System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving an idea input by a user; means for distributing the idea to a plurality of artificial intelligent agents having different characteristics, wherein each agent performs brush-up of the idea; and means for integrating the ideas subjected to brush-up and providing the integrated idea to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, many high-quality ideas are submitted to contests using generative AI, but many of them are eliminated in the first round of selection due to a lack of information or supporting ideas. Furthermore, due to a lack of support to improve the feasibility and specificity of ideas, individual time and technical constraints become barriers, preventing the overall quality of ideas from improving. Another issue is that creating presentation materials and preparing oral manuscripts takes time, resulting in an inability to deliver the presentations that participants intended. [Means for solving the problem]

[0005] To address this issue, the present invention provides the following: a system including a means for receiving ideas entered by a user, a means for distributing the ideas to multiple AI agents with different characteristics, a means for each agent to refine the ideas, and a means for integrating the refined ideas and providing them to the user. The present invention also provides a system including a means for evaluating ideas submitted by a user and a means for returning the evaluation results to the user, a system including a means for analyzing presentation content and automatically generating slides and materials, a means for adjusting the slides and materials based on the user's instructions, and a means for generating a final presentation file and providing it to the user, a system including a means for automatically generating a mockup site based on mockup site specifications specified by the user and a means for providing the generated mockup site to the user, and a system including a means for automatically generating a presentation script based on the presentation content and desired time, and a means for providing the generated presentation script to the user and adjusting it based on feedback. This system allows users to overcome time and technical constraints to improve the quality of their ideas and improve their competitiveness in competitions.

[0006] "User" refers to the entity that provides ideas and receives support from the system.

[0007] "Server" refers to a central computing system that receives input from users, processes it, and returns the results.

[0008] "Idea" refers to a new idea or concept provided by a user.

[0009] "Artificial intelligence agents" refer to programs that have specific characteristics and roles and work together to refine users' ideas.

[0010] "Dreamer AI" refers to an artificial intelligence agent that adds new, future-oriented ideas and big visions to ideas.

[0011] "Enjoyment AI" refers to artificial intelligence agents that emphasize user experience and entertainment elements.

[0012] "Realist AI" refers to an artificial intelligence agent that considers the feasibility of ideas and brings them to technical realization.

[0013] "Critic AI" refers to an artificial intelligence agent that points out the risks and weaknesses of an idea and suggests areas for improvement.

[0014] "Brushing up" refers to providing additional value to an idea and making improvements to it.

[0015] "Template" refers to a predefined format that forms the basis for the format and layout of generated slides and materials.

[0016] A "mockup site" refers to a website that is generated as a model to show users before it is actually put into operation.

[0017] "Presentation" refers to the presentation or announcement of information by a user at a contest or explanation event.

[0018] The "oral manuscript" refers to a document that summarizes the content of the speech that the user will use in the presentation.

[0019] A "slide" refers to a screen or page used as visual aid in a presentation. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The embodiment of this invention is a specialized system for supporting generative AI contests, which effectively refines users' ideas and assists in the creation of presentation materials, mockup sites, and oral manuscripts. This system operates based on communications between a server, terminals, and users.

[0042] System Overview

[0043] The system has the following main functions:

[0044] 1. Idea brush-up (virtual brainstorming)

[0045] 2. Final round of the contest

[0046] 3. Presentation file creation support

[0047] 4. Automatic generation of mockup sites

[0048] 5. Preparation of oral presentation script

[0049] 1. Idea brush-up (virtual brainstorming)

[0050] 1. The user inputs an idea into the system from a terminal.

[0051] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[0052] 3. Visionary AI adds new ideas and big visions to ideas.

[0053] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[0054] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[0055] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[0056] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[0057] Example: When a user suggests a "new social networking app," the dreamer AI adds "VR integration," the enjoyer AI suggests "gamification elements," the realist AI adds "instant photo sharing functionality," and the critic AI points out "privacy concerns." The final integrated idea is sent back to the user.

[0058] 2. Final round of the contest

[0059] 1. The user submits an idea to the system from their device.

[0060] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0061] 3. The server returns the evaluation results to the user.

[0062] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[0063] 3. Presentation file creation support

[0064] 1. The user inputs the presentation content into the system from their device.

[0065] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[0066] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[0067] 4. The server generates the final presentation file and serves it to the user.

[0068] Example: A user inputs a "business plan" and the server automatically generates slides. When the user instructs "add a graph to this section," the server adds the graph.

[0069] 4. Automatic generation of mockup sites

[0070] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[0071] 2. The server analyzes the input information and selects a template for the mockup site.

[0072] 3. The server automatically generates a mockup site and provides it to the user.

[0073] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction and provides it to the user.

[0074] 5. Preparation of oral presentation script

[0075] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[0076] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0077] 3. The server automatically generates a presentation transcript and provides it to the user.

[0078] 4. The server adjusts the manuscript based on user feedback.

[0079] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral manuscript that fits within 5 minutes. When the user instructs, "Please explain this part in more detail," the server adds content that details the relevant part.

[0080] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals.

[0081] The processing flow will be explained below.

[0082] Idea brush-up (virtual brainstorming)

[0083] Step 1:

[0084] The user inputs an idea from a terminal and sends it to the server.

[0085] Step 2:

[0086] A server receives ideas from users.

[0087] Step 3:

[0088] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[0089] Step 4:

[0090] The Visionary AI adds new ideas and big visions to ideas, specifically proposing future-oriented scenarios and new concepts to ideas.

[0091] Step 5:

[0092] The Hedonist AI adds elements to ideas that enrich the user experience, such as entertainment elements and improvements to user interaction.

[0093] Step 6:

[0094] Realistic AI considers the feasibility of ideas and gives them technical specificity, for example by proposing a tech stack and adding prototype designs.

[0095] Step 7:

[0096] The AI ​​critic points out the risks and weaknesses of an idea and suggests ways to improve it, specifically highlighting legal risks and market concerns.

[0097] Step 8:

[0098] The server integrates feedback from the four AI agents and generates refined ideas.

[0099] Step 9:

[0100] The server returns the synthesized ideas to the user.

[0101] The first round of the contest

[0102] Step 1:

[0103] The user inputs an idea from a terminal and sends it to the server.

[0104] Step 2:

[0105] A server receives the submitted ideas.

[0106] Step 3:

[0107] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0108] Step 4:

[0109] The server assigns a score to each evaluation item.

