The generated answer is provided to the investor and also sent to the user's device.

[0419] Specific examples

[0420] As a specific example, if a user "enters an idea for an AI-based health management app," the server analyzes the text using an emotion engine and recognizes that the user's emotional state is "excited." Based on that emotional state, the generative AI model generates and provides suggestions to the user, including positive improvement suggestions and encouraging messages. Through this process, the user can feel more at ease and move forward with concretizing their idea.

[0421] keyword

[0422] Generative AI model, prompt sentence

[0423] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0424] Step 1:

[0425] The user inputs their idea using the interface on their device. For example, they might type "Idea for a health management app using AI" into the text box. After completing the input, they click the "Send" button. This operation sends the input text data to the server.

[0426] Input: Idea text entered by the user (e.g., "Idea for a health management app using AI")

[0427] Output: The input text data is sent to the server.

[0428] Step 2:

[0429] The server receives the idea text sent by the user. It prepares the received text data for sending to the emotion engine. Specifically, it converts the text data into a format that can be analyzed by the emotion engine.

[0430] Input: Idea text submitted by user

[0431] Output: Text data converted into a format that can be parsed by the emotion engine

[0432] Step 3:

[0433] The emotion engine analyzes the text data received from the server and recognizes the user's emotional state. The emotion engine uses natural language processing to extract emotional states (e.g., "excitement" or "anxiety") from linguistic expressions and keywords in the text.

[0434] Input: Text data converted into a format that can be parsed by the emotion engine

[0435] Output: User's emotional state (e.g., "excited," "anxious")

[0436] Step 4:

[0437] The server creates prompts for the generative AI model based on the emotional information obtained from the emotion engine. These prompts include keywords and important topics for the idea. The server then sends the prompts to the generative AI model.

[0438] Input: Emotional information and idea text

[0439] Output: The prompt to send to the generative AI model

[0440] Step 5:

[0441] The generative AI model receives the prompt and generates relevant information and improvement suggestions based on the prompt's content. The generative AI model also takes emotional information into account and makes suggestions based on the user's emotional state.

[0442] Input: Prompt sent from the server

[0443] Output: Improvement suggestions based on relevant information and sentiment

[0444] Step 6:

[0445] The server receives suggestions from the generative AI model and sends them to the user's device. The device interface displays improvement suggestions based on the generated information and emotions, allowing the user to confirm and modify them.

[0446] Input: Information and improvement suggestions from the generative AI model

[0447] Output: Display on the user's terminal

[0448] Step 7:

[0449] The user uses the interface to select the details of the business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) and enter the required information. After completing the input, the user clicks the "Submit" button, which sends the input data to the server.

[0450] Input: Business plan details entered by the user

[0451] Output: The input data is sent to the server

[0452] Step 8:

[0453] The server receives the details entered and sends them to a generative AI model, which uses this data as prompts to generate a draft business plan.

[0454] Input: Business plan details entered by the user

[0455] Output: The prompt to send to the generative AI model

[0456] Step 9:

[0457] The generative AI model automatically generates a draft business plan based on the prompts and also makes suggested revisions based on the user's emotional state.

[0458] Input: Prompt sent

[0459] Output: Draft business plan and proposed revisions

[0460] Step 10:

[0461] The server sends the generated draft and revision suggestions to the user's terminal, where the user can review them on the interface and make revisions as necessary.

[0462] Input: Draft and revision suggestions from a generative AI model

[0463] Output: Display on the user's terminal

[0464] Step 11:

[0465] The server extracts the required skill sets from the automatically generated business plan, searches the platform's database of engineer and creator profiles, generates a list of candidates that match the skill sets, and sends it to the user's device.

[0466] Input: Auto-generated business plan data

[0467] Output: List of matching candidates

[0468] Step 12:

[0469] The user reviews the list of candidates and selects the appropriate engineers or creators. They then send a message to the selected engineers or creators requesting their cooperation.

[0470] Input: Presented candidate list

[0471] Output: A message to the selected engineers and creators

[0472] Step 13:

[0473] The server manages the sending and receiving of messages in real time and stores the necessary records in a database, allowing for smooth communication between users and engineers / creators.

[0474] Input: Message from the user

[0475] Output: Real-time transmission and recording

[0476] Step 14:

[0477] The user enters the details of the crowdfunding campaign (e.g., title, description, goal amount, duration, etc.) and submits it. The server receives the campaign details and sends them to the generative AI model.

[0478] Input: Campaign details entered by the user

[0479] Output: The prompt to send to the generative AI model

[0480] Step 15:

[0481] The generative AI model proposes effective campaign content and marketing strategies based on the campaign details and sends them to the user, who then creates and publishes a campaign page based on the proposals.

[0482] Input: Prompt sent

[0483] Output: Effective campaign content and marketing strategies

[0484] Step 16:

[0485] The server recommends suitable projects based on the investor's interests and past investment history, and notifies the investor. The investor can then review the recommended projects and submit inquiries.

[0486] Input: Investor interests and past investment history

[0487] Output: Recommended projects and investor questions

[0488] Step 17:

[0489] The server sends the received questions to a generative AI model that generates a quick and appropriate answer, which is then provided to the investor and sent to the user's device.

[0490] Input: Investor Questions

[0491] Output: Answer from the generative AI model

[0492] (Application example 2)

[0493] Next, a description will be given of Application 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."

[0494] In current factory environments, production processes are not optimized with consideration given to the emotional state of workers. This creates challenges in improving productivity and worker satisfaction, and workers' motivation and mental state are often ignored. This can lead to reduced production efficiency and health risks for workers in the long term. Therefore, there is a need for a system that can analyze workers' emotional state in real time and use that data to suggest tasks and optimize resources.

[0495] 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 means for providing an interface for workers to input their emotional states, means for analyzing the input emotional states using a generative AI model and generating related information and optimization suggestions, means for displaying the generated information and optimization suggestions to the workers, means for generating task suggestions and break suggestions based on the workers' emotions, and means for optimizing resource allocation based on the status of the production process. This enables real-time work suggestions and resource optimization that take into account the emotional states of workers on the production line.

[0496] An "interface" is a connection means through which a user inputs data into a system.

[0497] A "generative AI model" is an artificial intelligence algorithm that performs various analyses and generation based on provided data.

[0498] "Emotional state" refers to the mental and emotional state and feelings of the worker.

[0499] "Analysis" is the process of taking input data, understanding it, and evaluating it.

[0500] "Relevant information" refers to information about workers' conditions and production processes obtained from the analyzed data.

[0501] "Optimization suggestions" are suggestions for improving work efficiency that are generated based on the worker's emotional state and production status.

[0502] "Display" refers to the act of presenting the generated information or proposal content to the user in a visible form.

[0503] "Task proposal" means proposing specific tasks for workers to perform.

[0504] A "rest suggestion" is a suggestion encouraging workers to take a rest.

[0505] "Production process" refers to the entire manufacturing process of a product in a factory and its management system.

[0506] "Resource allocation" refers to the most effective distribution of necessary resources and tasks, taking into account the production process and the emotional state of workers.

[0507] MODE FOR CARRYING OUT THE INVENTION

[0508] This invention relates to a factory robot system that analyzes the emotional state of workers and optimizes the production process based on the results. How this system is implemented will be described below.

[0509] 1. System Configuration

[0510] The system includes an interface for workers to input their emotional state, a generative AI model, an emotion analysis engine, and a factory robot for execution. It collects and analyzes emotional data from workers and provides the functionality to suggest appropriate tasks and breaks based on the results.

[0511] 2. Hardware and Software

[0512] Hardware: Factory robots, wearable devices for workers, user devices (PCs, smartphones, etc.)

[0513] Software: Python programs, natural language processing (NLP) engines, generative AI models (e.g., AI models using the Transformers library)

[0514] 3. Processing Flow

[0515] The server provides an interface that allows workers to input their emotional state via smartphone or PC. The input emotional data is sent to the server and analyzed by the emotion analysis engine. The analyzed emotional state data is further processed by the generative AI model to generate relevant information and optimization suggestions.

[0516] The generated information and suggestions are sent from the server to the worker's device, allowing the worker to receive appropriate tasks and break suggestions based on their emotional state. Furthermore, real-time data from the production process is used to optimize resource allocation, improving overall work efficiency.

[0517] Specific examples

[0518] For example, if a worker types, "I'm feeling a little stressed today," the sentiment analysis engine will interpret this as "NEGATIVE." Based on that emotional state, the generative AI model will generate a suggestion, "Take a short break to refresh yourself," and display it on the worker's device.

[0519] Prompt Sentence Examples

[0520] Below is an example of a prompt sentence to input to the generative AI model.

[0521] "Analyzing the emotional state of workers on a factory production line and extracting important emotional elements."

[0522] This makes it possible to analyze workers' emotional states in real time and, based on that data, optimally allocate resources and suggest tasks. The system aims to contribute to improving worker productivity and satisfaction.

[0523] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0524] Step 1:

[0525] The user inputs their emotional state. Using the interface of a smartphone or PC, the user inputs their emotional state in text format. The input data is a sentence that expresses the user's feelings (e.g., "I'm feeling a little stressed today").

[0526] Step 2:

[0527] The emotion data is sent to the server. The input emotion data is sent to the server via the Internet. The server receives this data and proceeds to the next analysis step.

[0528] Step 3:

[0529] The server analyzes the input data using an emotion engine. The server uses an emotion analysis engine (NLP model) to analyze the input text data and classify the emotional state into categories such as "positive" or "negative." This analysis outputs the type of emotion and its intensity.

[0530] Step 4:

[0531] The generative AI model generates optimization suggestions based on the emotional state. The server inputs the emotional state data obtained from the emotion analysis engine into the generative AI model, which then generates appropriate task and break suggestions based on that data. A specific prompt sentence might be, "Analyze the emotional state of workers on the factory production line and extract important emotional elements." The generated suggestions are obtained as output.

[0532] Step 5:

[0533] The generated suggestions are sent to the user's device. The server then sends the suggestions generated by the generative AI model to the user's device. These suggestions include specific actions (e.g., "Take a short break and refresh yourself").

[0534] Step 6:

[0535] The user checks the suggestions displayed on the device and acts on them. For example, if a suggestion to take a break is displayed, the user can refresh themselves by taking a break.

[0536] Step 7:

[0537] The server optimizes resource allocation in the production process based on real-time data. The server collects real-time data from the factory's production line and calculates the optimal resource allocation based on generative AI models and sentiment analysis data. This is expected to improve production efficiency.

[0538] The above processing steps create a system that analyzes the emotional state of workers in real time and, based on that data, optimally allocates resources and suggests tasks.

[0539] 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.

[0540] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[0541] 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.

[0542] [Second embodiment]

[0543] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0544] 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.

[0545] 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).

[0546] 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.

[0547] 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.

[0548] 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).

[0549] 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.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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.

[0554] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0555] 1. System Overview

[0556] This is a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support fundraising. This system is implemented via a network that includes a server and user terminals.

[0557] 2. Idea input and analysis

[0558] The user (entrepreneur) enters their idea using an interface on their device. This interface includes a text input box. The entered text is sent to the server and analyzed by a generative AI model. The server extracts keywords and important topics from the idea and generates related information and improvement suggestions based on that information. The generated information is then sent to the device for the user to review and edit.

[0559] Examples:

[0560] The user enters "AI-based health management app."

[0561] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[0562] 3. Automatic generation of business plans

[0563] Users use the interface to select and input details of their business plan (market size, competitive analysis, SWOT analysis, etc.). This data is sent to the server, where it is analyzed by a generative AI model. The server then automatically generates a draft business plan based on the input data. This draft is then displayed on the device for the user to review and modify.

[0564] Examples:

[0565] Users input data on market size and competitive analysis.

[0566] The server generates a draft business plan based on this information and presents it to the user.

[0567] 4. Matching engineers and creators

[0568] The server extracts the required skill sets from the automatically generated business plan. The extracted skill sets are matched with the profiles of engineers and creators on the platform. The server generates a list of optimal candidates and presents them to the user. The user reviews and selects from the list of candidates, and communication begins.

[0569] Examples:

[0570] The server extracts skills such as "data analysis" and "mobile app development."

[0571] The server matches the profiles of engineers and creators who possess these skills and provides the list to the user.

[0572] The user selects the appropriate candidate from the list and sends a message.

[0573] 5. Crowdfunding and Investor Communication

[0574] Users enter details of their crowdfunding campaign into the interface, including the title, description, target amount, and duration. The server uses a generative AI model to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server then recommends suitable projects based on the investor's areas of interest and investment history, providing an interface for smooth communication between users and investors.

[0575] Examples:

[0576] The user enters the crowdfunding details and submits.

[0577] The server uses the generative AI model to propose effective campaign content and present it to the user.

[0578] The user edits and publishes the campaign page based on the proposal.

[0579] Investors can review the recommended projects and submit questions.

[0580] The server uses generative AI models to generate fast and relevant responses and send them to investors.

[0581] As a result, the present invention can efficiently support a series of processes from realizing an entrepreneur's idea to raising funds.

[0582] The processing flow will be explained below.

[0583] Idea input and analysis

[0584] Step 1:

[0585] The terminal (user) enters an idea in the text box and clicks the send button.

[0586] Step 2:

[0587] The server receives the input text data and sends it to a natural language processing (NLP) engine.

[0588] Step 3:

[0589] The server uses an NLP engine to break down input ideas into keywords and key topics.

[0590] Step 4:

[0591] The server generates relevant information and improvement suggestions based on the analyzed keywords and topics.

[0592] Step 5:

[0593] The server transmits the generated information and improvement suggestions to the user's terminal.

[0594] Step 6:

[0595] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[0596] Automatic generation of business plans

[0597] Step 1:

[0598] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[0599] Step 2:

[0600] The server receives the details and data entered and sends them to the generative AI model.

[0601] Step 3:

[0602] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[0603] Step 4:

[0604] The server transmits the generated draft business plan to the user's terminal.

[0605] Step 5:

[0606] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[0607] Matching engineers and creators

[0608] Step 1:

[0609] The server extracts the required skill sets from the automatically generated business plan.

[0610] Step 2:

[0611] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[0612] Step 3:

[0613] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[0614] Step 4:

[0615] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[0616] Step 5:

[0617] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[0618] Step 6:

[0619] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0620] Crowdfunding and communication with investors

[0621] Step 1:

[0622] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[0623] Step 2:

[0624] The server receives the entered campaign details and sends them to the generative AI model.

[0625] Step 3:

[0626] The server uses generative AI models to suggest effective campaign content and marketing strategies.

[0627] Step 4:

[0628] The server transmits the proposed campaign content to the user's terminal.

[0629] Step 5:

[0630] The terminal (user) edits and publishes the campaign page based on the proposal content.

[0631] Step 6:

[0632] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[0633] Step 7:

[0634] The terminal (investor) reviews the recommended projects and sends questions.

[0635] Step 8:

[0636] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0637] Step 9:

[0638] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[0639] Example 1

[0640] Next, a description will be given of 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."

[0641] The process of entrepreneurs concretizing new business ideas, formulating business plans, matching with engineers and creators, and finally raising funds requires a lot of time and expertise. For this reason, entrepreneurs are seeking support systems to efficiently move through these processes. However, many current systems only support each process individually, and there is a lack of systems that consistently support the entire process. To solve this problem, a system is needed that provides comprehensive support from concretizing ideas to raising funds.

[0642] 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.

[0643] In this invention, the server includes a means for providing a user interface for entrepreneurs to input ideas, a means for analyzing the input idea using a generative AI model and generating related information and improvement suggestions, a means for displaying the generated information and improvement suggestions to the entrepreneur, a means for providing a user interface for selecting and inputting business plan items, a means for automatically generating a draft business plan based on the input data, a means for providing a user interface for the entrepreneur to review and modify the automatically generated draft, and a system for extracting necessary skill sets from the business plan, matching the skill sets with the profiles of engineers and creators on the platform to generate a list of matching candidates, providing a user interface for inputting details of the crowdfunding campaign, proposing effective campaign content and marketing strategies using a generative AI model, and creating a campaign page based on the input and proposed content, thereby enabling entrepreneurs to efficiently proceed through the entire process from idea realization to fundraising.

[0644] An "entrepreneur" refers to an individual or organization that has a new business idea and is trying to materialize it and develop it into a business.

[0645] A "user interface" is an interface through which a user interacts with a system, and includes input forms, buttons, and other operational elements.

[0646] A "generative AI model" is an artificial intelligence model that generates and analyzes text based on given data, and examples include models that perform natural language processing.

[0647] "Related information" refers to supplementary information or references provided by the generative AI model based on ideas and data input by the user.

[0648] "Improvement suggestions" refers to the generative AI model analyzing input data and providing suggestions and advice to improve an idea or plan.

[0649] A business plan is a document that details the direction and strategy of a business, and includes items such as market size, competitive analysis, and SWOT analysis.

[0650] "Draft" refers to an early version or preliminary document of a business plan automatically generated by a generative AI model.