[0110] Step 5:

[0111] The server calculates the overall score.

[0112] Step 6:

[0113] The server returns the evaluation results and feedback to the user.

[0114] Presentation file creation support

[0115] Step 1:

[0116] The user inputs the presentation content from the terminal and sends it to the server.

[0117] Step 2:

[0118] The server receives and analyzes the presentation content.

[0119] Step 3:

[0120] The server automatically selects a slide template.

[0121] Step 4:

[0122] The server generates the materials required for the presentation.

[0123] Step 5:

[0124] The user specifies the range or gives verbal instructions, which are then sent to the server.

[0125] Step 6:

[0126] The server adjusts the slides and materials based on the user's instructions.

[0127] Step 7:

[0128] The server generates the final presentation file and provides it to the user.

[0129] Automatic generation of mockup sites

[0130] Step 1:

[0131] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[0132] Step 2:

[0133] The server receives and analyzes the input information.

[0134] Step 3:

[0135] The server selects an appropriate mockup site template.

[0136] Step 4:

[0137] The server automatically generates a mockup site.

[0138] Step 5:

[0139] The server provides the generated mockup site to the user.

[0140] Presentation script creation

[0141] Step 1:

[0142] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[0143] Step 2:

[0144] The server receives and analyzes the presentation content and desired time.

[0145] Step 3:

[0146] The server calculates the appropriate time allocation for each slide or section.

[0147] Step 4:

[0148] The server automatically generates a presentation transcript.

[0149] Step 5:

[0150] The server provides the generated oral transcript to the user.

[0151] Step 6:

[0152] The user provides feedback and sends it to the server.

[0153] Step 7:

[0154] The server adjusts the manuscript based on the feedback.

[0155] The above are the detailed processing steps for each function of the Generative AI Contest Support System. Because the roles of the server, terminal, and user are clearly separated in each step, it is expected that the flow of the entire system will proceed smoothly.

[0156] Example 1

[0157] 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."

[0158] Conventional idea generation support systems and presentation material creation systems can only address user input from a single perspective, resulting in a lack of multifaceted refinement and optimization. Furthermore, automatic generation of presentation materials is problematic due to the difficulty of making appropriate adjustments based on specific user instructions, hindering efficient material creation. Therefore, there is a need for systems that can improve and evaluate ideas from multiple perspectives and support the creation of more flexible presentation materials.

[0159] 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.

[0160] In this invention, the server includes: means for receiving concepts entered by a user; means for distributing concepts to multiple AI agents with different characteristics, with each agent adding new perspectives and improvement suggestions; and means for integrating the concepts to which the new perspectives and improvement suggestions have been added and providing them to the user. This allows the user's ideas to be refined from multiple angles and improved to higher quality content. The server also includes means for evaluating the concepts submitted by the user based on evaluation criteria and means for returning the evaluation results to the user. This allows the submitted ideas to be objectively evaluated and the direction of improvement clarified. The server also includes means for analyzing presentation content and automatically generating visual materials, means for adjusting the visual materials based on user instructions, and means for generating and providing final presentation materials to the user. This allows presentation materials to be efficiently created and optimized in line with the user's intentions.

[0161] A "user" is a person or individual who accesses the system via a terminal and inputs concepts and instructions.

[0162] A "concept" refers to any or all of an idea or suggestion that a user inputs into the system.

[0163] "Multiple artificial intelligence agents with different characteristics" refers to multiple artificial intelligence-based software agents that have specific perspectives and characteristics and refine and consider ideas.

[0164] "Brushing up" refers to improving an idea or concept from multiple perspectives to raise its quality.

[0165] "Evaluation criteria" refers to the criteria or perspectives (e.g., creativity, feasibility, social impact, etc.) used to evaluate ideas and concepts.

[0166] "Visual materials" are visual documents such as slides, charts, and text generated for a presentation.

[0167] The embodiment of this invention is a system for effectively polishing and evaluating user ideas, creating presentation materials, generating mockup sites, and creating oral presentation scripts. This system operates based on communications between a server, terminals, and users.

[0168] The main hardware configuration of the system is as follows: The devices used by users include interface devices such as PCs, smartphones, and tablets. The server is a server machine equipped with a high-performance processor and large amount of memory, and it is also possible to use a cloud-based processing engine. The software consists of a generative AI model, a natural language processing (NLP) engine, and a database management system (DBMS).

[0169] Idea brush-up

[0170] 1. A user uses an input form on their device to enter their idea in text form into the system. For example, they enter their idea for a "new social networking app."

[0171] 2. The server receives the idea and stores it in a database. It then distributes the data to multiple AI agents (Dreamers, Enjoyers, Realists, and Critics). This process involves sending the idea data to each agent using an API.

[0172] 3. The Dreamer AI generates innovative ideas and big visions based on the prompt, "Add a new vision to this idea." For example, it adds "integration with VR."

[0173] 4. Based on the prompt, "Brush up this idea by adding entertainment elements," the Pleasure AI will output improvement proposals incorporating user experience and entertainment elements. For example, it will suggest "gamification elements."

[0174] 5. Based on the prompt, "Describe the technical steps required to realize this idea," the Realist AI will consider specific technical feasibility and propose technical implementations. For example, adding an "instant photo sharing function."

[0175] 6. Based on the prompt, "Please suggest the risks of this idea and how to improve it," the critic AI will extract risks and weaknesses and suggest ways to address them. For example, it will point out "privacy concerns."

[0176] 7. Finally, the server integrates the output of each agent and returns the integrated refinement idea to the user.

[0177] The first round of the contest

[0178] When a user submits an idea through an input form on their device, the server receives the idea and evaluates it based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.) using an AI model. The evaluation results are scored and sent back to the user as feedback.

[0179] Presentation file creation support

[0180] When a user inputs their presentation content from their device, the server receives it and analyzes it using a natural language processing engine. Based on the analysis results, it automatically selects a slide template and generates visual materials. If the user requests specific corrections or adjustments, the server adjusts the materials according to those instructions, generates the final presentation file, and provides it to the user.

[0181] Automatic generation of mockup sites

[0182] When a user inputs the specifications for a mockup website, the server receives them and selects a template. The server then automatically generates the mockup website and provides it to the user. For example, if a user requests, "Create a mockup website for a social networking app," the server generates a mockup website based on that information and provides it to the user as a URL or download link.