[0651] A "skill set" refers to the skills, knowledge, and experience required to accomplish a specific task or project.

[0652] "Technologist" refers to an individual or organization with specialized knowledge or skills in a particular technical field.

[0653] "Creator" refers to a professional individual or organization that produces creative works or content.

[0654] "Profile" refers to information that describes the background, skills, and achievements of an engineer or creator.

[0655] The "matching candidate list" refers to a list of the most suitable engineers and creators selected by the generative AI model based on skill sets.

[0656] "Crowdfunding" refers to a method of raising funds from an unspecified number of supporters via the Internet.

[0657] "Campaign page" refers to a webpage that provides detailed information about crowdfunding and introduces the project.

[0658] This invention relates to a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support them in raising funds. This system is realized via a network that includes a server and user terminals.

[0659] System Configuration

[0660] 1. User idea input

[0661] Users access the system using a device (e.g., a PC or tablet). They input their ideas through the interface and click the "Submit" button. This input is sent to the server as an HTTP request.

[0662] Examples:

[0663] The user enters "AI-based health management app."

[0664] 2. Receiving and analyzing ideas

[0665] The server receives ideas submitted by users and analyzes them with a generative AI model (e.g., GPT-4). The model extracts keywords and important topics from the ideas and generates related information and improvement suggestions.

[0666] Examples:

[0667] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[0668] 3. Sending and displaying analysis results

[0669] The server converts the generated analysis results into JSON format and sends it to the user's device as an HTTP response. The user's device receives this response and displays the analysis results on its interface. The user can check the displayed analysis results and modify the text as necessary.

[0670] 4. Enter details of your business plan

[0671] Users input details of their business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) into the interface, and this data is sent to a server where a generative AI model analyzes it.

[0672] Examples:

[0673] Users input data on market size and competitive analysis.

[0674] 5. Automatic generation of business plans

[0675] The server automatically generates a draft business plan using a generative AI model based on the input data. This draft is displayed on the user's device, where the user can review and revise it.

[0676] 6. Matching engineers and creators

[0677] The server extracts the required skill sets from the business plan and matches them with the profiles of engineers and creators on the platform. A list of the best candidates is generated and presented to the user. The user selects the appropriate candidate from the list and communication begins.

[0678] Examples:

[0679] The server extracts skills such as "data analysis" and "mobile app development," matches the profiles of engineers and creators who possess these skills, and provides the list to the user.

[0680] The user selects the appropriate candidate from the list and sends a message.

[0681] 7. Enter your crowdfunding campaign details

[0682] Users input details of their crowdfunding campaign (e.g., title, description, target amount, duration, etc.) into the interface, and the server provides this information to a generative AI model that then suggests effective campaign content and marketing strategies.

[0683] Examples:

[0684] Users enter and submit their details to launch a crowdfunding campaign aimed at "developing a new AI health management app."

[0685] The server uses a generative AI model to propose effective campaign content, and users edit and publish campaign pages based on that content.

[0686] 8. Support for communication with investors

[0687] When an investor reviews a recommended project and submits a question, the server uses a generative AI model to analyze the question and generate a quick and appropriate answer, which is then sent to the investor for smooth communication.

[0688] This system allows entrepreneurs to efficiently go through the entire process from concretizing their ideas to raising funds.

[0689] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0690] Step 1:

[0691] The user enters an idea into the device's interface and clicks the "Submit" button, which causes the device to send the user-entered text as an HTTP request to the server.

[0692] Input: User's idea text.

[0693] Output: HTTP request to the server.

[0694] Specific operation: The user writes "Health management app using AI" in the text input box and clicks the "Send" button.

[0695] Step 2:

[0696] The server receives an HTTP request sent by a user, extracts text data from the request body, and provides this text data as input to a generative AI model to begin analysis.

[0697] Input: Idea text included in the request from the device.

[0698] Output: Analysis results (keywords, related information, improvement suggestions).

[0699] Specific operation: The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions.

[0700] Step 3:

[0701] The server converts the generated analysis results into JSON format and sends them as an HTTP response to the user's device. The user's device receives this response and displays the analysis results on its interface.

[0702] Input: Parsed result by the server.

[0703] Output: Analysis results displayed on the user's terminal.

[0704] Specific operation: The user terminal displays the analysis results on a graphical user interface (GUI) so that the user can check and correct them.

[0705] Step 4:

[0706] The user enters the details of the business plan (market size, competitive analysis, SWOT analysis, etc.) into the interface on the terminal and clicks the "Submit" button. This operation causes the terminal to send the detailed data to the server as an HTTP request.

[0707] Input: Detailed information about the business plan provided by the user.

[0708] Output: HTTP request to the server.

[0709] Specific operation: The user inputs "market size," "competitive analysis," "SWOT analysis," etc.

[0710] Step 5:

[0711] The server receives the detailed item data submitted by the user and provides this data as input to the generative AI model, which then automatically generates a draft business plan and returns it to the server.

[0712] Input: Business plan details included in the request from the device.

[0713] Output: A generated draft business plan.

[0714] Specific operation: The server automatically generates a business plan draft and sends the data converted into JSON format to the user's terminal.

[0715] Step 6:

[0716] The user terminal displays the received draft of the business plan on the interface, and the user can check the displayed content and make corrections as necessary.

[0717] Input: A draft business plan sent from the server.

[0718] Output: User-confirmed and revised business plan.

[0719] What happens: The user reviews and, if necessary, corrects the draft.

[0720] Step 7:

[0721] The server extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform, generating a list of the most suitable candidates and sending it to the user's device.

[0722] Input: Thurber's draft business plan.

[0723] Output: A list of the best candidates.

[0724] Specific operation: The server extracts required skill sets such as "data analysis" and "mobile app development" and generates a list of matching candidates.

[0725] Step 8:

[0726] The user checks the candidate list on the interface and selects the appropriate candidate. After selecting, the user enters a message and clicks the "Send" button. This message is sent to the server and distributed to the appropriate candidate.

[0727] Input: User selection result and message.

[0728] Output: Message delivery to candidates.

[0729] Specific behavior: The user selects a technician from a list of candidates and sends a message.

[0730] Step 9:

[0731] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) into the interface and clicks the "Submit" button, which causes the device to send the details to the server.

[0732] Input: Crowdfunding details entered by the user.

[0733] Output: HTTP request to the server.

[0734] Specific behavior: User enters details for "Developing a new AI health management app."

[0735] Step 10:

[0736] The server provides the received detailed data to the generative AI model, which then proposes effective campaign content and marketing strategies. These proposals are then sent to the user, who then edits and publishes the campaign page based on the proposals.

[0737] Input: Crowdfunding details data from the server.

[0738] Output: Proposal of effective campaign content and marketing strategy.

[0739] Specific operation: The server analyzes using the generative AI model and sends campaign content suggestions to the user.

[0740] Step 11:

[0741] When an investor reviews a recommended project and submits a question, the server analyzes the question using a generative AI model to generate a quick and appropriate answer, which is then sent to the investor, ensuring smooth communication.

[0742] Input: Investor questions.

[0743] Output: The answer from the generative AI model.

[0744] Specific operation: The server analyzes the investor's question, generates an appropriate answer, and sends it.

[0745] (Application example 1)

[0746] Next, a description will be given of Application 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."

[0747] It is necessary to smoothly support the entire process of entrepreneurs' efforts to materialize new ideas, efficiently formulate business plans, match them with appropriate engineers and creators, and effectively raise funds. These processes also require the provision of relevant information and optimization of marketing strategies through appropriate keyword extraction and prompt sentence generation.

[0748] 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.

[0749] In this invention, the server includes: means for providing an interface for entrepreneurs to input ideas; means for analyzing the input ideas using a generative AI model and generating related information and improvement proposals; means for displaying the generated information and improvement proposals to the entrepreneur; means for providing an interface for selecting and inputting business plan items; means for automatically generating a business plan draft based on the input data; means for providing an interface for the entrepreneur to review and modify the automatically generated draft; means for summarizing the idea and extracting keywords using an AI model; and means for generating additional information and proposals using the suggested keywords as prompts. This enables entrepreneurs to efficiently materialize their ideas, develop business plans, match with appropriate engineers and creators, and effectively raise funds.

[0750] An "interface" is a screen or operating means used by a user to input or receive information.

[0751] A "generative AI model" is an algorithm that uses natural language processing and machine learning to analyze text data and generate relevant information and suggestions.

[0752] "Analysis" is the process of analyzing input data and extracting its contents and related information.

[0753] "Related information" is additional data or knowledge related to the ideas or data entered.

[0754] "Improvement proposals" are specific advice or suggestions for further improvement based on the ideas and data entered.

[0755] A business plan is a written plan that includes business goals, strategies, market and competitive analysis, financial forecasts, etc.

[0756] "Selection" is the act of choosing the appropriate option from multiple options.

[0757] "Input" is the act of sending information or data to a system.

[0758] "Auto-generation" is the process by which a system automatically generates a specific form of output based on user input data.

[0759] A "draft" is an early document or plan developed toward a final version.

[0760] "Keywords" are important words or phrases in the text data.

[0761] A "prompt sentence" is a guided sentence that generates a response to text or a question entered by the user.

[0762] "Matching" is the process of finding the best match based on certain criteria.

[0763] "Crowdfunding" is a method of raising small amounts of money from a large number of people via the Internet.

[0764] A "marketing strategy" is a plan or method for appropriately delivering products or services to the market and promoting sales.

[0765] This invention is a system that helps entrepreneurs materialize their ideas, develop business plans, match them with engineers and creators, and ultimately support them in raising funds. This system is realized through an application installed on a smartphone or head-mounted display (HMD).

[0766] The server first provides an interface for users to input their ideas. When users input their ideas using a text input box on their device, the text is sent to the server. The server then uses a generative AI model (e.g., Hugging Face's BART model) to analyze the input ideas and extract summaries and keywords. It then uses an AI model (e.g., OpenAI's GPT-3) to generate related information and improvement suggestions.

[0767] The generated information and suggestions are sent to the user's device, where the user can review and edit them. For example, if a user types in "health management app using AI," the server will extract keywords such as "AI," "health management," and "app" and provide the user with related information and suggestions.

[0768] The server then provides an interface for the user to select and input details of the business plan (market size, competitive analysis, etc.). Once the user has entered these items, the data is sent to the server, which automatically generates a draft business plan using a generative AI model. The generated draft is displayed on the user's device for review and revision.

[0769] The server then extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform. A list of the most suitable candidates is generated and presented to the user. The user can then review the list and begin communicating with the appropriate candidates.

[0770] To raise funds, the server provides an interface for users to enter details of their crowdfunding campaign. Once users enter the title, description, target amount, etc., the generative AI model is used to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server also recommends appropriate projects based on investors' areas of interest and investment history, providing an interface for smooth communication between users and investors.

[0771] Examples of specific prompts include:

[0772] Idea analysis prompt:

[0773] Analyze and provide keywords for the following idea:

[0774] Health management app

[0775] ·Automatically generate business plan prompt:

[0776] Create a business plan draft for a startup based on the following details:

[0777] Idea Summary: Development of a health management app using AI

[0778] Market Size: $100 million

[0779] Competitor Analysis: Multiple Existing Applications

[0780] In this way, users can efficiently materialize their ideas, develop business plans, match with suitable engineers and creators, and effectively raise funds.

[0781] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0782] Step 1:

[0783] The user inputs their idea using a smartphone or HMD. The input text is sent from the device to the server. At this time, the user enters a specific idea, such as "a health management app using AI," into the input box.

[0784] Step 2:

[0785] The server passes the received text data to a generative AI model (Hugging Face's BART model) to analyze the idea. The server extracts a summary of the idea and keywords (e.g., "AI," "health management," "app") and generates related information. The generated information and suggestions are sent to the device.

[0786] Step 3:

[0787] The user checks the analysis results and suggestions displayed on the device. They make any necessary changes or corrections and resubmit the new content. For example, the user might make a correction such as "Add a function to measure the effectiveness of AI health management."

[0788] Step 4:

[0789] The server provides an interface for selecting and inputting items in the business plan based on the content resubmitted by the user. The user inputs detailed data such as market size and competitive analysis and transmits it to the server.

[0790] Step 5:

[0791] The server sends the received data to a generative AI model (OpenAI's GPT-3) that automatically generates a draft business plan. The draft business plan is generated based on specific input data, such as "market size: $100 million" and "competitive analysis: many existing apps." The generated draft is then sent to the device.

[0792] Step 6:

[0793] The user checks the draft business plan on the device and makes any necessary revisions, such as "narrowing the target market to young people aged 20-30." The revised content is then sent back to the server.

[0794] Step 7:

[0795] The server extracts the necessary skill sets from the final business plan and matches them with engineers and creators. It compares the profile information on the platform with the skill sets and generates a list of optimal candidates. The generated candidate list is sent to the device.

[0796] Step 8:

[0797] The user checks the list of candidates displayed on the device and selects the appropriate engineers and creators. Communication with the selected candidates takes place through a dedicated interface.

[0798] Step 9:

[0799] The server provides an interface for the user to enter details of the crowdfunding campaign (title, description, goal amount, etc.), which the user enters and submits to the server.

[0800] Step 10:

[0801] The server passes the received detailed information to the generative AI model, which then proposes effective campaign content and marketing strategies. For example, specific proposals such as "target market should utilize social media and campaign duration should be three months" are generated and sent to the user's device.

[0802] Step 11:

[0803] Users edit and publish crowdfunding campaign pages based on the proposed content, and the server simultaneously recommends suitable projects and generates prompts based on the investor's areas of interest and investment history.

[0804] Step 12:

[0805] Investors review recommended projects and send questions. The server uses a generative AI model to generate quick and appropriate answers and sends them to the investors, ensuring smooth communication between entrepreneurs and investors.

[0806] 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.

[0807] This invention is an entrepreneurship support system that combines an emotion engine and analyzes the user's emotional state to materialize ideas, formulate business plans, match engineers and creators, and optimize crowdfunding. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[0808] Idea input and analysis

[0809] 1. Enter your idea

[0810] Users input their ideas using the interface on their devices. The input field has a text box where users can freely describe their ideas.

[0811] 2. Sentiment Analysis and Recommendation Generation

[0812] The server receives the input idea text and sends it to the emotion engine.

[0813] The emotion engine uses natural language processing (NLP) to analyze the linguistic expressions contained in ideas and recognize the user's emotional state.

[0814] The server uses a generative AI model to analyze the emotional information obtained from the emotion engine and the keywords and important topics of the ideas.

[0815] The server generates relevant information and improvement suggestions, dynamically adjusting the content according to the user's emotional state.

[0816] Improvement suggestions based on the generated information and emotions are displayed on the user's device, and the user can confirm and correct them.

[0817] Automatic generation of business plans and emotional personalization

[0818] 1. Enter business plan items

[0819] The user uses the interface to select business plan details (market size, competitive analysis, SWOT analysis, etc.) and enter the required information.

[0820] 2. Automatic draft generation

[0821] The server receives the details entered and sends them to the generative AI model.

[0822] The server uses a generative AI model to automatically generate a draft business plan and personalizes suggested revisions based on the user's emotional state.

[0823] The automatically generated draft and suggested revisions are displayed on the user's terminal.

[0824] Matching engineers and creators

[0825] 1. Skill set extraction and matching

[0826] The server extracts the required skill sets from the automatically generated business plan and searches the platform's database of engineer and creator profiles.

[0827] A list of candidates matching the skill set is generated and sent to the user's terminal.

[0828] 2. Initiating communication

[0829] The user reviews the list of candidates presented and selects the appropriate engineers and creators.

[0830] Users send messages to selected engineers and creators, requesting their cooperation.

[0831] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0832] Crowdfunding and communication with investors

[0833] 1. Enter campaign details and submit proposal

[0834] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) and submits it.

[0835] The server receives the entered campaign details and sends them to the generative AI model.

[0836] Using generative AI models, it suggests effective campaign content and marketing strategies, adjusting them according to the user's emotional state.

[0837] Based on the proposal, the user edits and publishes the campaign page.

[0838] 2. Investor Recommendations and Q&A

[0839] The server recommends suitable crowdfunding projects based on investors' areas of interest and past investment history.

[0840] Investors can review the recommended projects and submit questions.

[0841] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0842] The generated answers are retransmitted to the user's terminal and provided to the investor.

[0843] Examples:

[0844] When a user inputs an idea for an AI-based health management app, the server analyzes the text using an emotion engine and recognizes the user's emotional state, such as excitement or anxiety. Based on that emotional state, the generative AI model generates and provides the user with suggestions for improvement, particularly those with positive directions or encouraging messages. Through this process, the user can feel more at ease as they work to bring their idea to fruition.

[0845] The processing flow will be explained below.

[0846] Idea input and analysis

[0847] Step 1:

[0848] The terminal (user) enters an idea in the text box and clicks the send button.

[0849] Step 2:

[0850] The server receives the input text data and sends it to the emotion engine.