[0183] Presentation script creation

[0184] When a user inputs the content of their presentation and the desired presentation time, the server receives this, analyzes it, and allocates the appropriate time to each slide. Next, it automatically generates a presentation transcript and provides it to the user. If the user requests revisions, the server makes the revisions and provides it again. For example, if a user inputs a request for a "five-minute presentation," the server creates a transcript that fits within five minutes and provides it.

[0185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0186] Idea brush-up

[0187] Step 1:

[0188] The user enters his / her idea into the system using an input form on the terminal.

[0189] Input: The user inputs an idea (e.g., "a new social networking app") in text format through the device.

[0190] Output: The entered text data is sent to the server.

[0191] Step 2:

[0192] The server receives the ideas, stores them in a database, and distributes the data to each AI agent.

[0193] Input: Idea data sent from the device.

[0194] Data processing: The server stores idea data in a database and distributes the data to multiple AI agents via API.

[0195] Output: Idea data is sent to each AI agent.

[0196] Step 3:

[0197] The Dreamer AI adds new perspectives and visions.

[0198] Input: Dreamer AI receives idea data.

[0199] Prompt: "Add a new vision to this idea"

[0200] Data Computation: Generative AI models add new perspectives and visions to ideas.

[0201] Output: Ideas with added novelty.

[0202] Step 4:

[0203] The enjoyment-loving AI improves ideas by taking into account user experience and entertainment elements.

[0204] Input: The Hedonist AI receives idea data.

[0205] Prompt: "Refine this idea by adding entertainment value."

[0206] Data Computation: Generative AI models make suggestions to improve the user experience.

[0207] Output: Ideas with an added entertainment element.

[0208] Step 5:

[0209] A realistic AI will consider feasibility and make specific technical proposals.

[0210] Input: Realist AI receives idea data.

[0211] Prompt: "Describe the technical steps required to realize this idea."

[0212] Data computation: Generative AI models propose technical implementations.

[0213] Output: Ideas with added technical feasibility.

[0214] Step 6:

[0215] The AI ​​critic points out risks and weaknesses and suggests areas for improvement.

[0216] Input: Critic AI receives idea data.

[0217] Prompt: "What are the risks of this idea and how can you improve it?"

[0218] Data calculation: The generative AI model analyzes risks and weaknesses and outputs improvement proposals.

[0219] Output: Ideas with added risks and weaknesses and suggestions for their improvement.

[0220] Step 7:

[0221] The server integrates the output of each AI agent, generates final refinement ideas, and provides them to the user.

[0222] Input: Ideas with refinements submitted by each AI agent.

[0223] Data processing: The server integrates all the improvement proposals and generates the final refinement ideas.

[0224] Output: The consolidated refinement ideas are returned to the user.

[0225] The first round of the contest

[0226] Step 1:

[0227] The user submits an idea through an input form on the device.

[0228] Input: User inputs their idea and clicks the submit button.

[0229] Output: The submitted ideas are sent to the server.

[0230] Step 2:

[0231] The server evaluates the submitted ideas based on the evaluation criteria.

[0232] Input: Idea data sent from the device.

[0233] Data calculation: The server generates an evaluation score based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.).

[0234] Output: Scoring data as the evaluation result.

[0235] Step 3:

[0236] The server returns the evaluation results to the user.

[0237] Input: Scoring data of evaluation results.

[0238] Data processing: The server compiles the evaluation results and generates feedback for the user.

[0239] Output: The evaluation results are sent to the user via email or notification.

[0240] Presentation file creation support

[0241] Step 1:

[0242] The user inputs the presentation content into the system from the terminal.

[0243] Input: The user inputs the presentation content in text format.

[0244] Output: The input presentation content is sent to the server.

[0245] Step 2:

[0246] The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[0247] Input: Presentation content data sent from the device.

[0248] Data Computing: Using natural language processing techniques, the presentation content is analyzed, appropriate slide templates are selected, and visual aids are generated.

[0249] Output: The generated visual aid.

[0250] Step 3:

[0251] The user indicates specific modifications or adjustments and the server adjusts the file accordingly.

[0252] Input: The user inputs correction instructions for a specific part.

[0253] Data calculation: The server modifies the visual materials based on the user's instructions.

[0254] Output: The corrected visual.

[0255] Step 4:

[0256] The server generates the final presentation file and provides it to the user.

[0257] Input: Visual data after corrections are complete.

[0258] Data processing: Generate the final presentation file.

[0259] Output: The generated presentation file is provided to the user.

[0260] Automatic generation of mockup sites

[0261] Step 1:

[0262] The user inputs the specifications of the mockup site into the system from a terminal.

[0263] Input: The user enters the specifications of the mockup site (page structure, functional requirements, etc.).

[0264] Output: The entered specification information is sent to the server.

[0265] Step 2:

[0266] The server analyzes the input information and selects a template.

[0267] Input: Specification information sent from the device.

[0268] Data calculation: The server analyzes the specification information and selects an appropriate template based on it.

[0269] Output: The selected template.

[0270] Step 3:

[0271] The server automatically generates a mockup site and provides it to the user.

[0272] Input: Selected template and specification information.

[0273] Data processing: Automatically generate a mockup site.

[0274] Output: The generated mockup site is provided to the user as a URL or download link.

[0275] Presentation script creation

[0276] Step 1:

[0277] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[0278] Input: The user inputs the presentation content and desired presentation time.

[0279] Output: The entered data is sent to the server.

[0280] Step 2:

[0281] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0282] Input: Presentation content sent from the device and desired presentation time.

[0283] Data calculation: Analyze the presentation content and calculate the appropriate time allocation for each slide.

[0284] Output: Time allocation data.

[0285] Step 3:

[0286] The server automatically generates a presentation manuscript and provides it to the user.

[0287] Input: Time allocation data and analysis results.

[0288] Data processing: Automatically generate oral presentation manuscripts.

[0289] Output: The generated transcript is provided to the user.

[0290] Step 4:

[0291] The user makes a correction request and the server adjusts the manuscript accordingly.

[0292] Input: The user inputs correction instructions for the oral manuscript.

[0293] Data calculation: The server adjusts the manuscript based on the correction instructions.

[0294] Output: The revised transcript is provided to the user again.

[0295] (Application example 1)

[0296] 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."

[0297] To efficiently create high-quality content, modern content creators need to collect, evaluate, and ensure consistency in various ideas. However, many creators face challenges such as limited ability to refine their own concepts and few opportunities to receive objective evaluation and feedback. Furthermore, creating optimal presentation materials and mockup websites takes time and effort. As a result, creative work stagnates, risking a decline in content quality.

[0298] 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.

[0299] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, means for evaluating and refining different content formats, and means for further evaluating and improving the idea integrated with improvements suggested by the user. This enables content creators to refine their ideas by receiving feedback from multiple perspectives and quickly create high-quality content.

[0300] "Means for receiving user-input ideas" refers to a function or module that receives, in digital form, ideas or concepts that users provide to the system.

[0301] "Multiple AI agents with different characteristics" are heterogeneous AI models, each with a specific perspective and role, that evaluate and improve ideas from different perspectives.

[0302] "Means for brushing up ideas" is a function that analyzes received ideas from multiple angles and adds improvements and new suggestions to further develop the ideas.

[0303] "Means for integrating refined ideas" is a function that synthesizes feedback and improvements from each AI agent and brings them together into a single integrated idea.

[0304] "Means to provide to users" refers to the ability to communicate the integrated ideas and proposed improvements to users in a clear and understandable format.

[0305] "A means to evaluate and refine different content formats" is a function that evaluates various forms of content, such as videos, articles, and podcasts, and suggests appropriate improvements for each.

[0306] "Suggestions for improving content quality based on feedback" is a function that provides specific advice for further improving content based on the evaluations and improvements received from users.

[0307] "Means for analyzing presentation content and automatically generating slides and materials" refers to a function that understands the content of a user's presentation and automatically creates appropriate slides and materials.

[0308] "Means for adjusting slides and materials based on user instructions" refers to a function for correcting and adjusting the content of already generated slides and materials in accordance with user requests and instructions.

[0309] The "means for automatically generating a content preview site" is a function that automatically creates a simple website or a preview page based on the user's ideas and content.

[0310] The present invention is a system that evaluates and improves ideas input by users from multiple angles and automatically generates high-quality content. Detailed embodiments of the system are described below.

[0311] System Configuration

[0312] The system operates based on communication between the server, terminals, and users, and uses smartphones (iOS or Android devices), Python, and OpenAI APIs as its main hardware and software.

[0313] Program processing

[0314] 1. A means of receiving user-entered ideas

[0315] Users input ideas into the system using their smartphones or PCs, and the ideas are sent to the server via the platform or application user interface.

[0316] 2. A way to share and refine ideas

[0317] The server distributes the received ideas to multiple AI agents with different characteristics. Each agent analyzes the idea from a specific perspective and generates improvements and new proposals. Specifically, the Dreamer AI is responsible for creative vision, the Hedonist AI for user experience, the Realist AI for feasibility, and the Critic AI for risk assessment.

[0318] 3. A way to integrate refined ideas

[0319] The feedback from each agent is integrated to generate a single improved idea. This integration process is carried out on the server and is reflected in the final result provided to the user.

[0320] 4. A way to evaluate and refine different content formats

[0321] The server provides feedback on various content formats, including videos, articles, and podcasts, and suggests appropriate improvements for each format, providing users with instructions to improve the quality of their content.

[0322] 5. A way to automatically generate a preview site for your content

[0323] The server automatically creates mockups and preview sites based on the generated ideas. These preview sites can be viewed in a browser, allowing users to see the final form of the content.

[0324] Usage example

[0325] As a specific example, a case will be described in which a user inputs an idea for an "introductory video for an environmentally friendly product." When the user inputs the idea into the system, the following process is carried out.

[0326] Visionary AI adds "vision of futuristic eco-technology"

[0327] The Hedonist AI recommends "visually appealing effects and music"

[0328] Realistic AI takes into account "specific product specifications and practical examples"

[0329] Critic AI points out "privacy and legal concerns"

[0330] This provides users with consolidated feedback, which allows them to create optimized content.

[0331] Prompt Sentence Examples

[0332] As a dreamer, please provide feedback on the following idea: A new cooking recipe sharing app

[0333] In this way, a system is provided that allows content creators to receive feedback from multiple perspectives and quickly create high-quality content.

[0334] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0335] Step 1:

[0336] The ideas entered by the user are sent from the device to the server. The user uses a smartphone or computer to enter their ideas and concepts into the system in text format. The entered ideas are sent to the server and stored in a database.

[0337] Input: Textual ideas from users

[0338] Output: Ideas stored in a database on the server

[0339] Step 2:

[0340] The server distributes ideas to multiple AI agents. The server retrieves ideas from a database and sends them to each agent (Dreamer, Enjoyer, Realist, Critic).

[0341] Input: Ideas retrieved from the database

[0342] Output: Ideas distributed to each agent

[0343] Step 3:

[0344] The Dreamer AI analyzes the idea and proposes a new creative vision. The server sends the idea to the Dreamer AI, and the Dreamer AI generates new visions and creative elements based on the idea.

[0345] Input: Ideas sent to the Dreamer AI

[0346] Output: Creative suggestions from the Dreamer AI

[0347] Step 4:

[0348] The Pleasure AI improves the idea by taking into account the user experience. The server sends the idea to the Pleasure AI, which then generates a proposal that incorporates entertainment elements and user experience into the idea.

[0349] Input: Idea sent to the Hedonist AI

[0350] Output: Suggestions from the Enjoyer AI to improve the user experience

[0351] Step 5:

[0352] The Realist AI considers the feasibility of the idea. The server sends the idea to the Realist AI, which then generates a concrete proposal that is feasible from a technical standpoint.

[0353] Input: Ideas sent to the Realist AI

[0354] Output: Feasible proposals from a realist AI

[0355] Step 6:

[0356] The critic AI evaluates the risk of ideas. The server sends ideas to the critic AI, which then points out risks and weaknesses and suggests ways to improve them.

[0357] Input: Ideas sent to the critic AI

[0358] Output: Risk assessment and improvement suggestions from the critic AI

[0359] Step 7:

[0360] The server integrates the feedback from each agent. The server receives feedback from each agent and synthesizes it into a single integrated idea, reconciling overlapping and contradictory points.

[0361] Input: Feedback from each agent

[0362] Output: Unified refinement proposal

[0363] Step 8:

[0364] The server provides the user with the integrated idea, which the user can then review and use. The user can then make further modifications as needed.

[0365] Input: Integrated refinement proposal

[0366] Output: Consolidated ideas provided to the user

[0367] Step 9:

[0368] The server evaluates and refines the content according to its format. It provides appropriate evaluation and feedback based on the format of the user-generated content (video, article, podcast, etc.) and generates suggestions to further improve the content.