[0851] Step 3:

[0852] The emotion engine analyzes the linguistic expressions in the text and recognizes the user's emotional state (e.g., excitement, joy, anxiety, sadness, etc.).

[0853] Step 4:

[0854] The server sends the emotional information obtained from the emotion engine, along with the idea keywords and important topics, to the generative AI model.

[0855] Step 5:

[0856] The generative AI model generates relevant information and improvement suggestions based on emotional information and keywords, dynamically adjusting the suggestions according to the user's emotional state.

[0857] Step 6:

[0858] The server transmits improvement suggestions based on the generated information and emotions to the user's terminal.

[0859] Step 7:

[0860] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[0861] Automatic generation of business plans and emotional personalization

[0862] Step 1:

[0863] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[0864] Step 2:

[0865] The server receives the details and data entered and sends them to the generative AI model.

[0866] Step 3:

[0867] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[0868] Step 4:

[0869] The server takes into account the user's emotional state and personalizes the suggested corrections needed, for example suggesting more detailed explanations for a user in an anxious state.

[0870] Step 5:

[0871] The server transmits the generated business plan draft and proposed revisions to the user's terminal.

[0872] Step 6:

[0873] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[0874] Matching engineers and creators

[0875] Step 1:

[0876] The server extracts the required skill sets from the automatically generated business plan.

[0877] Step 2:

[0878] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[0879] Step 3:

[0880] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[0881] Step 4:

[0882] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[0883] Step 5:

[0884] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[0885] Step 6:

[0886] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[0887] Crowdfunding and communication with investors

[0888] Step 1:

[0889] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[0890] Step 2:

[0891] The server receives the entered campaign details and sends them to the generative AI model.

[0892] Step 3:

[0893] The server uses a generative AI model to propose effective campaign content and marketing strategies, taking into account the user's emotional state.

[0894] Step 4:

[0895] The server transmits the proposed campaign content to the user's terminal.

[0896] Step 5:

[0897] The terminal (user) edits and publishes the campaign page based on the proposal content.

[0898] Step 6:

[0899] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[0900] Step 7:

[0901] The terminal (investor) reviews the recommended projects and sends questions if necessary.

[0902] Step 8:

[0903] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[0904] Step 9:

[0905] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[0906] Example 2

[0907] Next, a description will be given of 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."

[0908] Conventional entrepreneurship support systems provide improvement suggestions and business plans without considering the user's emotional state, making it difficult for users to receive appropriate feedback. Furthermore, it is difficult to address individual users' emotional states and specific needs when matching with engineers and creators or optimizing crowdfunding. Therefore, there is a need for improved user experience and more effective and personalized support.

[0909] 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. In this invention, the server includes: means for providing an interface for users to input ideas; means for analyzing the input ideas using a generative AI model and generating improvement suggestions based on related information and sentiment analysis; means for displaying the generated information and improvement suggestions to the user; means for providing an interface for selecting and inputting items of a business plan; means for automatically generating a draft of a business plan based on the input data; means for providing an interface for the user to check and modify the automatically generated draft; means for extracting required skill sets from the business plan; means for matching the profiles of engineers and creators on the platform with the skill sets and generating a list of matching candidates; means for presenting the list of matching candidates to the user; means for managing communication with the engineers and creators selected by the user and storing records; means for providing an interface for inputting details of the crowdfunding campaign; means for proposing effective campaign content and marketing strategies using a generative AI model; means for creating a campaign page based on the input and proposed content; means for recommending appropriate projects based on the investor's areas of interest and past investment history; and means for quickly and appropriately generating answers to questions from investors. This will enable personalized support based on the user's emotional state, effective matching with engineers and creators, and optimization of crowdfunding.

[0910] A "user" is a person who uses the entrepreneurial support system to input ideas and develop business plans.

[0911] An "interface" is a screen or operating means through which a user inputs data into a system.

[0912] A "generative AI model" is an artificial intelligence model that analyzes data entered by the user and generates improvement suggestions and information.

[0913] "Emotion analysis" is a technology that recognizes and analyzes the emotional state of a user from the text they enter.

[0914] "Improvement suggestions" are specific advice for improvements or corrections provided by the generative AI model in response to input ideas or data.

[0915] A business plan is a strategy or plan for starting a business or promoting a new venture, and includes market size, competitive analysis, and SWOT analysis.

[0916] A "draft" is a draft of an early stage business plan.

[0917] A "skill set" is a list of skills and abilities required for a particular task or project.

[0918] An "engineer" is a specialist who has the specialized knowledge and skills required for a system or project.

[0919] A "creator" is someone with specialized skills in design and content production.

[0920] The "matching candidate list" is a list of suitable engineers and creators selected based on their skill sets.

[0921] "Crowdfunding" is a method of raising funds from a large number of investors via the Internet.

[0922] A "campaign page" is a webpage created for crowdfunding that lists campaign details, target amount, and description.

[0923] "Investor" means a person who provides funds to a crowdfunding campaign.

[0924] This invention is an entrepreneurship support system that combines an emotion engine and realizes the realization of users' ideas, business plan formulation, matching of engineers and creators, and optimization of crowdfunding via a network. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[0925] Idea input and analysis

[0926] A user inputs an idea using an interface on the user device. For example, they can enter "Idea for a health management app using AI" in a text box. The server then receives the input idea text and sends it to an emotion engine. The emotion engine (e.g., a specific platform using natural language processing) analyzes the linguistic expression and recognizes the user's emotional state as "excited" or "anxious," etc.

[0927] The server then uses a generative AI model (e.g., OpenAI GPT-4) to analyze the emotional information and keywords and important topics of the ideas, generating relevant information and improvement suggestions. The generated information and suggestions are dynamically adjusted according to the user's emotional state. Finally, this information is displayed on the user's device, where the user can review and modify it.

[0928] Automatic generation of business plans and emotional personalization

[0929] The user uses the interface to input details of the business plan, such as market size, competitive analysis, and SWOT analysis. The server receives these details and sends them to the generative AI model, which then automatically generates a draft of the business plan and personalizes suggested revisions based on the user's emotional state. The proposal and draft are then displayed on the user's device for review and revision.

[0930] Matching engineers and creators

[0931] The server extracts the required skill sets from the automatically generated business plan. It then searches the platform's database of engineer and creator profiles to generate a list of candidates that match the skill sets. This list is sent to the user's device, where the user reviews the presented list of candidates and selects the appropriate engineer or creator. After selection, the user sends a message requesting cooperation. The server manages message sending and receiving in real time and stores the necessary records in a database.

[0932] Crowdfunding and communication with investors

[0933] The user inputs details of their crowdfunding campaign (e.g., title, description, target amount, and duration). The server then receives the campaign details and sends them to a generative AI model. The generative AI model then suggests effective campaign content and marketing strategies, adjusting the content based on the user's emotional state. The user can then create and publish a campaign page based on the suggested content.

[0934] In addition, the server recommends suitable projects based on the investor's areas of interest and past investment history, and the investor can review the recommended projects. If the investor has a question, the server sends it to the generative AI model to generate an appropriate answer. The generated answer is provided to the investor and also sent to the user's device.

[0935] Specific examples

[0936] As a specific example, if a user "enters an idea for an AI-based health management app," the server analyzes the text using an emotion engine and recognizes that the user's emotional state is "excited." Based on that emotional state, the generative AI model generates and provides suggestions to the user, including positive improvement suggestions and encouraging messages. Through this process, the user can feel more at ease and move forward with concretizing their idea.

[0937] keyword

[0938] Generative AI model, prompt sentence

[0939] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0940] Step 1:

[0941] The user inputs their idea using the interface on their device. For example, they might type "Idea for a health management app using AI" into the text box. After completing the input, they click the "Send" button. This operation sends the input text data to the server.

[0942] Input: Idea text entered by the user (e.g., "Idea for a health management app using AI")

[0943] Output: The input text data is sent to the server.

[0944] Step 2:

[0945] The server receives the idea text sent by the user. It prepares the received text data for sending to the emotion engine. Specifically, it converts the text data into a format that can be analyzed by the emotion engine.

[0946] Input: Idea text submitted by user

[0947] Output: Text data converted into a format that can be parsed by the emotion engine

[0948] Step 3:

[0949] The emotion engine analyzes the text data received from the server and recognizes the user's emotional state. The emotion engine uses natural language processing to extract emotional states (e.g., "excitement" or "anxiety") from linguistic expressions and keywords in the text.

[0950] Input: Text data converted into a format that can be parsed by the emotion engine

[0951] Output: User's emotional state (e.g., "excited," "anxious")

[0952] Step 4:

[0953] The server creates prompts for the generative AI model based on the emotional information obtained from the emotion engine. These prompts include keywords and important topics for the idea. The server then sends the prompts to the generative AI model.

[0954] Input: Emotional information and idea text

[0955] Output: The prompt to send to the generative AI model

[0956] Step 5:

[0957] The generative AI model receives the prompt and generates relevant information and improvement suggestions based on the prompt's content. The generative AI model also takes emotional information into account and makes suggestions based on the user's emotional state.

[0958] Input: Prompt sent from the server

[0959] Output: Improvement suggestions based on relevant information and sentiment

[0960] Step 6:

[0961] The server receives suggestions from the generative AI model and sends them to the user's device. The device interface displays improvement suggestions based on the generated information and emotions, allowing the user to confirm and modify them.

[0962] Input: Information and improvement suggestions from the generative AI model

[0963] Output: Display on the user's terminal

[0964] Step 7:

[0965] The user uses the interface to select the details of the business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) and enter the required information. After completing the input, the user clicks the "Submit" button, which sends the input data to the server.

[0966] Input: Business plan details entered by the user

[0967] Output: The input data is sent to the server

[0968] Step 8:

[0969] The server receives the details entered and sends them to a generative AI model, which uses this data as prompts to generate a draft business plan.

[0970] Input: Business plan details entered by the user

[0971] Output: The prompt to send to the generative AI model

[0972] Step 9:

[0973] The generative AI model automatically generates a draft business plan based on the prompts and also makes suggested revisions based on the user's emotional state.

[0974] Input: Prompt sent

[0975] Output: Draft business plan and proposed revisions

[0976] Step 10:

[0977] The server sends the generated draft and revision suggestions to the user's terminal, where the user can review them on the interface and make revisions as necessary.

[0978] Input: Draft and revision suggestions from a generative AI model

[0979] Output: Display on the user's terminal

[0980] Step 11:

[0981] The server extracts the required skill sets from the automatically generated business plan, searches the platform's database of engineer and creator profiles, generates a list of candidates that match the skill sets, and sends it to the user's device.

[0982] Input: Auto-generated business plan data

[0983] Output: List of matching candidates

[0984] Step 12:

[0985] The user reviews the list of candidates and selects the appropriate engineers or creators. They then send a message to the selected engineers or creators requesting their cooperation.

[0986] Input: Presented candidate list

[0987] Output: A message to the selected engineers and creators

[0988] Step 13:

[0989] The server manages the sending and receiving of messages in real time and stores the necessary records in a database, allowing for smooth communication between users and engineers / creators.

[0990] Input: Message from the user

[0991] Output: Real-time transmission and recording

[0992] Step 14:

[0993] The user enters the details of the crowdfunding campaign (e.g., title, description, goal amount, duration, etc.) and submits it. The server receives the campaign details and sends them to the generative AI model.

[0994] Input: Campaign details entered by the user

[0995] Output: The prompt to send to the generative AI model

[0996] Step 15:

[0997] The generative AI model proposes effective campaign content and marketing strategies based on the campaign details and sends them to the user, who then creates and publishes a campaign page based on the proposals.

[0998] Input: Prompt sent

[0999] Output: Effective campaign content and marketing strategies

[1000] Step 16:

[1001] The server recommends suitable projects based on the investor's interests and past investment history, and notifies the investor. The investor can then review the recommended projects and submit inquiries.

[1002] Input: Investor interests and past investment history

[1003] Output: Recommended projects and investor questions

[1004] Step 17:

[1005] The server sends the received questions to a generative AI model that generates a quick and appropriate answer, which is then provided to the investor and sent to the user's device.

[1006] Input: Investor Questions

[1007] Output: Answer from the generative AI model

[1008] (Application example 2)

[1009] Next, a description will be given of Application 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."

[1010] In current factory environments, production processes are not optimized with consideration given to the emotional state of workers. This creates challenges in improving productivity and worker satisfaction, and workers' motivation and mental state are often ignored. This can lead to reduced production efficiency and health risks for workers in the long term. Therefore, there is a need for a system that can analyze workers' emotional state in real time and use that data to suggest tasks and optimize resources.

[1011] 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 means for providing an interface for workers to input their emotional states, means for analyzing the input emotional states using a generative AI model and generating related information and optimization suggestions, means for displaying the generated information and optimization suggestions to the workers, means for generating task suggestions and break suggestions based on the workers' emotions, and means for optimizing resource allocation based on the status of the production process. This enables real-time work suggestions and resource optimization that take into account the emotional states of workers on the production line.

[1012] An "interface" is a connection means through which a user inputs data into a system.

[1013] A "generative AI model" is an artificial intelligence algorithm that performs various analyses and generation based on provided data.

[1014] "Emotional state" refers to the mental and emotional state and feelings of the worker.

[1015] "Analysis" is the process of taking input data, understanding it, and evaluating it.

[1016] "Relevant information" refers to information about workers' conditions and production processes obtained from the analyzed data.

[1017] "Optimization suggestions" are suggestions for improving work efficiency that are generated based on the worker's emotional state and production status.

[1018] "Display" refers to the act of presenting the generated information or proposal content to the user in a visible form.

[1019] "Task proposal" means proposing specific tasks for workers to perform.

[1020] A "rest suggestion" is a suggestion encouraging workers to take a rest.

[1021] "Production process" refers to the entire manufacturing process of a product in a factory and its management system.

[1022] "Resource allocation" refers to the most effective distribution of necessary resources and tasks, taking into account the production process and the emotional state of workers.

[1023] MODE FOR CARRYING OUT THE INVENTION

[1024] This invention relates to a factory robot system that analyzes the emotional state of workers and optimizes the production process based on the results. How this system is implemented will be described below.

[1025] 1. System Configuration

[1026] The system includes an interface for workers to input their emotional state, a generative AI model, an emotion analysis engine, and a factory robot for execution. It collects and analyzes emotional data from workers and provides the functionality to suggest appropriate tasks and breaks based on the results.

[1027] 2. Hardware and Software

[1028] Hardware: Factory robots, wearable devices for workers, user devices (PCs, smartphones, etc.)

[1029] Software: Python programs, natural language processing (NLP) engines, generative AI models (e.g., AI models using the Transformers library)

[1030] 3. Processing Flow

[1031] The server provides an interface that allows workers to input their emotional state via smartphone or PC. The input emotional data is sent to the server and analyzed by the emotion analysis engine. The analyzed emotional state data is further processed by the generative AI model to generate relevant information and optimization suggestions.

[1032] The generated information and suggestions are sent from the server to the worker's device, allowing the worker to receive appropriate tasks and break suggestions based on their emotional state. Furthermore, real-time data from the production process is used to optimize resource allocation, improving overall work efficiency.

[1033] Specific examples

[1034] For example, if a worker types, "I'm feeling a little stressed today," the sentiment analysis engine will interpret this as "NEGATIVE." Based on that emotional state, the generative AI model will generate a suggestion, "Take a short break to refresh yourself," and display it on the worker's device.

[1035] Prompt Sentence Examples

[1036] Below is an example of a prompt sentence to input to the generative AI model.

[1037] "Analyzing the emotional state of workers on a factory production line and extracting important emotional elements."

[1038] This makes it possible to analyze workers' emotional states in real time and, based on that data, optimally allocate resources and suggest tasks. The system aims to contribute to improving worker productivity and satisfaction.

[1039] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1040] Step 1:

[1041] The user inputs their emotional state. Using the interface of a smartphone or PC, the user inputs their emotional state in text format. The input data is a sentence that expresses the user's feelings (e.g., "I'm feeling a little stressed today").

[1042] Step 2:

[1043] The emotion data is sent to the server. The input emotion data is sent to the server via the Internet. The server receives this data and proceeds to the next analysis step.

[1044] Step 3:

[1045] The server analyzes the input data using an emotion engine. The server uses an emotion analysis engine (NLP model) to analyze the input text data and classify the emotional state into categories such as "positive" or "negative." This analysis outputs the type of emotion and its intensity.

[1046] Step 4:

[1047] The generative AI model generates optimization suggestions based on the emotional state. The server inputs the emotional state data obtained from the emotion analysis engine into the generative AI model, which then generates appropriate task and break suggestions based on that data. A specific prompt sentence might be, "Analyze the emotional state of workers on the factory production line and extract important emotional elements." The generated suggestions are obtained as output.

[1048] Step 5:

[1049] The generated suggestions are sent to the user's device. The server then sends the suggestions generated by the generative AI model to the user's device. These suggestions include specific actions (e.g., "Take a short break and refresh yourself").

[1050] Step 6:

[1051] The user checks the suggestions displayed on the device and acts on them. For example, if a suggestion to take a break is displayed, the user can refresh themselves by taking a break.

[1052] Step 7:

[1053] The server optimizes resource allocation in the production process based on real-time data. The server collects real-time data from the factory's production line and calculates the optimal resource allocation based on generative AI models and sentiment analysis data. This is expected to improve production efficiency.

[1054] The above processing steps create a system that analyzes the emotional state of workers in real time and, based on that data, optimally allocates resources and suggests tasks.

[1055] 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.

[1056] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1057] 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.

[1058] [Third embodiment]

[1059] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1060] 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.

[1061] 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).

[1062] 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.

[1063] 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.

[1064] 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).

[1065] 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.

[1066] 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.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1071] 1. System Overview

[1072] This is a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support fundraising. This system is implemented via a network that includes a server and user terminals.

[1073] 2. Idea input and analysis

[1074] The user (entrepreneur) enters their idea using an interface on their device. This interface includes a text input box. The entered text is sent to the server and analyzed by a generative AI model. The server extracts keywords and important topics from the idea and generates related information and improvement suggestions based on that information. The generated information is then sent to the device for the user to review and edit.

[1075] Examples:

[1076] The user enters "AI-based health management app."

[1077] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[1078] 3. Automatic generation of business plans

[1079] Users use the interface to select and input details of their business plan (market size, competitive analysis, SWOT analysis, etc.). This data is sent to the server, where it is analyzed by a generative AI model. The server then automatically generates a draft business plan based on the input data. This draft is then displayed on the device for the user to review and modify.

[1080] Examples:

[1081] Users input data on market size and competitive analysis.

[1082] The server generates a draft business plan based on this information and presents it to the user.

[1083] 4. Matching engineers and creators

[1084] The server extracts the required skill sets from the automatically generated business plan. The extracted skill sets are matched with the profiles of engineers and creators on the platform. The server generates a list of optimal candidates and presents them to the user. The user reviews and selects from the list of candidates, and communication begins.

[1085] Examples:

[1086] The server extracts skills such as "data analysis" and "mobile app development."

[1087] The server matches the profiles of engineers and creators who possess these skills and provides the list to the user.

[1088] The user selects the appropriate candidate from the list and sends a message.

[1089] 5. Crowdfunding and Investor Communication

[1090] Users enter details of their crowdfunding campaign into the interface, including the title, description, target amount, and duration. The server uses a generative AI model to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server then recommends suitable projects based on the investor's areas of interest and investment history, providing an interface for smooth communication between users and investors.

[1091] Examples:

[1092] The user enters the crowdfunding details and submits.

[1093] The server uses the generative AI model to propose effective campaign content and present it to the user.

[1094] The user edits and publishes the campaign page based on the proposal.

[1095] Investors can review the recommended projects and submit questions.

[1096] The server uses generative AI models to generate fast and relevant responses and send them to investors.

[1097] As a result, the present invention can efficiently support a series of processes from realizing an entrepreneur's idea to raising funds.

[1098] The processing flow will be explained below.

[1099] Idea input and analysis

[1100] Step 1:

[1101] The terminal (user) enters an idea in the text box and clicks the send button.

[1102] Step 2:

[1103] The server receives the input text data and sends it to a natural language processing (NLP) engine.

[1104] Step 3:

[1105] The server uses an NLP engine to break down input ideas into keywords and key topics.

[1106] Step 4:

[1107] The server generates relevant information and improvement suggestions based on the analyzed keywords and topics.

[1108] Step 5:

[1109] The server transmits the generated information and improvement suggestions to the user's terminal.

[1110] Step 6:

[1111] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[1112] Automatic generation of business plans

[1113] Step 1:

[1114] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[1115] Step 2:

[1116] The server receives the details and data entered and sends them to the generative AI model.

[1117] Step 3:

[1118] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[1119] Step 4:

[1120] The server transmits the generated draft business plan to the user's terminal.

[1121] Step 5:

[1122] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[1123] Matching engineers and creators

[1124] Step 1:

[1125] The server extracts the required skill sets from the automatically generated business plan.

[1126] Step 2:

[1127] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[1128] Step 3:

[1129] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[1130] Step 4:

[1131] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[1132] Step 5:

[1133] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[1134] Step 6:

[1135] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1136] Crowdfunding and communication with investors

[1137] Step 1:

[1138] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[1139] Step 2:

[1140] The server receives the entered campaign details and sends them to the generative AI model.

[1141] Step 3:

[1142] The server uses generative AI models to suggest effective campaign content and marketing strategies.

[1143] Step 4:

[1144] The server transmits the proposed campaign content to the user's terminal.

[1145] Step 5:

[1146] The terminal (user) edits and publishes the campaign page based on the proposal content.

[1147] Step 6:

[1148] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[1149] Step 7:

[1150] The terminal (investor) reviews the recommended projects and sends questions.

[1151] Step 8:

[1152] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1153] Step 9:

[1154] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[1155] Example 1

[1156] Next, a description will be given of 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."

[1157] The process of entrepreneurs concretizing new business ideas, formulating business plans, matching with engineers and creators, and finally raising funds requires a lot of time and expertise. For this reason, entrepreneurs are seeking support systems to efficiently move through these processes. However, many current systems only support each process individually, and there is a lack of systems that consistently support the entire process. To solve this problem, a system is needed that provides comprehensive support from concretizing ideas to raising funds.

[1158] 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.

[1159] In this invention, the server includes a means for providing a user interface for entrepreneurs to input ideas, a means for analyzing the input idea using a generative AI model and generating related information and improvement suggestions, a means for displaying the generated information and improvement suggestions to the entrepreneur, a means for providing a user interface for selecting and inputting business plan items, a means for automatically generating a draft business plan based on the input data, a means for providing a user interface for the entrepreneur to review and modify the automatically generated draft, and a system for extracting necessary skill sets from the business plan, matching the skill sets with the profiles of engineers and creators on the platform to generate a list of matching candidates, providing a user interface for inputting details of the crowdfunding campaign, proposing effective campaign content and marketing strategies using a generative AI model, and creating a campaign page based on the input and proposed content, thereby enabling entrepreneurs to efficiently proceed through the entire process from idea realization to fundraising.

[1160] An "entrepreneur" refers to an individual or organization that has a new business idea and is trying to materialize it and develop it into a business.

[1161] A "user interface" is an interface through which a user interacts with a system, and includes input forms, buttons, and other operational elements.

[1162] A "generative AI model" is an artificial intelligence model that generates and analyzes text based on given data, and examples include models that perform natural language processing.

[1163] "Related information" refers to supplementary information or references provided by the generative AI model based on ideas and data input by the user.

[1164] "Improvement suggestions" refers to the generative AI model analyzing input data and providing suggestions and advice to improve an idea or plan.

[1165] A business plan is a document that details the direction and strategy of a business, and includes items such as market size, competitive analysis, and SWOT analysis.

[1166] "Draft" refers to an early version or preliminary document of a business plan automatically generated by a generative AI model.

[1167] A "skill set" refers to the skills, knowledge, and experience required to accomplish a specific task or project.

[1168] "Technologist" refers to an individual or organization with specialized knowledge or skills in a particular technical field.

[1169] "Creator" refers to a professional individual or organization that produces creative works or content.

[1170] "Profile" refers to information that describes the background, skills, and achievements of an engineer or creator.

[1171] The "matching candidate list" refers to a list of the most suitable engineers and creators selected by the generative AI model based on skill sets.

[1172] "Crowdfunding" refers to a method of raising funds from an unspecified number of supporters via the Internet.

[1173] "Campaign page" refers to a webpage that provides detailed information about crowdfunding and introduces the project.

[1174] This invention relates to a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support them in raising funds. This system is realized via a network that includes a server and user terminals.

[1175] System Configuration

[1176] 1. User idea input

[1177] Users access the system using a device (e.g., a PC or tablet). They input their ideas through the interface and click the "Submit" button. This input is sent to the server as an HTTP request.

[1178] Examples:

[1179] The user enters "AI-based health management app."

[1180] 2. Receiving and analyzing ideas

[1181] The server receives ideas submitted by users and analyzes them with a generative AI model (e.g., GPT-4). The model extracts keywords and important topics from the ideas and generates related information and improvement suggestions.

[1182] Examples:

[1183] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[1184] 3. Sending and displaying analysis results

[1185] The server converts the generated analysis results into JSON format and sends it to the user's device as an HTTP response. The user's device receives this response and displays the analysis results on its interface. The user can check the displayed analysis results and modify the text as necessary.

[1186] 4. Enter details of your business plan

[1187] Users input details of their business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) into the interface, and this data is sent to a server where a generative AI model analyzes it.

[1188] Examples:

[1189] Users input data on market size and competitive analysis.

[1190] 5. Automatic generation of business plans

[1191] The server automatically generates a draft business plan using a generative AI model based on the input data. This draft is displayed on the user's device, where the user can review and revise it.

[1192] 6. Matching engineers and creators

[1193] The server extracts the required skill sets from the business plan and matches them with the profiles of engineers and creators on the platform. A list of the best candidates is generated and presented to the user. The user selects the appropriate candidate from the list and communication begins.

[1194] Examples:

[1195] The server extracts skills such as "data analysis" and "mobile app development," matches the profiles of engineers and creators who possess these skills, and provides the list to the user.

[1196] The user selects the appropriate candidate from the list and sends a message.

[1197] 7. Enter your crowdfunding campaign details

[1198] Users input details of their crowdfunding campaign (e.g., title, description, target amount, duration, etc.) into the interface, and the server provides this information to a generative AI model that then suggests effective campaign content and marketing strategies.

[1199] Examples:

[1200] Users enter and submit their details to launch a crowdfunding campaign aimed at "developing a new AI health management app."

[1201] The server uses a generative AI model to propose effective campaign content, and users edit and publish campaign pages based on that content.

[1202] 8. Support for communication with investors

[1203] When an investor reviews a recommended project and submits a question, the server uses a generative AI model to analyze the question and generate a quick and appropriate answer, which is then sent to the investor for smooth communication.

[1204] This system allows entrepreneurs to efficiently go through the entire process from concretizing their ideas to raising funds.

[1205] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1206] Step 1:

[1207] The user enters an idea into the device's interface and clicks the "Submit" button, which causes the device to send the user-entered text as an HTTP request to the server.

[1208] Input: User's idea text.

[1209] Output: HTTP request to the server.

[1210] Specific operation: The user writes "Health management app using AI" in the text input box and clicks the "Send" button.

[1211] Step 2:

[1212] The server receives an HTTP request sent by a user, extracts text data from the request body, and provides this text data as input to a generative AI model to begin analysis.

[1213] Input: Idea text included in the request from the device.

[1214] Output: Analysis results (keywords, related information, improvement suggestions).

[1215] Specific operation: The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions.

[1216] Step 3:

[1217] The server converts the generated analysis results into JSON format and sends them as an HTTP response to the user's device. The user's device receives this response and displays the analysis results on its interface.

[1218] Input: Parsed result by the server.

[1219] Output: Analysis results displayed on the user's terminal.

[1220] Specific operation: The user terminal displays the analysis results on a graphical user interface (GUI) so that the user can check and correct them.

[1221] Step 4:

[1222] The user enters the details of the business plan (market size, competitive analysis, SWOT analysis, etc.) into the interface on the terminal and clicks the "Submit" button. This operation causes the terminal to send the detailed data to the server as an HTTP request.

[1223] Input: Detailed information about the business plan provided by the user.

[1224] Output: HTTP request to the server.

[1225] Specific operation: The user inputs "market size," "competitive analysis," "SWOT analysis," etc.

[1226] Step 5:

[1227] The server receives the detailed item data submitted by the user and provides this data as input to the generative AI model, which then automatically generates a draft business plan and returns it to the server.

[1228] Input: Business plan details included in the request from the device.

[1229] Output: A generated draft business plan.

[1230] Specific operation: The server automatically generates a business plan draft and sends the data converted into JSON format to the user's terminal.

[1231] Step 6:

[1232] The user terminal displays the received draft of the business plan on the interface, and the user can check the displayed content and make corrections as necessary.

[1233] Input: A draft business plan sent from the server.

[1234] Output: User-confirmed and revised business plan.

[1235] What happens: The user reviews and, if necessary, corrects the draft.

[1236] Step 7:

[1237] The server extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform, generating a list of the most suitable candidates and sending it to the user's device.

[1238] Input: Thurber's draft business plan.

[1239] Output: A list of the best candidates.

[1240] Specific operation: The server extracts required skill sets such as "data analysis" and "mobile app development" and generates a list of matching candidates.

[1241] Step 8:

[1242] The user checks the candidate list on the interface and selects the appropriate candidate. After selecting, the user enters a message and clicks the "Send" button. This message is sent to the server and distributed to the appropriate candidate.

[1243] Input: User selection result and message.

[1244] Output: Message delivery to candidates.

[1245] Specific behavior: The user selects a technician from a list of candidates and sends a message.

[1246] Step 9:

[1247] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) into the interface and clicks the "Submit" button, which causes the device to send the details to the server.

[1248] Input: Crowdfunding details entered by the user.

[1249] Output: HTTP request to the server.

[1250] Specific behavior: User enters details for "Developing a new AI health management app."

[1251] Step 10:

[1252] The server provides the received detailed data to the generative AI model, which then proposes effective campaign content and marketing strategies. These proposals are then sent to the user, who then edits and publishes the campaign page based on the proposals.

[1253] Input: Crowdfunding details data from the server.

[1254] Output: Proposal of effective campaign content and marketing strategy.

[1255] Specific operation: The server analyzes using the generative AI model and sends campaign content suggestions to the user.

[1256] Step 11:

[1257] When an investor reviews a recommended project and submits a question, the server analyzes the question using a generative AI model to generate a quick and appropriate answer, which is then sent to the investor, ensuring smooth communication.

[1258] Input: Investor questions.

[1259] Output: The answer from the generative AI model.

[1260] Specific operation: The server analyzes the investor's question, generates an appropriate answer, and sends it.

[1261] (Application example 1)

[1262] Next, a description will be given of Application 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."

[1263] It is necessary to smoothly support the entire process of entrepreneurs' efforts to materialize new ideas, efficiently formulate business plans, match them with appropriate engineers and creators, and effectively raise funds. These processes also require the provision of relevant information and optimization of marketing strategies through appropriate keyword extraction and prompt sentence generation.

[1264] 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.

[1265] In this invention, the server includes: means for providing an interface for entrepreneurs to input ideas; means for analyzing the input ideas using a generative AI model and generating related information and improvement proposals; means for displaying the generated information and improvement proposals to the entrepreneur; means for providing an interface for selecting and inputting business plan items; means for automatically generating a business plan draft based on the input data; means for providing an interface for the entrepreneur to review and modify the automatically generated draft; means for summarizing the idea and extracting keywords using an AI model; and means for generating additional information and proposals using the suggested keywords as prompts. This enables entrepreneurs to efficiently materialize their ideas, develop business plans, match with appropriate engineers and creators, and effectively raise funds.

[1266] An "interface" is a screen or operating means used by a user to input or receive information.

[1267] A "generative AI model" is an algorithm that uses natural language processing and machine learning to analyze text data and generate relevant information and suggestions.

[1268] "Analysis" is the process of analyzing input data and extracting its contents and related information.

[1269] "Related information" is additional data or knowledge related to the ideas or data entered.

[1270] "Improvement proposals" are specific advice or suggestions for further improvement based on the ideas and data entered.

[1271] A business plan is a written plan that includes business goals, strategies, market and competitive analysis, financial forecasts, etc.

[1272] "Selection" is the act of choosing the appropriate option from multiple options.

[1273] "Input" is the act of sending information or data to a system.

[1274] "Auto-generation" is the process by which a system automatically generates a specific form of output based on user input data.

[1275] A "draft" is an early document or plan developed toward a final version.

[1276] "Keywords" are important words or phrases in the text data.

[1277] A "prompt sentence" is a guided sentence that generates a response to text or a question entered by the user.

[1278] "Matching" is the process of finding the best match based on certain criteria.

[1279] "Crowdfunding" is a method of raising small amounts of money from a large number of people via the Internet.

[1280] A "marketing strategy" is a plan or method for appropriately delivering products or services to the market and promoting sales.

[1281] This invention is a system that helps entrepreneurs materialize their ideas, develop business plans, match them with engineers and creators, and ultimately support them in raising funds. This system is realized through an application installed on a smartphone or head-mounted display (HMD).

[1282] The server first provides an interface for users to input their ideas. When users input their ideas using a text input box on their device, the text is sent to the server. The server then uses a generative AI model (e.g., Hugging Face's BART model) to analyze the input ideas and extract summaries and keywords. It then uses an AI model (e.g., OpenAI's GPT-3) to generate related information and improvement suggestions.

[1283] The generated information and suggestions are sent to the user's device, where the user can review and edit them. For example, if a user types in "health management app using AI," the server will extract keywords such as "AI," "health management," and "app" and provide the user with related information and suggestions.