[0369] Input: The format of the content provided by the user

[0370] Output: Evaluation and suggestions for improving the content

[0371] Step 10:

[0372] The server provides users with suggestions for improving the quality of content based on their feedback. The server reflects the feedback from each agent and proposes specific improvement actions to the user.

[0373] Input: Feedback from each agent

[0374] Output: Suggestions for improving the content provided to the user

[0375] 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.

[0376] This embodiment of the invention combines an emotion engine with a specialized system for supporting generative AI contests, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[0377] System Overview

[0378] The system has the following main functions:

[0379] 1. Idea brush-up (virtual brainstorming)

[0380] 2. Final round of the contest

[0381] 3. Presentation file creation support

[0382] 4. Automatic generation of mockup sites

[0383] 5. Preparation of oral presentation script

[0384] 6. Emotion Recognition and Adaptation with Emotion Engine

[0385] 1. Idea brush-up (virtual brainstorming)

[0386] 1. The user inputs an idea into the system from a terminal.

[0387] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[0388] 3. Visionary AI adds new ideas and big visions to ideas.

[0389] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[0390] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[0391] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[0392] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[0393] 8. The emotion engine analyzes the user's emotional data and makes adjustments based on the AI ​​agent's feedback.

[0394] Example: When a user suggests a "new social networking app," the Dreamer AI suggests "integration with VR," the Enjoyer AI suggests "gamification elements," the Realist AI adds "instant photo sharing functionality," and the Critic AI points out "privacy concerns." If the user expresses positive emotions toward the suggestion, the emotion engine takes this into account to further strengthen the idea.

[0395] 2. Final round of the contest

[0396] 1. The user submits an idea to the system from their device.

[0397] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0398] 3. The server returns the evaluation results to the user.

[0399] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[0400] 3. Presentation file creation support

[0401] 1. The user inputs the presentation content into the system from their device.

[0402] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[0403] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[0404] 4. The emotion engine analyzes the user's emotion data and adjusts the design and content of the material based on the user's emotions.

[0405] 5. The server generates the final presentation file and serves it to the user.

[0406] Example: A user inputs "business plan" and the server automatically generates slides. If the user says "add a graph to this part," the server adds the graph. Also, if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[0407] 4. Automatic generation of mockup sites

[0408] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[0409] 2. The server analyzes the input information and selects a template for the mockup site.

[0410] 3. The server automatically generates a mockup site.

[0411] 4. The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[0412] 5. The server serves the generated mockup site to the user.

[0413] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction, and the emotion engine observes the user's reaction, adjusts the color scheme and layout, and delivers the final site to the user.

[0414] 5. Preparation of oral presentation script

[0415] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[0416] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0417] 3. The server automatically generates the oral presentation script.

[0418] 4. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[0419] 5. The server provides the generated oral transcript to the user.

[0420] 6. The server adjusts the manuscript based on user feedback.

[0421] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral script that fits within 5 minutes. If the user instructs the server to "explain this part in more detail," the server adds content that details the relevant part. Also, if the user is nervous, the emotion engine detects this and generates a script with a more relaxed tone.

[0422] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals. By combining it with an emotion engine, it is expected to provide output optimized for the user's emotional state, improving the user experience.

[0423] The processing flow will be explained below.

[0424] Idea brush-up (including emotion engine)

[0425] Step 1:

[0426] The user inputs an idea from a terminal and sends it to the server.

[0427] Step 2:

[0428] A server receives ideas from users.

[0429] Step 3:

[0430] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[0431] Step 4:

[0432] The Visionary AI adds new ideas and big visions to ideas, for example, proposing innovative technologies and generating future-oriented scenarios.

[0433] Step 5:

[0434] The Pleasure AI adds elements to ideas that enrich the user experience, such as suggesting easy-to-use interfaces and entertainment elements.

[0435] Step 6:

[0436] Realistic AI considers the feasibility of ideas and gives them technical realization, for example proposing a technology stack and designing a prototype.

[0437] Step 7:

[0438] The AI ​​critics point out risks and weaknesses in ideas and suggest areas for improvement, such as legal risks and market concerns.

[0439] Step 8:

[0440] The emotion engine analyzes the user's emotional data, for example, whether the user is excited or skeptical about an idea.

[0441] Step 9:

[0442] The server integrates feedback from each AI agent and generates refined ideas.

[0443] Step 10:

[0444] The emotion engine adjusts the final ideas based on the user's emotional data, for example adding more challenging ideas if the user is excited.

[0445] Step 11:

[0446] The server is integrated and sends the coordinated ideas back to the user.

[0447] The first round of the contest

[0448] Step 1:

[0449] The user inputs an idea from a terminal and sends it to the server.

[0450] Step 2:

[0451] A server receives the submitted ideas.

[0452] Step 3:

[0453] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0454] Step 4:

[0455] The server assigns a score to each evaluation item.

[0456] Step 5:

[0457] The server calculates the overall score.

[0458] Step 6:

[0459] The server returns the evaluation results and feedback to the user.

[0460] Presentation file creation support

[0461] Step 1:

[0462] The user inputs the presentation content from the terminal and sends it to the server.

[0463] Step 2:

[0464] The server receives and analyzes the presentation content.

[0465] Step 3:

[0466] The server automatically selects a slide template.

[0467] Step 4:

[0468] The server generates the materials required for the presentation.

[0469] Step 5:

[0470] The user specifies the range or gives verbal instructions, which are then sent to the server.

[0471] Step 6:

[0472] The server adjusts the slides and materials based on the user's instructions.

[0473] Step 7:

[0474] The emotion engine analyzes the user's emotional data and adjusts the design and content of the materials based on the user's emotions. For example, if the user is nervous, it uses colors and designs that are relaxing.

[0475] Step 8:

[0476] The server generates the final presentation file and provides it to the user.

[0477] Automatic generation of mockup sites

[0478] Step 1:

[0479] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[0480] Step 2:

[0481] The server receives and analyzes the input information.

[0482] Step 3:

[0483] The server selects an appropriate mockup site template.

[0484] Step 4:

[0485] The server automatically generates a mockup site.

[0486] Step 5:

[0487] The emotion engine analyzes user emotion data and adjusts the site design and element placement. For example, if a user expresses positive emotions, the engine adds design elements that emphasize those emotions.

[0488] Step 6:

[0489] The server provides the generated mockup site to the user.