[1284] The server then provides an interface for the user to select and input details of the business plan (market size, competitive analysis, etc.). Once the user has entered these items, the data is sent to the server, which automatically generates a draft business plan using a generative AI model. The generated draft is displayed on the user's device for review and revision.

[1285] The server then extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform. A list of the most suitable candidates is generated and presented to the user. The user can then review the list and begin communicating with the appropriate candidates.

[1286] To raise funds, the server provides an interface for users to enter details of their crowdfunding campaign. Once users enter the title, description, target amount, etc., the generative AI model is used to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server also recommends appropriate projects based on investors' areas of interest and investment history, providing an interface for smooth communication between users and investors.

[1287] Examples of specific prompts include:

[1288] Idea analysis prompt:

[1289] Analyze and provide keywords for the following idea:

[1290] Health management app

[1291] ·Automatically generate business plan prompt:

[1292] Create a business plan draft for a startup based on the following details:

[1293] Idea Summary: Development of a health management app using AI

[1294] Market Size: $100 million

[1295] Competitor Analysis: Multiple Existing Applications

[1296] In this way, users can efficiently materialize their ideas, develop business plans, match with suitable engineers and creators, and effectively raise funds.

[1297] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1298] Step 1:

[1299] The user inputs their idea using a smartphone or HMD. The input text is sent from the device to the server. At this time, the user enters a specific idea, such as "a health management app using AI," into the input box.

[1300] Step 2:

[1301] The server passes the received text data to a generative AI model (Hugging Face's BART model) to analyze the idea. The server extracts a summary of the idea and keywords (e.g., "AI," "health management," "app") and generates related information. The generated information and suggestions are sent to the device.

[1302] Step 3:

[1303] The user checks the analysis results and suggestions displayed on the device. They make any necessary changes or corrections and resubmit the new content. For example, the user might make a correction such as "Add a function to measure the effectiveness of AI health management."

[1304] Step 4:

[1305] The server provides an interface for selecting and inputting items in the business plan based on the content resubmitted by the user. The user inputs detailed data such as market size and competitive analysis and transmits it to the server.

[1306] Step 5:

[1307] The server sends the received data to a generative AI model (OpenAI's GPT-3) that automatically generates a draft business plan. The draft business plan is generated based on specific input data, such as "market size: $100 million" and "competitive analysis: many existing apps." The generated draft is then sent to the device.

[1308] Step 6:

[1309] The user checks the draft business plan on the device and makes any necessary revisions, such as "narrowing the target market to young people aged 20-30." The revised content is then sent back to the server.

[1310] Step 7:

[1311] The server extracts the necessary skill sets from the final business plan and matches them with engineers and creators. It compares the profile information on the platform with the skill sets and generates a list of optimal candidates. The generated candidate list is sent to the device.

[1312] Step 8:

[1313] The user checks the list of candidates displayed on the device and selects the appropriate engineers and creators. Communication with the selected candidates takes place through a dedicated interface.

[1314] Step 9:

[1315] The server provides an interface for the user to enter details of the crowdfunding campaign (title, description, goal amount, etc.), which the user enters and submits to the server.

[1316] Step 10:

[1317] The server passes the received detailed information to the generative AI model, which then proposes effective campaign content and marketing strategies. For example, specific proposals such as "target market should utilize social media and campaign duration should be three months" are generated and sent to the user's device.

[1318] Step 11:

[1319] Users edit and publish crowdfunding campaign pages based on the proposed content, and the server simultaneously recommends suitable projects and generates prompts based on the investor's areas of interest and investment history.

[1320] Step 12:

[1321] Investors review recommended projects and send questions. The server uses a generative AI model to generate quick and appropriate answers and sends them to the investors, ensuring smooth communication between entrepreneurs and investors.

[1322] 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.

[1323] This invention is an entrepreneurship support system that combines an emotion engine and analyzes the user's emotional state to materialize ideas, formulate business plans, match engineers and creators, and optimize crowdfunding. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[1324] Idea input and analysis

[1325] 1. Enter your idea

[1326] Users input their ideas using the interface on their devices. The input field has a text box where users can freely describe their ideas.

[1327] 2. Sentiment Analysis and Recommendation Generation

[1328] The server receives the input idea text and sends it to the emotion engine.

[1329] The emotion engine uses natural language processing (NLP) to analyze the linguistic expressions contained in ideas and recognize the user's emotional state.

[1330] The server uses a generative AI model to analyze the emotional information obtained from the emotion engine and the keywords and important topics of the ideas.

[1331] The server generates relevant information and improvement suggestions, dynamically adjusting the content according to the user's emotional state.

[1332] Improvement suggestions based on the generated information and emotions are displayed on the user's device, and the user can confirm and correct them.

[1333] Automatic generation of business plans and emotional personalization

[1334] 1. Enter business plan items

[1335] The user uses the interface to select business plan details (market size, competitive analysis, SWOT analysis, etc.) and enter the required information.

[1336] 2. Automatic draft generation

[1337] The server receives the details entered and sends them to the generative AI model.

[1338] The server uses a generative AI model to automatically generate a draft business plan and personalizes suggested revisions based on the user's emotional state.

[1339] The automatically generated draft and suggested revisions are displayed on the user's terminal.

[1340] Matching engineers and creators

[1341] 1. Skill set extraction and matching

[1342] The server extracts the required skill sets from the automatically generated business plan and searches the platform's database of engineer and creator profiles.

[1343] A list of candidates matching the skill set is generated and sent to the user's terminal.

[1344] 2. Initiating communication

[1345] The user reviews the list of candidates presented and selects the appropriate engineers and creators.

[1346] Users send messages to selected engineers and creators, requesting their cooperation.

[1347] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1348] Crowdfunding and communication with investors

[1349] 1. Enter campaign details and submit proposal

[1350] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) and submits it.

[1351] The server receives the entered campaign details and sends them to the generative AI model.

[1352] Using generative AI models, it suggests effective campaign content and marketing strategies, adjusting them according to the user's emotional state.

[1353] Based on the proposal, the user edits and publishes the campaign page.

[1354] 2. Investor Recommendations and Q&A

[1355] The server recommends suitable crowdfunding projects based on investors' areas of interest and past investment history.

[1356] Investors can review the recommended projects and submit questions.

[1357] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1358] The generated answers are retransmitted to the user's terminal and provided to the investor.

[1359] Examples:

[1360] When a user inputs an idea for an AI-based health management app, the server analyzes the text using an emotion engine and recognizes the user's emotional state, such as excitement or anxiety. Based on that emotional state, the generative AI model generates and provides the user with suggestions for improvement, particularly those with positive directions or encouraging messages. Through this process, the user can feel more at ease as they work to bring their idea to fruition.

[1361] The processing flow will be explained below.

[1362] Idea input and analysis

[1363] Step 1:

[1364] The terminal (user) enters an idea in the text box and clicks the send button.

[1365] Step 2:

[1366] The server receives the input text data and sends it to the emotion engine.

[1367] Step 3:

[1368] The emotion engine analyzes the linguistic expressions in the text and recognizes the user's emotional state (e.g., excitement, joy, anxiety, sadness, etc.).

[1369] Step 4:

[1370] The server sends the emotional information obtained from the emotion engine, along with the idea keywords and important topics, to the generative AI model.

[1371] Step 5:

[1372] The generative AI model generates relevant information and improvement suggestions based on emotional information and keywords, dynamically adjusting the suggestions according to the user's emotional state.

[1373] Step 6:

[1374] The server transmits improvement suggestions based on the generated information and emotions to the user's terminal.

[1375] Step 7:

[1376] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[1377] Automatic generation of business plans and emotional personalization

[1378] Step 1:

[1379] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[1380] Step 2:

[1381] The server receives the details and data entered and sends them to the generative AI model.

[1382] Step 3:

[1383] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[1384] Step 4:

[1385] The server takes into account the user's emotional state and personalizes the suggested corrections needed, for example suggesting more detailed explanations for a user in an anxious state.

[1386] Step 5:

[1387] The server transmits the generated business plan draft and proposed revisions to the user's terminal.

[1388] Step 6:

[1389] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[1390] Matching engineers and creators

[1391] Step 1:

[1392] The server extracts the required skill sets from the automatically generated business plan.

[1393] Step 2:

[1394] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[1395] Step 3:

[1396] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[1397] Step 4:

[1398] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[1399] Step 5:

[1400] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[1401] Step 6:

[1402] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1403] Crowdfunding and communication with investors

[1404] Step 1:

[1405] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[1406] Step 2:

[1407] The server receives the entered campaign details and sends them to the generative AI model.

[1408] Step 3:

[1409] The server uses a generative AI model to propose effective campaign content and marketing strategies, taking into account the user's emotional state.

[1410] Step 4:

[1411] The server transmits the proposed campaign content to the user's terminal.

[1412] Step 5:

[1413] The terminal (user) edits and publishes the campaign page based on the proposal content.

[1414] Step 6:

[1415] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[1416] Step 7:

[1417] The terminal (investor) reviews the recommended projects and sends questions if necessary.

[1418] Step 8:

[1419] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1420] Step 9:

[1421] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[1422] Example 2

[1423] Next, a description will be given of 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."

[1424] Conventional entrepreneurship support systems provide improvement suggestions and business plans without considering the user's emotional state, making it difficult for users to receive appropriate feedback. Furthermore, it is difficult to address individual users' emotional states and specific needs when matching with engineers and creators or optimizing crowdfunding. Therefore, there is a need for improved user experience and more effective and personalized support.

[1425] 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. In this invention, the server includes: means for providing an interface for users to input ideas; means for analyzing the input ideas using a generative AI model and generating improvement suggestions based on related information and sentiment analysis; means for displaying the generated information and improvement suggestions to the user; means for providing an interface for selecting and inputting items of a business plan; means for automatically generating a draft of a business plan based on the input data; means for providing an interface for the user to check and modify the automatically generated draft; means for extracting required skill sets from the business plan; means for matching the profiles of engineers and creators on the platform with the skill sets and generating a list of matching candidates; means for presenting the list of matching candidates to the user; means for managing communication with the engineers and creators selected by the user and storing records; means for providing an interface for inputting details of the crowdfunding campaign; means for proposing effective campaign content and marketing strategies using a generative AI model; means for creating a campaign page based on the input and proposed content; means for recommending appropriate projects based on the investor's areas of interest and past investment history; and means for quickly and appropriately generating answers to questions from investors. This will enable personalized support based on the user's emotional state, effective matching with engineers and creators, and optimization of crowdfunding.

[1426] A "user" is a person who uses the entrepreneurial support system to input ideas and develop business plans.

[1427] An "interface" is a screen or operating means through which a user inputs data into a system.

[1428] A "generative AI model" is an artificial intelligence model that analyzes data entered by the user and generates improvement suggestions and information.

[1429] "Emotion analysis" is a technology that recognizes and analyzes the emotional state of a user from the text they enter.

[1430] "Improvement suggestions" are specific advice for improvements or corrections provided by the generative AI model in response to input ideas or data.

[1431] A business plan is a strategy or plan for starting a business or promoting a new venture, and includes market size, competitive analysis, and SWOT analysis.

[1432] A "draft" is a draft of an early stage business plan.

[1433] A "skill set" is a list of skills and abilities required for a particular task or project.

[1434] An "engineer" is a specialist who has the specialized knowledge and skills required for a system or project.

[1435] A "creator" is someone with specialized skills in design and content production.

[1436] The "matching candidate list" is a list of suitable engineers and creators selected based on their skill sets.

[1437] "Crowdfunding" is a method of raising funds from a large number of investors via the Internet.

[1438] A "campaign page" is a webpage created for crowdfunding that lists campaign details, target amount, and description.

[1439] "Investor" means a person who provides funds to a crowdfunding campaign.

[1440] This invention is an entrepreneurship support system that combines an emotion engine and realizes the realization of users' ideas, business plan formulation, matching of engineers and creators, and optimization of crowdfunding via a network. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[1441] Idea input and analysis

[1442] A user inputs an idea using an interface on the user device. For example, they can enter "Idea for a health management app using AI" in a text box. The server then receives the input idea text and sends it to an emotion engine. The emotion engine (e.g., a specific platform using natural language processing) analyzes the linguistic expression and recognizes the user's emotional state as "excited" or "anxious," etc.

[1443] The server then uses a generative AI model (e.g., OpenAI GPT-4) to analyze the emotional information and keywords and important topics of the ideas, generating relevant information and improvement suggestions. The generated information and suggestions are dynamically adjusted according to the user's emotional state. Finally, this information is displayed on the user's device, where the user can review and modify it.

[1444] Automatic generation of business plans and emotional personalization

[1445] The user uses the interface to input details of the business plan, such as market size, competitive analysis, and SWOT analysis. The server receives these details and sends them to the generative AI model, which then automatically generates a draft of the business plan and personalizes suggested revisions based on the user's emotional state. The proposal and draft are then displayed on the user's device for review and revision.

[1446] Matching engineers and creators

[1447] The server extracts the required skill sets from the automatically generated business plan. It then searches the platform's database of engineer and creator profiles to generate a list of candidates that match the skill sets. This list is sent to the user's device, where the user reviews the presented list of candidates and selects the appropriate engineer or creator. After selection, the user sends a message requesting cooperation. The server manages message sending and receiving in real time and stores the necessary records in a database.

[1448] Crowdfunding and communication with investors

[1449] The user inputs details of their crowdfunding campaign (e.g., title, description, target amount, and duration). The server then receives the campaign details and sends them to a generative AI model. The generative AI model then suggests effective campaign content and marketing strategies, adjusting the content based on the user's emotional state. The user can then create and publish a campaign page based on the suggested content.

[1450] In addition, the server recommends suitable projects based on the investor's areas of interest and past investment history, and the investor can review the recommended projects. If the investor has a question, the server sends it to the generative AI model to generate an appropriate answer. The generated answer is provided to the investor and also sent to the user's device.

[1451] Specific examples

[1452] As a specific example, if a user "enters an idea for an AI-based health management app," the server analyzes the text using an emotion engine and recognizes that the user's emotional state is "excited." Based on that emotional state, the generative AI model generates and provides suggestions to the user, including positive improvement suggestions and encouraging messages. Through this process, the user can feel more at ease and move forward with concretizing their idea.

[1453] keyword

[1454] Generative AI model, prompt sentence

[1455] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1456] Step 1:

[1457] The user inputs their idea using the interface on their device. For example, they might type "Idea for a health management app using AI" into the text box. After completing the input, they click the "Send" button. This operation sends the input text data to the server.

[1458] Input: Idea text entered by the user (e.g., "Idea for a health management app using AI")

[1459] Output: The input text data is sent to the server.

[1460] Step 2:

[1461] The server receives the idea text sent by the user. It prepares the received text data for sending to the emotion engine. Specifically, it converts the text data into a format that can be analyzed by the emotion engine.

[1462] Input: Idea text submitted by user

[1463] Output: Text data converted into a format that can be parsed by the emotion engine

[1464] Step 3:

[1465] The emotion engine analyzes the text data received from the server and recognizes the user's emotional state. The emotion engine uses natural language processing to extract emotional states (e.g., "excitement" or "anxiety") from linguistic expressions and keywords in the text.

[1466] Input: Text data converted into a format that can be parsed by the emotion engine

[1467] Output: User's emotional state (e.g., "excited," "anxious")

[1468] Step 4:

[1469] The server creates prompts for the generative AI model based on the emotional information obtained from the emotion engine. These prompts include keywords and important topics for the idea. The server then sends the prompts to the generative AI model.

[1470] Input: Emotional information and idea text

[1471] Output: The prompt to send to the generative AI model

[1472] Step 5:

[1473] The generative AI model receives the prompt and generates relevant information and improvement suggestions based on the prompt's content. The generative AI model also takes emotional information into account and makes suggestions based on the user's emotional state.

[1474] Input: Prompt sent from the server

[1475] Output: Improvement suggestions based on relevant information and sentiment

[1476] Step 6:

[1477] The server receives suggestions from the generative AI model and sends them to the user's device. The device interface displays improvement suggestions based on the generated information and emotions, allowing the user to confirm and modify them.

[1478] Input: Information and improvement suggestions from the generative AI model

[1479] Output: Display on the user's terminal

[1480] Step 7:

[1481] The user uses the interface to select the details of the business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) and enter the required information. After completing the input, the user clicks the "Submit" button, which sends the input data to the server.

[1482] Input: Business plan details entered by the user

[1483] Output: The input data is sent to the server

[1484] Step 8:

[1485] The server receives the details entered and sends them to a generative AI model, which uses this data as prompts to generate a draft business plan.

[1486] Input: Business plan details entered by the user

[1487] Output: The prompt to send to the generative AI model

[1488] Step 9:

[1489] The generative AI model automatically generates a draft business plan based on the prompts and also makes suggested revisions based on the user's emotional state.

[1490] Input: Prompt sent

[1491] Output: Draft business plan and proposed revisions

[1492] Step 10:

[1493] The server sends the generated draft and revision suggestions to the user's terminal, where the user can review them on the interface and make revisions as necessary.

[1494] Input: Draft and revision suggestions from a generative AI model

[1495] Output: Display on the user's terminal

[1496] Step 11:

[1497] The server extracts the required skill sets from the automatically generated business plan, searches the platform's database of engineer and creator profiles, generates a list of candidates that match the skill sets, and sends it to the user's device.

[1498] Input: Auto-generated business plan data

[1499] Output: List of matching candidates

[1500] Step 12:

[1501] The user reviews the list of candidates and selects the appropriate engineers or creators. They then send a message to the selected engineers or creators requesting their cooperation.

[1502] Input: Presented candidate list

[1503] Output: A message to the selected engineers and creators

[1504] Step 13:

[1505] The server manages the sending and receiving of messages in real time and stores the necessary records in a database, allowing for smooth communication between users and engineers / creators.

[1506] Input: Message from the user

[1507] Output: Real-time transmission and recording

[1508] Step 14:

[1509] The user enters the details of the crowdfunding campaign (e.g., title, description, goal amount, duration, etc.) and submits it. The server receives the campaign details and sends them to the generative AI model.

[1510] Input: Campaign details entered by the user

[1511] Output: The prompt to send to the generative AI model

[1512] Step 15:

[1513] The generative AI model proposes effective campaign content and marketing strategies based on the campaign details and sends them to the user, who then creates and publishes a campaign page based on the proposals.

[1514] Input: Prompt sent

[1515] Output: Effective campaign content and marketing strategies

[1516] Step 16:

[1517] The server recommends suitable projects based on the investor's interests and past investment history, and notifies the investor. The investor can then review the recommended projects and submit inquiries.

[1518] Input: Investor interests and past investment history

[1519] Output: Recommended projects and investor questions

[1520] Step 17:

[1521] The server sends the received questions to a generative AI model that generates a quick and appropriate answer, which is then provided to the investor and sent to the user's device.

[1522] Input: Investor Questions

[1523] Output: Answer from the generative AI model

[1524] (Application example 2)

[1525] Next, a description will be given of Application 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."

[1526] In current factory environments, production processes are not optimized with consideration given to the emotional state of workers. This creates challenges in improving productivity and worker satisfaction, and workers' motivation and mental state are often ignored. This can lead to reduced production efficiency and health risks for workers in the long term. Therefore, there is a need for a system that can analyze workers' emotional state in real time and use that data to suggest tasks and optimize resources.

[1527] 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 means for providing an interface for workers to input their emotional states, means for analyzing the input emotional states using a generative AI model and generating related information and optimization suggestions, means for displaying the generated information and optimization suggestions to the workers, means for generating task suggestions and break suggestions based on the workers' emotions, and means for optimizing resource allocation based on the status of the production process. This enables real-time work suggestions and resource optimization that take into account the emotional states of workers on the production line.

[1528] An "interface" is a connection means through which a user inputs data into a system.

[1529] A "generative AI model" is an artificial intelligence algorithm that performs various analyses and generation based on provided data.

[1530] "Emotional state" refers to the mental and emotional state and feelings of the worker.

[1531] "Analysis" is the process of taking input data, understanding it, and evaluating it.

[1532] "Relevant information" refers to information about workers' conditions and production processes obtained from the analyzed data.

[1533] "Optimization suggestions" are suggestions for improving work efficiency that are generated based on the worker's emotional state and production status.

[1534] "Display" refers to the act of presenting the generated information or proposal content to the user in a visible form.

[1535] "Task proposal" means proposing specific tasks for workers to perform.

[1536] A "rest suggestion" is a suggestion encouraging workers to take a rest.

[1537] "Production process" refers to the entire manufacturing process of a product in a factory and its management system.

[1538] "Resource allocation" refers to the most effective distribution of necessary resources and tasks, taking into account the production process and the emotional state of workers.

[1539] MODE FOR CARRYING OUT THE INVENTION

[1540] This invention relates to a factory robot system that analyzes the emotional state of workers and optimizes the production process based on the results. How this system is implemented will be described below.

[1541] 1. System Configuration

[1542] The system includes an interface for workers to input their emotional state, a generative AI model, an emotion analysis engine, and a factory robot for execution. It collects and analyzes emotional data from workers and provides the functionality to suggest appropriate tasks and breaks based on the results.

[1543] 2. Hardware and Software

[1544] Hardware: Factory robots, wearable devices for workers, user devices (PCs, smartphones, etc.)

[1545] Software: Python programs, natural language processing (NLP) engines, generative AI models (e.g., AI models using the Transformers library)

[1546] 3. Processing Flow

[1547] The server provides an interface that allows workers to input their emotional state via smartphone or PC. The input emotional data is sent to the server and analyzed by the emotion analysis engine. The analyzed emotional state data is further processed by the generative AI model to generate relevant information and optimization suggestions.

[1548] The generated information and suggestions are sent from the server to the worker's device, allowing the worker to receive appropriate tasks and break suggestions based on their emotional state. Furthermore, real-time data from the production process is used to optimize resource allocation, improving overall work efficiency.

[1549] Specific examples

[1550] For example, if a worker types, "I'm feeling a little stressed today," the sentiment analysis engine will interpret this as "NEGATIVE." Based on that emotional state, the generative AI model will generate a suggestion, "Take a short break to refresh yourself," and display it on the worker's device.

[1551] Prompt Sentence Examples

[1552] Below is an example of a prompt sentence to input to the generative AI model.

[1553] "Analyzing the emotional state of workers on a factory production line and extracting important emotional elements."

[1554] This makes it possible to analyze workers' emotional states in real time and, based on that data, optimally allocate resources and suggest tasks. The system aims to contribute to improving worker productivity and satisfaction.

[1555] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1556] Step 1:

[1557] The user inputs their emotional state. Using the interface of a smartphone or PC, the user inputs their emotional state in text format. The input data is a sentence that expresses the user's feelings (e.g., "I'm feeling a little stressed today").

[1558] Step 2:

[1559] The emotion data is sent to the server. The input emotion data is sent to the server via the Internet. The server receives this data and proceeds to the next analysis step.

[1560] Step 3:

[1561] The server analyzes the input data using an emotion engine. The server uses an emotion analysis engine (NLP model) to analyze the input text data and classify the emotional state into categories such as "positive" or "negative." This analysis outputs the type of emotion and its intensity.

[1562] Step 4:

[1563] The generative AI model generates optimization suggestions based on the emotional state. The server inputs the emotional state data obtained from the emotion analysis engine into the generative AI model, which then generates appropriate task and break suggestions based on that data. A specific prompt sentence might be, "Analyze the emotional state of workers on the factory production line and extract important emotional elements." The generated suggestions are obtained as output.

[1564] Step 5:

[1565] The generated suggestions are sent to the user's device. The server then sends the suggestions generated by the generative AI model to the user's device. These suggestions include specific actions (e.g., "Take a short break and refresh yourself").

[1566] Step 6:

[1567] The user checks the suggestions displayed on the device and acts on them. For example, if a suggestion to take a break is displayed, the user can refresh themselves by taking a break.

[1568] Step 7:

[1569] The server optimizes resource allocation in the production process based on real-time data. The server collects real-time data from the factory's production line and calculates the optimal resource allocation based on generative AI models and sentiment analysis data. This is expected to improve production efficiency.

[1570] The above processing steps create a system that analyzes the emotional state of workers in real time and, based on that data, optimally allocates resources and suggests tasks.

[1571] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1572] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[1573] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1574] [Fourth embodiment]

[1575] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1576] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1577] 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).

[1578] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1579] 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.

[1580] 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).

[1581] 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.

[1582] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1583] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1584] 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.

[1585] 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.

[1586] In the robot 414, the processor 46 performs the reception output process. 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.

[1587] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1588] 1. System Overview

[1589] This is a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support fundraising. This system is implemented via a network that includes a server and user terminals.

[1590] 2. Idea input and analysis

[1591] The user (entrepreneur) enters their idea using an interface on their device. This interface includes a text input box. The entered text is sent to the server and analyzed by a generative AI model. The server extracts keywords and important topics from the idea and generates related information and improvement suggestions based on that information. The generated information is then sent to the device for the user to review and edit.

[1592] Examples:

[1593] The user enters "AI-based health management app."

[1594] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[1595] 3. Automatic generation of business plans

[1596] Users use the interface to select and input details of their business plan (market size, competitive analysis, SWOT analysis, etc.). This data is sent to the server, where it is analyzed by a generative AI model. The server then automatically generates a draft business plan based on the input data. This draft is then displayed on the device for the user to review and modify.

[1597] Examples:

[1598] Users input data on market size and competitive analysis.

[1599] The server generates a draft business plan based on this information and presents it to the user.

[1600] 4. Matching engineers and creators

[1601] The server extracts the required skill sets from the automatically generated business plan. The extracted skill sets are matched with the profiles of engineers and creators on the platform. The server generates a list of optimal candidates and presents them to the user. The user reviews and selects from the list of candidates, and communication begins.

[1602] Examples:

[1603] The server extracts skills such as "data analysis" and "mobile app development."

[1604] The server matches the profiles of engineers and creators who possess these skills and provides the list to the user.

[1605] The user selects the appropriate candidate from the list and sends a message.

[1606] 5. Crowdfunding and Investor Communication

[1607] Users enter details of their crowdfunding campaign into the interface, including the title, description, target amount, and duration. The server uses a generative AI model to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server then recommends suitable projects based on the investor's areas of interest and investment history, providing an interface for smooth communication between users and investors.

[1608] Examples:

[1609] The user enters the crowdfunding details and submits.

[1610] The server uses the generative AI model to propose effective campaign content and present it to the user.

[1611] The user edits and publishes the campaign page based on the proposal.

[1612] Investors can review the recommended projects and submit questions.

[1613] The server uses generative AI models to generate fast and relevant responses and send them to investors.

[1614] As a result, the present invention can efficiently support a series of processes from realizing an entrepreneur's idea to raising funds.

[1615] The processing flow will be explained below.

[1616] Idea input and analysis

[1617] Step 1:

[1618] The terminal (user) enters an idea in the text box and clicks the send button.

[1619] Step 2:

[1620] The server receives the input text data and sends it to a natural language processing (NLP) engine.

[1621] Step 3:

[1622] The server uses an NLP engine to break down input ideas into keywords and key topics.

[1623] Step 4:

[1624] The server generates relevant information and improvement suggestions based on the analyzed keywords and topics.

[1625] Step 5:

[1626] The server transmits the generated information and improvement suggestions to the user's terminal.

[1627] Step 6:

[1628] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[1629] Automatic generation of business plans

[1630] Step 1:

[1631] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[1632] Step 2:

[1633] The server receives the details and data entered and sends them to the generative AI model.

[1634] Step 3:

[1635] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[1636] Step 4:

[1637] The server transmits the generated draft business plan to the user's terminal.

[1638] Step 5:

[1639] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[1640] Matching engineers and creators

[1641] Step 1:

[1642] The server extracts the required skill sets from the automatically generated business plan.

[1643] Step 2:

[1644] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[1645] Step 3:

[1646] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[1647] Step 4:

[1648] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[1649] Step 5:

[1650] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[1651] Step 6:

[1652] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1653] Crowdfunding and communication with investors

[1654] Step 1:

[1655] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[1656] Step 2:

[1657] The server receives the entered campaign details and sends them to the generative AI model.

[1658] Step 3:

[1659] The server uses generative AI models to suggest effective campaign content and marketing strategies.

[1660] Step 4:

[1661] The server transmits the proposed campaign content to the user's terminal.

[1662] Step 5:

[1663] The terminal (user) edits and publishes the campaign page based on the proposal content.

[1664] Step 6:

[1665] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[1666] Step 7:

[1667] The terminal (investor) reviews the recommended projects and sends questions.

[1668] Step 8:

[1669] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1670] Step 9:

[1671] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[1672] Example 1

[1673] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1674] The process of entrepreneurs concretizing new business ideas, formulating business plans, matching with engineers and creators, and finally raising funds requires a lot of time and expertise. For this reason, entrepreneurs are seeking support systems to efficiently move through these processes. However, many current systems only support each process individually, and there is a lack of systems that consistently support the entire process. To solve this problem, a system is needed that provides comprehensive support from concretizing ideas to raising funds.

[1675] 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.

[1676] In this invention, the server includes a means for providing a user interface for entrepreneurs to input ideas, a means for analyzing the input idea using a generative AI model and generating related information and improvement suggestions, a means for displaying the generated information and improvement suggestions to the entrepreneur, a means for providing a user interface for selecting and inputting business plan items, a means for automatically generating a draft business plan based on the input data, a means for providing a user interface for the entrepreneur to review and modify the automatically generated draft, and a system for extracting necessary skill sets from the business plan, matching the skill sets with the profiles of engineers and creators on the platform to generate a list of matching candidates, providing a user interface for inputting details of the crowdfunding campaign, proposing effective campaign content and marketing strategies using a generative AI model, and creating a campaign page based on the input and proposed content, thereby enabling entrepreneurs to efficiently proceed through the entire process from idea realization to fundraising.

[1677] An "entrepreneur" refers to an individual or organization that has a new business idea and is trying to materialize it and develop it into a business.

[1678] A "user interface" is an interface through which a user interacts with a system, and includes input forms, buttons, and other operational elements.

[1679] A "generative AI model" is an artificial intelligence model that generates and analyzes text based on given data, and examples include models that perform natural language processing.

[1680] "Related information" refers to supplementary information or references provided by the generative AI model based on ideas and data input by the user.

[1681] "Improvement suggestions" refers to the generative AI model analyzing input data and providing suggestions and advice to improve an idea or plan.

[1682] A business plan is a document that details the direction and strategy of a business, and includes items such as market size, competitive analysis, and SWOT analysis.

[1683] "Draft" refers to an early version or preliminary document of a business plan automatically generated by a generative AI model.

[1684] A "skill set" refers to the skills, knowledge, and experience required to accomplish a specific task or project.

[1685] "Technologist" refers to an individual or organization with specialized knowledge or skills in a particular technical field.

[1686] "Creator" refers to a professional individual or organization that produces creative works or content.

[1687] "Profile" refers to information that describes the background, skills, and achievements of an engineer or creator.

[1688] The "matching candidate list" refers to a list of the most suitable engineers and creators selected by the generative AI model based on skill sets.

[1689] "Crowdfunding" refers to a method of raising funds from an unspecified number of supporters via the Internet.

[1690] "Campaign page" refers to a webpage that provides detailed information about crowdfunding and introduces the project.

[1691] This invention relates to a system that helps entrepreneurs realize their ideas, develop business plans, match them with engineers and creators, and support them in raising funds. This system is realized via a network that includes a server and user terminals.

[1692] System Configuration

[1693] 1. User idea input

[1694] Users access the system using a device (e.g., a PC or tablet). They input their ideas through the interface and click the "Submit" button. This input is sent to the server as an HTTP request.

[1695] Examples:

[1696] The user enters "AI-based health management app."

[1697] 2. Receiving and analyzing ideas

[1698] The server receives ideas submitted by users and analyzes them with a generative AI model (e.g., GPT-4). The model extracts keywords and important topics from the ideas and generates related information and improvement suggestions.

[1699] Examples:

[1700] The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions to provide to users.

[1701] 3. Sending and displaying analysis results

[1702] The server converts the generated analysis results into JSON format and sends it to the user's device as an HTTP response. The user's device receives this response and displays the analysis results on its interface. The user can check the displayed analysis results and modify the text as necessary.

[1703] 4. Enter details of your business plan

[1704] Users input details of their business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) into the interface, and this data is sent to a server where a generative AI model analyzes it.

[1705] Examples:

[1706] Users input data on market size and competitive analysis.

[1707] 5. Automatic generation of business plans

[1708] The server automatically generates a draft business plan using a generative AI model based on the input data. This draft is displayed on the user's device, where the user can review and revise it.

[1709] 6. Matching engineers and creators

[1710] The server extracts the required skill sets from the business plan and matches them with the profiles of engineers and creators on the platform. A list of the best candidates is generated and presented to the user. The user selects the appropriate candidate from the list and communication begins.

[1711] Examples:

[1712] The server extracts skills such as "data analysis" and "mobile app development," matches the profiles of engineers and creators who possess these skills, and provides the list to the user.

[1713] The user selects the appropriate candidate from the list and sends a message.

[1714] 7. Enter your crowdfunding campaign details

[1715] Users input details of their crowdfunding campaign (e.g., title, description, target amount, duration, etc.) into the interface, and the server provides this information to a generative AI model that then suggests effective campaign content and marketing strategies.

[1716] Examples:

[1717] Users enter and submit their details to launch a crowdfunding campaign aimed at "developing a new AI health management app."

[1718] The server uses a generative AI model to propose effective campaign content, and users edit and publish campaign pages based on that content.

[1719] 8. Support for communication with investors

[1720] When an investor reviews a recommended project and submits a question, the server uses a generative AI model to analyze the question and generate a quick and appropriate answer, which is then sent to the investor for smooth communication.