[0490] Presentation script creation

[0491] Step 1:

[0492] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[0493] Step 2:

[0494] The server receives and analyzes the presentation content and desired time.

[0495] Step 3:

[0496] The server calculates the appropriate time allocation for each slide or section.

[0497] Step 4:

[0498] The server automatically generates a presentation transcript.

[0499] Step 5:

[0500] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript. For example, if the user is nervous, the engine will generate a manuscript with a relaxed tone.

[0501] Step 6:

[0502] The server provides the generated oral transcript to the user.

[0503] Step 7:

[0504] The user provides feedback and sends it to the server.

[0505] Step 8:

[0506] The server adjusts the manuscript based on the feedback.

[0507] The above are the detailed processing steps for each function of the generative AI contest support system that combines an emotion engine. In each step, the roles of the server, terminal, and user are clearly separated, and it is expected that the overall system will proceed smoothly. The incorporation of an emotion engine makes it possible to adapt to the user's emotional state, providing more effective and personalized support.

[0508] Example 2

[0509] 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."

[0510] This invention relates to a system that can provide optimal feedback and output by taking into account the user's emotional state during processes such as refining and evaluating ideas in contests and supporting the creation of presentations. Conventional systems often refine ideas or create presentation materials without taking the user's emotions into account, making it difficult to achieve user-friendly and effective results. Furthermore, because they are unable to optimally adjust to the user's emotional state, they are unable to improve user satisfaction or the quality of proposals.

[0511] 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.

[0512] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, and emotion engine means for analyzing the user's emotion data and making adjustments based on feedback from the AI ​​agents. This makes it possible to provide feedback and output optimized for the user's emotional state, enabling user-friendly and effective idea refinement and the creation of presentation materials.

[0513] "User" refers to the entity that inputs ideas and presentation content into the system and receives feedback and output based on them.

[0514] "Terminal" refers to an apparatus or device for transmitting information entered by a user to a system.

[0515] "Server" refers to a central system that receives and processes information sent by users.

[0516] An "artificial intelligence agent" is a program that has specific characteristics and roles, analyzes input information, and refines ideas based on those characteristics.

[0517] A "dreamer agent" refers to an artificial intelligence agent that has the ability to add new ideas and big visions.

[0518] A "pleasure agent" refers to an artificial intelligence agent that has the ability to improve ideas by taking into account user experience and entertainment elements.

[0519] A "realist agent" is an artificial intelligence agent that has the ability to consider the feasibility of ideas and bring them to technical realization.

[0520] A "critic agent" is an artificial intelligence agent that has the ability to point out the risks and weaknesses of an idea and suggest areas for improvement.

[0521] An "emotion engine" is a program that analyzes the user's emotional data and makes optimal adjustments based on feedback from the AI ​​agent.

[0522] "Brushing up" refers to the process of making improvements and additions to an input idea to make it better.

[0523] "Presentation" refers to materials and presentations that visually and verbally express the information or proposals that a user wants to show.

[0524] A "mockup site" is a prototype of a website or application that does not replicate actual functionality but instead provides a visual representation of the design and user interface.

[0525] "Preliminary judging" refers to the first idea evaluation process in a contest.

[0526] This invention combines an emotion engine with a specialized system for generative AI contest support, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[0527] To implement this system, the following major components are required:

[0528] 1. Idea brush-up (virtual brainstorming)

[0529] 2. Final round of the contest

[0530] 3. Presentation file creation support

[0531] 4. Automatic generation of mockup sites

[0532] 5. Preparation of oral presentation script

[0533] 6. Emotion Recognition and Adaptation with Emotion Engine

[0534] Idea brush-up (virtual brainstorming)

[0535] When a user inputs a new idea into the system from a terminal, the server receives the idea. The server distributes the idea to several artificial intelligence (AI) agents with different characteristics: the Dreamer, the Hedonist, the Realist, and the Critic. Each AI agent behaves according to its characteristics as follows:

[0536] Visionary agents add new ideas and big visions to ideas.

[0537] The hedonist agent improves ideas by taking into account user experience and entertainment factors.

[0538] The realist agent considers the feasibility of the idea and gives it technical realization.

[0539] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[0540] The server integrates these outputs and presents the refined idea to the user. The emotion engine also analyzes the user's emotional data and makes adjustments based on the AI ​​agents' feedback. For example, if a user suggests a "new social media app," the dreamer agent might suggest "integration with VR," the hedonist agent might suggest "gamification elements," the realist agent might add "instant photo sharing functionality," and the critic agent might point out "privacy concerns." If the user expresses positive emotions toward the proposal, the emotion engine takes this into account to further strengthen the idea.

[0541] The first round of the contest

[0542] When a user submits an idea to the system from their device, the server receives the idea. The server evaluates the idea based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.) and returns the evaluation results to the user. For example, if a user submits an "environmentally friendly product," the server will evaluate it based on creativity, feasibility, and social impact, and provide the evaluation results as feedback to the user.

[0543] Presentation file creation support

[0544] When a user inputs the content of their presentation into the system from their device, the server analyzes the content, automatically selects a slide template, and generates the presentation material. The user specifies the range or gives verbal instructions, and the server adjusts the file accordingly. The emotion engine also analyzes the user's emotional data and adjusts the design and content of the presentation material based on the user's emotions. The server generates the final presentation file and provides it to the user. For example, a user inputs "business plan" and the server automatically generates slides. If the user instructs "add a graph to this part," the server adds the graph, and if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[0545] Automatic generation of mockup sites

[0546] When a user inputs the specifications of a mockup site into the system from their device, the server analyzes the input information and selects a template for the mockup site. The server then automatically generates the mockup site, and the emotion engine analyzes the user's emotional data and adjusts the site's design and element placement. Finally, the server provides the generated mockup site to the user. For example, if a user instructs the server to "create a mockup site for a social networking app," the server generates the mockup site based on that information, and the emotion engine adjusts the color scheme and layout based on the user's reaction, and provides the final site to the user.

[0547] Presentation script creation

[0548] When a user inputs the presentation content and desired presentation time into the system from their device, the server analyzes the presentation content and calculates the appropriate time allocation for each slide and section. The server then automatically generates an oral presentation script. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the script. The final oral presentation script is provided to the user, and the server adjusts the script based on feedback from the user. For example, if a user inputs a request for a "five-minute presentation," the server will create and provide an oral presentation script that fits within five minutes. If the user instructs the server to "explain this part in more detail," the server will add content that details the relevant part, and if the user is nervous, the emotion engine will detect this and generate a script with a more relaxed tone.