[1721] This system allows entrepreneurs to efficiently go through the entire process from concretizing their ideas to raising funds.

[1722] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1723] Step 1:

[1724] The user enters an idea into the device's interface and clicks the "Submit" button, which causes the device to send the user-entered text as an HTTP request to the server.

[1725] Input: User's idea text.

[1726] Output: HTTP request to the server.

[1727] Specific operation: The user writes "Health management app using AI" in the text input box and clicks the "Send" button.

[1728] Step 2:

[1729] The server receives an HTTP request sent by a user, extracts text data from the request body, and provides this text data as input to a generative AI model to begin analysis.

[1730] Input: Idea text included in the request from the device.

[1731] Output: Analysis results (keywords, related information, improvement suggestions).

[1732] Specific operation: The server extracts keywords such as "AI," "health management," and "apps," and generates related information and suggestions.

[1733] Step 3:

[1734] The server converts the generated analysis results into JSON format and sends them as an HTTP response to the user's device. The user's device receives this response and displays the analysis results on its interface.

[1735] Input: Parsed result by the server.

[1736] Output: Analysis results displayed on the user's terminal.

[1737] Specific operation: The user terminal displays the analysis results on a graphical user interface (GUI) so that the user can check and correct them.

[1738] Step 4:

[1739] The user enters the details of the business plan (market size, competitive analysis, SWOT analysis, etc.) into the interface on the terminal and clicks the "Submit" button. This operation causes the terminal to send the detailed data to the server as an HTTP request.

[1740] Input: Detailed information about the business plan provided by the user.

[1741] Output: HTTP request to the server.

[1742] Specific operation: The user inputs "market size," "competitive analysis," "SWOT analysis," etc.

[1743] Step 5:

[1744] The server receives the detailed item data submitted by the user and provides this data as input to the generative AI model, which then automatically generates a draft business plan and returns it to the server.

[1745] Input: Business plan details included in the request from the device.

[1746] Output: A generated draft business plan.

[1747] Specific operation: The server automatically generates a business plan draft and sends the data converted into JSON format to the user's terminal.

[1748] Step 6:

[1749] The user terminal displays the received draft of the business plan on the interface, and the user can check the displayed content and make corrections as necessary.

[1750] Input: A draft business plan sent from the server.

[1751] Output: User-confirmed and revised business plan.

[1752] What happens: The user reviews and, if necessary, corrects the draft.

[1753] Step 7:

[1754] The server extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform, generating a list of the most suitable candidates and sending it to the user's device.

[1755] Input: Thurber's draft business plan.

[1756] Output: A list of the best candidates.

[1757] Specific operation: The server extracts required skill sets such as "data analysis" and "mobile app development" and generates a list of matching candidates.

[1758] Step 8:

[1759] The user checks the candidate list on the interface and selects the appropriate candidate. After selecting, the user enters a message and clicks the "Send" button. This message is sent to the server and distributed to the appropriate candidate.

[1760] Input: User selection result and message.

[1761] Output: Message delivery to candidates.

[1762] Specific behavior: The user selects a technician from a list of candidates and sends a message.

[1763] Step 9:

[1764] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) into the interface and clicks the "Submit" button, which causes the device to send the details to the server.

[1765] Input: Crowdfunding details entered by the user.

[1766] Output: HTTP request to the server.

[1767] Specific behavior: User enters details for "Developing a new AI health management app."

[1768] Step 10:

[1769] The server provides the received detailed data to the generative AI model, which then proposes effective campaign content and marketing strategies. These proposals are then sent to the user, who then edits and publishes the campaign page based on the proposals.

[1770] Input: Crowdfunding details data from the server.

[1771] Output: Proposal of effective campaign content and marketing strategy.

[1772] Specific operation: The server analyzes using the generative AI model and sends campaign content suggestions to the user.

[1773] Step 11:

[1774] When an investor reviews a recommended project and submits a question, the server analyzes the question using a generative AI model to generate a quick and appropriate answer, which is then sent to the investor, ensuring smooth communication.

[1775] Input: Investor questions.

[1776] Output: The answer from the generative AI model.

[1777] Specific operation: The server analyzes the investor's question, generates an appropriate answer, and sends it.

[1778] (Application example 1)

[1779] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1780] It is necessary to smoothly support the entire process of entrepreneurs' efforts to materialize new ideas, efficiently formulate business plans, match them with appropriate engineers and creators, and effectively raise funds. These processes also require the provision of relevant information and optimization of marketing strategies through appropriate keyword extraction and prompt sentence generation.

[1781] 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.

[1782] In this invention, the server includes: means for providing an interface for entrepreneurs to input ideas; means for analyzing the input ideas using a generative AI model and generating related information and improvement proposals; means for displaying the generated information and improvement proposals to the entrepreneur; means for providing an interface for selecting and inputting business plan items; means for automatically generating a business plan draft based on the input data; means for providing an interface for the entrepreneur to review and modify the automatically generated draft; means for summarizing the idea and extracting keywords using an AI model; and means for generating additional information and proposals using the suggested keywords as prompts. This enables entrepreneurs to efficiently materialize their ideas, develop business plans, match with appropriate engineers and creators, and effectively raise funds.

[1783] An "interface" is a screen or operating means used by a user to input or receive information.

[1784] A "generative AI model" is an algorithm that uses natural language processing and machine learning to analyze text data and generate relevant information and suggestions.

[1785] "Analysis" is the process of analyzing input data and extracting its contents and related information.

[1786] "Related information" is additional data or knowledge related to the ideas or data entered.

[1787] "Improvement proposals" are specific advice or suggestions for further improvement based on the ideas and data entered.

[1788] A business plan is a written plan that includes business goals, strategies, market and competitive analysis, financial forecasts, etc.

[1789] "Selection" is the act of choosing the appropriate option from multiple options.

[1790] "Input" is the act of sending information or data to a system.

[1791] "Auto-generation" is the process by which a system automatically generates a specific form of output based on user input data.

[1792] A "draft" is an early document or plan developed toward a final version.

[1793] "Keywords" are important words or phrases in the text data.

[1794] A "prompt sentence" is a guided sentence that generates a response to text or a question entered by the user.

[1795] "Matching" is the process of finding the best match based on certain criteria.

[1796] "Crowdfunding" is a method of raising small amounts of money from a large number of people via the Internet.

[1797] A "marketing strategy" is a plan or method for appropriately delivering products or services to the market and promoting sales.

[1798] This invention is a system that helps entrepreneurs materialize their ideas, develop business plans, match them with engineers and creators, and ultimately support them in raising funds. This system is realized through an application installed on a smartphone or head-mounted display (HMD).

[1799] The server first provides an interface for users to input their ideas. When users input their ideas using a text input box on their device, the text is sent to the server. The server then uses a generative AI model (e.g., Hugging Face's BART model) to analyze the input ideas and extract summaries and keywords. It then uses an AI model (e.g., OpenAI's GPT-3) to generate related information and improvement suggestions.

[1800] The generated information and suggestions are sent to the user's device, where the user can review and edit them. For example, if a user types in "health management app using AI," the server will extract keywords such as "AI," "health management," and "app" and provide the user with related information and suggestions.

[1801] The server then provides an interface for the user to select and input details of the business plan (market size, competitive analysis, etc.). Once the user has entered these items, the data is sent to the server, which automatically generates a draft business plan using a generative AI model. The generated draft is displayed on the user's device for review and revision.

[1802] The server then extracts the required skill sets from the automatically generated business plan and matches them with the profiles of engineers and creators on the platform. A list of the most suitable candidates is generated and presented to the user. The user can then review the list and begin communicating with the appropriate candidates.

[1803] To raise funds, the server provides an interface for users to enter details of their crowdfunding campaign. Once users enter the title, description, target amount, etc., the generative AI model is used to suggest effective campaign content and marketing strategies. Based on the suggestions, users edit and publish the campaign page. The server also recommends appropriate projects based on investors' areas of interest and investment history, providing an interface for smooth communication between users and investors.

[1804] Examples of specific prompts include:

[1805] Idea analysis prompt:

[1806] Analyze and provide keywords for the following idea:

[1807] Health management app

[1808] ·Automatically generate business plan prompt:

[1809] Create a business plan draft for a startup based on the following details:

[1810] Idea Summary: Development of a health management app using AI

[1811] Market Size: $100 million

[1812] Competitor Analysis: Multiple Existing Applications

[1813] In this way, users can efficiently materialize their ideas, develop business plans, match with suitable engineers and creators, and effectively raise funds.

[1814] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1815] Step 1:

[1816] The user inputs their idea using a smartphone or HMD. The input text is sent from the device to the server. At this time, the user enters a specific idea, such as "a health management app using AI," into the input box.

[1817] Step 2:

[1818] The server passes the received text data to a generative AI model (Hugging Face's BART model) to analyze the idea. The server extracts a summary of the idea and keywords (e.g., "AI," "health management," "app") and generates related information. The generated information and suggestions are sent to the device.

[1819] Step 3:

[1820] The user checks the analysis results and suggestions displayed on the device. They make any necessary changes or corrections and resubmit the new content. For example, the user might make a correction such as "Add a function to measure the effectiveness of AI health management."

[1821] Step 4:

[1822] The server provides an interface for selecting and inputting items in the business plan based on the content resubmitted by the user. The user inputs detailed data such as market size and competitive analysis and transmits it to the server.

[1823] Step 5:

[1824] The server sends the received data to a generative AI model (OpenAI's GPT-3) that automatically generates a draft business plan. The draft business plan is generated based on specific input data, such as "market size: $100 million" and "competitive analysis: many existing apps." The generated draft is then sent to the device.

[1825] Step 6:

[1826] The user checks the draft business plan on the device and makes any necessary revisions, such as "narrowing the target market to young people aged 20-30." The revised content is then sent back to the server.

[1827] Step 7:

[1828] The server extracts the necessary skill sets from the final business plan and matches them with engineers and creators. It compares the profile information on the platform with the skill sets and generates a list of optimal candidates. The generated candidate list is sent to the device.

[1829] Step 8:

[1830] The user checks the list of candidates displayed on the device and selects the appropriate engineers and creators. Communication with the selected candidates takes place through a dedicated interface.

[1831] Step 9:

[1832] The server provides an interface for the user to enter details of the crowdfunding campaign (title, description, goal amount, etc.), which the user enters and submits to the server.

[1833] Step 10:

[1834] The server passes the received detailed information to the generative AI model, which then proposes effective campaign content and marketing strategies. For example, specific proposals such as "target market should utilize social media and campaign duration should be three months" are generated and sent to the user's device.

[1835] Step 11:

[1836] Users edit and publish crowdfunding campaign pages based on the proposed content, and the server simultaneously recommends suitable projects and generates prompts based on the investor's areas of interest and investment history.

[1837] Step 12:

[1838] Investors review recommended projects and send questions. The server uses a generative AI model to generate quick and appropriate answers and sends them to the investors, ensuring smooth communication between entrepreneurs and investors.

[1839] 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.

[1840] This invention is an entrepreneurship support system that combines an emotion engine and analyzes the user's emotional state to materialize ideas, formulate business plans, match engineers and creators, and optimize crowdfunding. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[1841] Idea input and analysis

[1842] 1. Enter your idea

[1843] Users input their ideas using the interface on their devices. The input field has a text box where users can freely describe their ideas.

[1844] 2. Sentiment Analysis and Recommendation Generation

[1845] The server receives the input idea text and sends it to the emotion engine.

[1846] The emotion engine uses natural language processing (NLP) to analyze the linguistic expressions contained in ideas and recognize the user's emotional state.

[1847] The server uses a generative AI model to analyze the emotional information obtained from the emotion engine and the keywords and important topics of the ideas.

[1848] The server generates relevant information and improvement suggestions, dynamically adjusting the content according to the user's emotional state.

[1849] Improvement suggestions based on the generated information and emotions are displayed on the user's device, and the user can confirm and correct them.

[1850] Automatic generation of business plans and emotional personalization

[1851] 1. Enter business plan items

[1852] The user uses the interface to select business plan details (market size, competitive analysis, SWOT analysis, etc.) and enter the required information.

[1853] 2. Automatic draft generation

[1854] The server receives the details entered and sends them to the generative AI model.

[1855] The server uses a generative AI model to automatically generate a draft business plan and personalizes suggested revisions based on the user's emotional state.

[1856] The automatically generated draft and suggested revisions are displayed on the user's terminal.

[1857] Matching engineers and creators

[1858] 1. Skill set extraction and matching

[1859] The server extracts the required skill sets from the automatically generated business plan and searches the platform's database of engineer and creator profiles.

[1860] A list of candidates matching the skill set is generated and sent to the user's terminal.

[1861] 2. Initiating communication

[1862] The user reviews the list of candidates presented and selects the appropriate engineers and creators.

[1863] Users send messages to selected engineers and creators, requesting their cooperation.

[1864] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1865] Crowdfunding and communication with investors

[1866] 1. Enter campaign details and submit proposal

[1867] The user enters the details of the crowdfunding campaign (title, description, target amount, duration, etc.) and submits it.

[1868] The server receives the entered campaign details and sends them to the generative AI model.

[1869] Using generative AI models, it suggests effective campaign content and marketing strategies, adjusting them according to the user's emotional state.

[1870] Based on the proposal, the user edits and publishes the campaign page.

[1871] 2. Investor Recommendations and Q&A

[1872] The server recommends suitable crowdfunding projects based on investors' areas of interest and past investment history.

[1873] Investors can review the recommended projects and submit questions.

[1874] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1875] The generated answers are retransmitted to the user's terminal and provided to the investor.

[1876] Examples:

[1877] When a user inputs an idea for an AI-based health management app, the server analyzes the text using an emotion engine and recognizes the user's emotional state, such as excitement or anxiety. Based on that emotional state, the generative AI model generates and provides the user with suggestions for improvement, particularly those with positive directions or encouraging messages. Through this process, the user can feel more at ease as they work to bring their idea to fruition.

[1878] The processing flow will be explained below.

[1879] Idea input and analysis

[1880] Step 1:

[1881] The terminal (user) enters an idea in the text box and clicks the send button.

[1882] Step 2:

[1883] The server receives the input text data and sends it to the emotion engine.

[1884] Step 3:

[1885] The emotion engine analyzes the linguistic expressions in the text and recognizes the user's emotional state (e.g., excitement, joy, anxiety, sadness, etc.).

[1886] Step 4:

[1887] The server sends the emotional information obtained from the emotion engine, along with the idea keywords and important topics, to the generative AI model.

[1888] Step 5:

[1889] The generative AI model generates relevant information and improvement suggestions based on emotional information and keywords, dynamically adjusting the suggestions according to the user's emotional state.

[1890] Step 6:

[1891] The server transmits improvement suggestions based on the generated information and emotions to the user's terminal.

[1892] Step 7:

[1893] The terminal (user) checks the received information and suggestions on the interface and makes corrections as necessary.

[1894] Automatic generation of business plans and emotional personalization

[1895] Step 1:

[1896] The terminal (user) selects important items of the business plan (market size, competitive analysis, SWOT analysis, etc.) and enters the necessary detailed information.

[1897] Step 2:

[1898] The server receives the details and data entered and sends them to the generative AI model.

[1899] Step 3:

[1900] The server uses a generative AI model to analyze the input data and automatically generate a draft business plan.

[1901] Step 4:

[1902] The server takes into account the user's emotional state and personalizes the suggested corrections needed, for example suggesting more detailed explanations for a user in an anxious state.

[1903] Step 5:

[1904] The server transmits the generated business plan draft and proposed revisions to the user's terminal.

[1905] Step 6:

[1906] The terminal (user) checks the draft on the interface and makes corrections as necessary.

[1907] Matching engineers and creators

[1908] Step 1:

[1909] The server extracts the required skill sets from the automatically generated business plan.

[1910] Step 2:

[1911] The server searches the profile database of engineers and creators on the platform based on the extracted skill set.

[1912] Step 3:

[1913] The server generates a list of candidates that match the skill set and sends it to the user's terminal.

[1914] Step 4:

[1915] The terminal (user) checks the candidate list and selects the appropriate engineers and creators.

[1916] Step 5:

[1917] The device (user) sends a message to the selected engineers or creators, requesting their cooperation.

[1918] Step 6:

[1919] The server manages the sending and receiving of messages in real time and stores the necessary records in a database.

[1920] Crowdfunding and communication with investors

[1921] Step 1:

[1922] The terminal (user) enters details of the crowdfunding campaign (title, description, target amount, period, etc.) and submits it.

[1923] Step 2:

[1924] The server receives the entered campaign details and sends them to the generative AI model.

[1925] Step 3:

[1926] The server uses a generative AI model to propose effective campaign content and marketing strategies, taking into account the user's emotional state.

[1927] Step 4:

[1928] The server transmits the proposed campaign content to the user's terminal.

[1929] Step 5:

[1930] The terminal (user) edits and publishes the campaign page based on the proposal content.

[1931] Step 6:

[1932] The server recommends suitable crowdfunding projects based on the investor's areas of interest and past investment history.