[0549] In this way, the present invention can provide optimal feedback and output according to the user's emotional state, thereby improving the quality of ideas, reducing the burden of creating presentation materials, and being extremely useful in making competitive proposals.

[0550] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0551] Idea brush-up (virtual brainstorming)

[0552] Step 1:

[0553] The user inputs an idea from the terminal.

[0554] Enter: an idea for a new social media app.

[0555] Output: Idea data sent to the system.

[0556] Specific operation: The user enters their idea for a "new SNS app" into the input form on the device and clicks the "Submit" button.

[0557] Step 2:

[0558] The server receives the idea.

[0559] Input: Idea data submitted by the user.

[0560] Output: Idea data distributed to multiple artificial intelligence agents with different characteristics.

[0561] Specific operation: The server analyzes the received idea data and sends it to the dreamer agent, the hedonist agent, the realist agent, and the critic agent.

[0562] Step 3:

[0563] Visionary agents add new ideas and big visions to your ideas.

[0564] Input: Idea data sent to the Dreamer Agent.

[0565] Output: Idea data with new ideas and visions added.

[0566] Specific operation: In response to the prompt "Propose a new vision or idea for a social networking app," the dreamer agent generates and outputs an idea for VR integration.

[0567] Step 4:

[0568] The hedonistic agent considers user experience and entertainment elements to improve the idea.

[0569] Input: Idea data sent to the hedonist agent.

[0570] Output: Idea data with improved user experience and entertainment elements added.

[0571] Specific operation: The hedonist agent proposes gamification elements based on the prompt "Elements that will enrich the user experience" and outputs them.

[0572] Step 5:

[0573] A realist agent considers the feasibility of the idea and gives it technical realization.

[0574] Input: Idea data sent to the Realist agent.

[0575] Output: Technically embodied idea data.

[0576] Specific behavior: The realist agent receives the prompt "technically feasible specific proposal," generates a proposal to add an instant photo sharing function, and outputs it.

[0577] Step 6:

[0578] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[0579] Input: Idea data sent to the critic agent.

[0580] Output: Idea data with risks and weaknesses pointed out and improvements added.

[0581] Specific behavior: Based on the prompt "Point out risks and weaknesses," the critic agent points out privacy concerns and outputs suggestions for improvement.

[0582] Step 7:

[0583] The server integrates the output of each agent, generates refined ideas, and provides them to the user.

[0584] Input: Refined idea data sent by each agent.

[0585] Output: A final, consolidated and refined idea.

[0586] Specific operation: The server integrates the data received from each agent and generates a final idea to send back to the user.

[0587] Step 8:

[0588] The emotion engine analyzes the user's emotional data and makes adjustments based on the feedback.

[0589] Input: User emotion data and final idea data.

[0590] Output: Final ideas adjusted based on user sentiment.

[0591] Specific operation: The emotion engine analyzes the user's emotion data, and if the user expresses positive emotions, it makes adjustments to further strengthen the idea.

[0592] The first round of the contest

[0593] Step 1:

[0594] A user submits an idea to the system from a terminal.

[0595] Input: Idea data to be submitted.

[0596] Output: The idea data sent to the system.

[0597] Specific operation: The user enters their idea for an "environmentally friendly product" into the input form on the device and clicks the "Submit" button.

[0598] Step 2:

[0599] The server evaluates the ideas based on the contest's evaluation criteria.

[0600] Input: Submitted idea data.

[0601] Output: Evaluation results based on the evaluation criteria.

[0602] Specific operation: The server evaluates the received idea data based on evaluation criteria (creativity, feasibility, social impact, etc.) and tally up the evaluation scores.

[0603] Step 3:

[0604] The server returns the evaluation results to the user.

[0605] Input: Evaluation result data.

[0606] Output: The evaluation results that are displayed to the user.

[0607] Specific operation: The server generates the evaluation results, displays them to the user, and sends them as feedback.

[0608] Presentation file creation support

[0609] Step 1:

[0610] The user inputs the presentation content into the system from the terminal.

[0611] Input: Presentation content data.

[0612] Output: Presentation content data sent to the system.

[0613] Specific operation: The user enters the details of the "business plan" into the input form on the terminal and clicks the "Submit" button.

[0614] Step 2:

[0615] The server analyzes the presentation content, automatically selects a slide template, and generates materials.

[0616] Input: Presentation content data.

[0617] Output: Selected slide templates and generated data.

[0618] Specific operation: The server analyzes the presentation content, selects an appropriate slide template, and generates the materials.

[0619] Step 3:

[0620] The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[0621] Input: Range specification or verbal instruction data from the user.

[0622] Output: Adjusted presentation data.

[0623] Specific operation: When the user instructs, for example, "Add a graph to this part," the server adds the graph based on that instruction.

[0624] Step 4:

[0625] The emotion engine analyzes the user's emotional data and adjusts the design and content of the document.

[0626] Input: User emotion data and presentation data.

[0627] Output: Presentation materials tailored based on user sentiment.

[0628] What it does: The emotion engine analyzes the user's emotions and, for example, if the user is excited, adds more attractive visualizations to the slides.

[0629] Step 5:

[0630] The server generates the final presentation file and provides it to the user.

[0631] Input: Adjusted presentation data.

[0632] Output: Final presentation file.

[0633] What happens: The server assembles the final presentation file and serves it to the user.

[0634] Automatic generation of mockup sites

[0635] Step 1:

[0636] The user inputs the specifications of the mockup site into the system from a terminal.

[0637] Input: Mockup site specification data.

[0638] Output: The specification data sent to the system.

[0639] Specific operation: The user enters, for example, "I would like you to create a mockup site for a social networking app" into the input form on the device and clicks the "Submit" button.

[0640] Step 2:

[0641] The server analyzes the input information and selects a template for the mockup site.

[0642] Input: Mockup site specification data.

[0643] Output: The selected template data.

[0644] Specific operation: The server analyzes the input specification data and selects an appropriate mockup site template.

[0645] Step 3:

[0646] The server automatically generates a mockup site.

[0647] Input: Selected template data and specification data.

[0648] Output: An automatically generated mockup site.

[0649] What happens: The server generates a mockup site based on the template and specification data.

[0650] Step 4:

[0651] The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[0652] Input: User emotion data and generated mockup site.