[1933] Step 7:

[1934] The terminal (investor) reviews the recommended projects and sends questions if necessary.

[1935] Step 8:

[1936] The server sends the received questions to a generative AI model, which generates quick and appropriate answers.

[1937] Step 9:

[1938] The server retransmits the generated answers to the user's terminal and provides them to the investor.

[1939] Example 2

[1940] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1941] Conventional entrepreneurship support systems provide improvement suggestions and business plans without considering the user's emotional state, making it difficult for users to receive appropriate feedback. Furthermore, it is difficult to address individual users' emotional states and specific needs when matching with engineers and creators or optimizing crowdfunding. Therefore, there is a need for improved user experience and more effective and personalized support.

[1942] 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. In this invention, the server includes: means for providing an interface for users to input ideas; means for analyzing the input ideas using a generative AI model and generating improvement suggestions based on related information and sentiment analysis; means for displaying the generated information and improvement suggestions to the user; means for providing an interface for selecting and inputting items of a business plan; means for automatically generating a draft of a business plan based on the input data; means for providing an interface for the user to check and modify the automatically generated draft; means for extracting required skill sets from the business plan; means for matching the profiles of engineers and creators on the platform with the skill sets and generating a list of matching candidates; means for presenting the list of matching candidates to the user; means for managing communication with the engineers and creators selected by the user and storing records; means for providing an interface for inputting details of the crowdfunding campaign; means for proposing effective campaign content and marketing strategies using a generative AI model; means for creating a campaign page based on the input and proposed content; means for recommending appropriate projects based on the investor's areas of interest and past investment history; and means for quickly and appropriately generating answers to questions from investors. This will enable personalized support based on the user's emotional state, effective matching with engineers and creators, and optimization of crowdfunding.

[1943] A "user" is a person who uses the entrepreneurial support system to input ideas and develop business plans.

[1944] An "interface" is a screen or operating means through which a user inputs data into a system.

[1945] A "generative AI model" is an artificial intelligence model that analyzes data entered by the user and generates improvement suggestions and information.

[1946] "Emotion analysis" is a technology that recognizes and analyzes the emotional state of a user from the text they enter.

[1947] "Improvement suggestions" are specific advice for improvements or corrections provided by the generative AI model in response to input ideas or data.

[1948] A business plan is a strategy or plan for starting a business or promoting a new venture, and includes market size, competitive analysis, and SWOT analysis.

[1949] A "draft" is a draft of an early stage business plan.

[1950] A "skill set" is a list of skills and abilities required for a particular task or project.

[1951] An "engineer" is a specialist who has the specialized knowledge and skills required for a system or project.

[1952] A "creator" is someone with specialized skills in design and content production.

[1953] The "matching candidate list" is a list of suitable engineers and creators selected based on their skill sets.

[1954] "Crowdfunding" is a method of raising funds from a large number of investors via the Internet.

[1955] A "campaign page" is a webpage created for crowdfunding that lists campaign details, target amount, and description.

[1956] "Investor" means a person who provides funds to a crowdfunding campaign.

[1957] This invention is an entrepreneurship support system that combines an emotion engine and realizes the realization of users' ideas, business plan formulation, matching of engineers and creators, and optimization of crowdfunding via a network. This system is executed through a network system that includes a server, user terminals, an emotion engine, and a generative AI model.

[1958] Idea input and analysis

[1959] A user inputs an idea using an interface on the user device. For example, they can enter "Idea for a health management app using AI" in a text box. The server then receives the input idea text and sends it to an emotion engine. The emotion engine (e.g., a specific platform using natural language processing) analyzes the linguistic expression and recognizes the user's emotional state as "excited" or "anxious," etc.

[1960] The server then uses a generative AI model (e.g., OpenAI GPT-4) to analyze the emotional information and keywords and important topics of the ideas, generating relevant information and improvement suggestions. The generated information and suggestions are dynamically adjusted according to the user's emotional state. Finally, this information is displayed on the user's device, where the user can review and modify it.

[1961] Automatic generation of business plans and emotional personalization

[1962] The user uses the interface to input details of the business plan, such as market size, competitive analysis, and SWOT analysis. The server receives these details and sends them to the generative AI model, which then automatically generates a draft of the business plan and personalizes suggested revisions based on the user's emotional state. The proposal and draft are then displayed on the user's device for review and revision.

[1963] Matching engineers and creators

[1964] The server extracts the required skill sets from the automatically generated business plan. It then searches the platform's database of engineer and creator profiles to generate a list of candidates that match the skill sets. This list is sent to the user's device, where the user reviews the presented list of candidates and selects the appropriate engineer or creator. After selection, the user sends a message requesting cooperation. The server manages message sending and receiving in real time and stores the necessary records in a database.

[1965] Crowdfunding and communication with investors

[1966] The user inputs details of their crowdfunding campaign (e.g., title, description, target amount, and duration). The server then receives the campaign details and sends them to a generative AI model. The generative AI model then suggests effective campaign content and marketing strategies, adjusting the content based on the user's emotional state. The user can then create and publish a campaign page based on the suggested content.

[1967] In addition, the server recommends suitable projects based on the investor's areas of interest and past investment history, and the investor can review the recommended projects. If the investor has a question, the server sends it to the generative AI model to generate an appropriate answer. The generated answer is provided to the investor and also sent to the user's device.

[1968] Specific examples

[1969] As a specific example, if a user "enters an idea for an AI-based health management app," the server analyzes the text using an emotion engine and recognizes that the user's emotional state is "excited." Based on that emotional state, the generative AI model generates and provides suggestions to the user, including positive improvement suggestions and encouraging messages. Through this process, the user can feel more at ease and move forward with concretizing their idea.

[1970] keyword

[1971] Generative AI model, prompt sentence

[1972] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1973] Step 1:

[1974] The user inputs their idea using the interface on their device. For example, they might type "Idea for a health management app using AI" into the text box. After completing the input, they click the "Send" button. This operation sends the input text data to the server.

[1975] Input: Idea text entered by the user (e.g., "Idea for a health management app using AI")

[1976] Output: The input text data is sent to the server.

[1977] Step 2:

[1978] The server receives the idea text sent by the user. It prepares the received text data for sending to the emotion engine. Specifically, it converts the text data into a format that can be analyzed by the emotion engine.

[1979] Input: Idea text submitted by user

[1980] Output: Text data converted into a format that can be parsed by the emotion engine

[1981] Step 3:

[1982] The emotion engine analyzes the text data received from the server and recognizes the user's emotional state. The emotion engine uses natural language processing to extract emotional states (e.g., "excitement" or "anxiety") from linguistic expressions and keywords in the text.

[1983] Input: Text data converted into a format that can be parsed by the emotion engine

[1984] Output: User's emotional state (e.g., "excited," "anxious")

[1985] Step 4:

[1986] The server creates prompts for the generative AI model based on the emotional information obtained from the emotion engine. These prompts include keywords and important topics for the idea. The server then sends the prompts to the generative AI model.

[1987] Input: Emotional information and idea text

[1988] Output: The prompt to send to the generative AI model

[1989] Step 5:

[1990] The generative AI model receives the prompt and generates relevant information and improvement suggestions based on the prompt's content. The generative AI model also takes emotional information into account and makes suggestions based on the user's emotional state.

[1991] Input: Prompt sent from the server

[1992] Output: Improvement suggestions based on relevant information and sentiment

[1993] Step 6:

[1994] The server receives suggestions from the generative AI model and sends them to the user's device. The device interface displays improvement suggestions based on the generated information and emotions, allowing the user to confirm and modify them.

[1995] Input: Information and improvement suggestions from the generative AI model

[1996] Output: Display on the user's terminal

[1997] Step 7:

[1998] The user uses the interface to select the details of the business plan (e.g., market size, competitive analysis, SWOT analysis, etc.) and enter the required information. After completing the input, the user clicks the "Submit" button, which sends the input data to the server.

[1999] Input: Business plan details entered by the user

[2000] Output: The input data is sent to the server

[2001] Step 8:

[2002] The server receives the details entered and sends them to a generative AI model, which uses this data as prompts to generate a draft business plan.

[2003] Input: Business plan details entered by the user

[2004] Output: The prompt to send to the generative AI model

[2005] Step 9:

[2006] The generative AI model automatically generates a draft business plan based on the prompts and also makes suggested revisions based on the user's emotional state.

[2007] Input: Prompt sent

[2008] Output: Draft business plan and proposed revisions

[2009] Step 10:

[2010] The server sends the generated draft and revision suggestions to the user's terminal, where the user can review them on the interface and make revisions as necessary.

[2011] Input: Draft and revision suggestions from a generative AI model

[2012] Output: Display on the user's terminal

[2013] Step 11:

[2014] The server extracts the required skill sets from the automatically generated business plan, searches the platform's database of engineer and creator profiles, generates a list of candidates that match the skill sets, and sends it to the user's device.

[2015] Input: Auto-generated business plan data

[2016] Output: List of matching candidates

[2017] Step 12:

[2018] The user reviews the list of candidates and selects the appropriate engineers or creators. They then send a message to the selected engineers or creators requesting their cooperation.

[2019] Input: Presented candidate list

[2020] Output: A message to the selected engineers and creators

[2021] Step 13:

[2022] The server manages the sending and receiving of messages in real time and stores the necessary records in a database, allowing for smooth communication between users and engineers / creators.

[2023] Input: Message from the user

[2024] Output: Real-time transmission and recording

[2025] Step 14:

[2026] The user enters the details of the crowdfunding campaign (e.g., title, description, goal amount, duration, etc.) and submits it. The server receives the campaign details and sends them to the generative AI model.

[2027] Input: Campaign details entered by the user

[2028] Output: The prompt to send to the generative AI model

[2029] Step 15:

[2030] The generative AI model proposes effective campaign content and marketing strategies based on the campaign details and sends them to the user, who then creates and publishes a campaign page based on the proposals.

[2031] Input: Prompt sent

[2032] Output: Effective campaign content and marketing strategies

[2033] Step 16:

[2034] The server recommends suitable projects based on the investor's interests and past investment history, and notifies the investor. The investor can then review the recommended projects and submit inquiries.

[2035] Input: Investor interests and past investment history

[2036] Output: Recommended projects and investor questions

[2037] Step 17:

[2038] The server sends the received questions to a generative AI model that generates a quick and appropriate answer, which is then provided to the investor and sent to the user's device.

[2039] Input: Investor Questions

[2040] Output: Answer from the generative AI model

[2041] (Application example 2)

[2042] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2043] In current factory environments, production processes are not optimized with consideration given to the emotional state of workers. This creates challenges in improving productivity and worker satisfaction, and workers' motivation and mental state are often ignored. This can lead to reduced production efficiency and health risks for workers in the long term. Therefore, there is a need for a system that can analyze workers' emotional state in real time and use that data to suggest tasks and optimize resources.

[2044] 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 means for providing an interface for workers to input their emotional states, means for analyzing the input emotional states using a generative AI model and generating related information and optimization suggestions, means for displaying the generated information and optimization suggestions to the workers, means for generating task suggestions and break suggestions based on the workers' emotions, and means for optimizing resource allocation based on the status of the production process. This enables real-time work suggestions and resource optimization that take into account the emotional states of workers on the production line.

[2045] An "interface" is a connection means through which a user inputs data into a system.

[2046] A "generative AI model" is an artificial intelligence algorithm that performs various analyses and generation based on provided data.

[2047] "Emotional state" refers to the mental and emotional state and feelings of the worker.

[2048] "Analysis" is the process of taking input data, understanding it, and evaluating it.

[2049] "Relevant information" refers to information about workers' conditions and production processes obtained from the analyzed data.

[2050] "Optimization suggestions" are suggestions for improving work efficiency that are generated based on the worker's emotional state and production status.

[2051] "Display" refers to the act of presenting the generated information or proposal content to the user in a visible form.

[2052] "Task proposal" means proposing specific tasks for workers to perform.

[2053] A "rest suggestion" is a suggestion encouraging workers to take a rest.

[2054] "Production process" refers to the entire manufacturing process of a product in a factory and its management system.

[2055] "Resource allocation" refers to the most effective distribution of necessary resources and tasks, taking into account the production process and the emotional state of workers.

[2056] MODE FOR CARRYING OUT THE INVENTION

[2057] This invention relates to a factory robot system that analyzes the emotional state of workers and optimizes the production process based on the results. How this system is implemented will be described below.

[2058] 1. System Configuration

[2059] The system includes an interface for workers to input their emotional state, a generative AI model, an emotion analysis engine, and a factory robot for execution. It collects and analyzes emotional data from workers and provides the functionality to suggest appropriate tasks and breaks based on the results.

[2060] 2. Hardware and Software

[2061] Hardware: Factory robots, wearable devices for workers, user devices (PCs, smartphones, etc.)

[2062] Software: Python programs, natural language processing (NLP) engines, generative AI models (e.g., AI models using the Transformers library)

[2063] 3. Processing Flow

[2064] The server provides an interface that allows workers to input their emotional state via smartphone or PC. The input emotional data is sent to the server and analyzed by the emotion analysis engine. The analyzed emotional state data is further processed by the generative AI model to generate relevant information and optimization suggestions.

[2065] The generated information and suggestions are sent from the server to the worker's device, allowing the worker to receive appropriate tasks and break suggestions based on their emotional state. Furthermore, real-time data from the production process is used to optimize resource allocation, improving overall work efficiency.

[2066] Specific examples

[2067] For example, if a worker types, "I'm feeling a little stressed today," the sentiment analysis engine will interpret this as "NEGATIVE." Based on that emotional state, the generative AI model will generate a suggestion, "Take a short break to refresh yourself," and display it on the worker's device.

[2068] Prompt Sentence Examples

[2069] Below is an example of a prompt sentence to input to the generative AI model.

[2070] "Analyzing the emotional state of workers on a factory production line and extracting important emotional elements."

[2071] This makes it possible to analyze workers' emotional states in real time and, based on that data, optimally allocate resources and suggest tasks. The system aims to contribute to improving worker productivity and satisfaction.

[2072] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2073] Step 1:

[2074] The user inputs their emotional state. Using the interface of a smartphone or PC, the user inputs their emotional state in text format. The input data is a sentence that expresses the user's feelings (e.g., "I'm feeling a little stressed today").

[2075] Step 2:

[2076] The emotion data is sent to the server. The input emotion data is sent to the server via the Internet. The server receives this data and proceeds to the next analysis step.

[2077] Step 3:

[2078] The server analyzes the input data using an emotion engine. The server uses an emotion analysis engine (NLP model) to analyze the input text data and classify the emotional state into categories such as "positive" or "negative." This analysis outputs the type of emotion and its intensity.

[2079] Step 4:

[2080] The generative AI model generates optimization suggestions based on the emotional state. The server inputs the emotional state data obtained from the emotion analysis engine into the generative AI model, which then generates appropriate task and break suggestions based on that data. A specific prompt sentence might be, "Analyze the emotional state of workers on the factory production line and extract important emotional elements." The generated suggestions are obtained as output.

[2081] Step 5:

[2082] The generated suggestions are sent to the user's device. The server then sends the suggestions generated by the generative AI model to the user's device. These suggestions include specific actions (e.g., "Take a short break and refresh yourself").

[2083] Step 6:

[2084] The user checks the suggestions displayed on the device and acts on them. For example, if a suggestion to take a break is displayed, the user can refresh themselves by taking a break.

[2085] Step 7:

[2086] The server optimizes resource allocation in the production process based on real-time data. The server collects real-time data from the factory's production line and calculates the optimal resource allocation based on generative AI models and sentiment analysis data. This is expected to improve production efficiency.

[2087] The above processing steps create a system that analyzes the emotional state of workers in real time and, based on that data, optimally allocates resources and suggests tasks.

[2088] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2089] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) 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.

[2090] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2091] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2092] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2093] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2094] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2095] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2096] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2097] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2098] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2099] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2100] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2101] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2102] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2103] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2104] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2105] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2106] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2107] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2108] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2109] The following is further disclosed regarding the above embodiment.

[2110] (Claim 1)

[2111] a means for providing an interface for entrepreneurs to input their ideas;

[2112] A means for analyz...

Claims

1. a means for providing an interface for entrepreneurs to input their ideas; A means for analyzing the input ideas using a generative AI model and generating related information and improvement suggestions; a means for displaying the generated information and improvement suggestions to the entrepreneur; means for providing an interface for selecting and inputting business plan items; A means to automatically generate a draft business plan based on input data; The system includes a means for providing an interface for the entrepreneur to review and modify the automatically generated draft.

2. 2. The system of claim 1, further comprising: means for extracting a required skill set from a business plan; A means of matching the profiles of engineers and creators on the platform with skill sets to generate a list of matching candidates; The system includes a means for presenting a list of matching candidates to the entrepreneur.

3. 10. The system of claim 1, comprising: means for providing an interface for inputting details of a crowdfunding campaign; A means of proposing effective campaign content and marketing strategies using generative AI models; The system includes a means for creating a campaign page based on input and suggested content.

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