[0653] Output: A tailored mockup site.

[0654] Specific behavior: The emotion engine analyzes the user's emotion data and adjusts the color scheme and layout.

[0655] Step 5:

[0656] The server provides the generated mockup site to the user.

[0657] Input: The adjusted mockup site.

[0658] Output: The final mockup site that is provided to the user.

[0659] Specific operation: The server generates the final mockup site and provides it to the user.

[0660] Presentation script creation

[0661] Step 1:

[0662] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[0663] Input: Presentation content data and desired time data.

[0664] Output: Presentation content and desired time data sent to the system.

[0665] Specific operation: The user enters the presentation content and desired time (e.g., "5-minute presentation") into the input form on the device and clicks the "Send" button.

[0666] Step 2:

[0667] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0668] Input: Presentation content data and desired time data.

[0669] Output: A presentation outline based on appropriate time allocation.

[0670] What it does: The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0671] Step 3:

[0672] The server automatically generates a presentation transcript.

[0673] Input: Presentation content data and time allocation data.

[0674] Output: The generated oral presentation transcript.

[0675] Specific operation: The server automatically creates a presentation manuscript based on the time allocation.

[0676] Step 4:

[0677] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[0678] Input: User emotion data and generated oral presentation script.

[0679] Output: Adjusted oral presentation transcript.

[0680] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the manuscript according to the emotion, such as by using a relaxed tone of voice.

[0681] Step 5:

[0682] The server provides the generated oral transcript to the user.

[0683] Input: Adjusted oral presentation transcript.

[0684] Output: The final presentation transcript provided to the user.

[0685] Specific operation: The server generates the final presentation transcript and provides it to the user.

[0686] Step 6:

[0687] The server adjusts the manuscript according to the user's feedback.

[0688] Input: Feedback data from users.

[0689] Output: Adjusted oral presentation transcript.

[0690] Specific operation: When the user gives feedback such as "Please explain this part in more detail," the server adds or corrects the relevant part in detail based on the user's instructions.

[0691] This process not only allows users to improve the quality of their ideas, but also allows them to receive feedback and output that is optimized for their emotional state, enabling them to create effective presentations and attractive mockup sites.

[0692] (Application example 2)

[0693] 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."

[0694] There is a need for technology to improve productivity and safety when using assistive robots in factories today. Furthermore, there are few systems that provide feedback or suggest work improvements that take into account the emotional state of workers, making it difficult to provide appropriate assistance based on their emotional state. There is a need for a system that can solve this problem.

[0695] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0696] In this invention, the server includes a means for analyzing the user's emotional data and adjusting the feedback of the generating AI agent based on the emotion, a means for receiving ideas input by the user, a means for distributing the ideas to multiple AI agents with different characteristics and having each agent refine the idea, and a means for integrating the refined ideas and providing them to the user. This makes it possible to propose appropriate work improvements and improve safety based on the worker's emotional state.

[0697] 1. "User" means a person or group who uses the system to input ideas, evaluate them, and receive feedback.

[0698] 2. "Emotional data" refers to information that indicates a user's emotional state, such as text, audio, images, or data obtained from sensors.

[0699] 3. "Generative AI agents" are multiple artificial intelligences that analyze users' ideas from different perspectives and provide improvement suggestions and feedback.

[0700] 4. "Feedback" refers to improvement suggestions and evaluation results for ideas refined by the generating AI agent.

[0701] 5. "Agents with different characteristics" are AIs that analyze ideas from different perspectives and criteria, such as dreamers, hedonists, realists, and critics.

[0702] 6. "Idea brush-up" is a process in which multiple AI agents improve an idea entered by a user and turn it into a better version.

[0703] 7. "Idea distribution" is the process of sending a user's input ideas to multiple artificial intelligence agents with different characteristics.

[0704] 8. A "system" is a complex collection of machines and software that handles everything from user idea input to evaluation, refinement, and feedback.

[0705] 9. A "refined idea" is an idea that has been improved by multiple AI agents with different perspectives.

[0706] 10. "Presentation Materials" means materials such as slides and documents used by Users when giving presentations.

[0707] 11. "Final presentation file" refers to the presentation materials that are finally generated based on the user's instructions and emotional data.

[0708] This paper describes a system applied to an assistive robot that supports workers in a factory. The system's program processing is explained in natural language below, and the specific names of the hardware and software used are specified.

[0709] Hardware:

[0710] 1. Emotion data acquisition devices: Wearable devices and cameras for acquiring workers' emotional data.

[0711] 2. Assistive robots: Physical robots that interact directly with workers.

[0712] software:

[0713] 1. Emotion engine: A module that analyzes user emotion data.

[0714] 2. Generative AI Agents: Artificial intelligence agents with multiple characteristics (e.g., Dreamer AI, Hedonist AI, Realist AI, Critic AI).

[0715] 3. Integrated system: A system that integrates feedback from different agents and provides it to the user.

[0716] Data processing and calculation:

[0717] 1. Emotion data acquisition: The terminal acquires the worker's emotion data from a wearable device or camera.

[0718] 2. Emotion analysis: The server analyzes the emotion data using an emotion engine to determine the worker's current emotional state.

[0719] 3. Idea sharing and polishing:

[0720] The server distributes work improvement ideas to the generated AI agents.

[0721] Each agent improves the idea from a different perspective and generates feedback.

[0722] 4. Feedback integration: The server integrates the feedback from each generated AI agent and provides it to the user.

[0723] 5. Emotion-based adjustment: The emotion engine adjusts the generated feedback and presentation materials based on the user's emotional state.

[0724] Examples:

[0725] If a worker feels "tired today," enter the following prompt:

[0726] Prompt: "I'm feeling tired today. How can I improve my work efficiency?"

[0727] Based on this prompt, the server does the following:

[0728] The emotion engine detects "fatigue" and notifies the generative AI agent of this emotional state.

[0729] The generative AI agent generates specific support suggestions, such as "take a break" or "recheck your work procedures."

[0730] The server integrates these suggestions and provides feedback to the worker via the assist robot.

[0731] Ultimately, workers can receive appropriate support according to their emotional state, improving work efficiency and safety.

[0732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0733] Step 1:

[0734] The user inputs emotional data using a terminal. For example, the user inputs, "I feel tired today. How can I improve my work efficiency?" This input becomes the initial data for the system.

[0735] Step 2:

[0736] The device collects emotional data and sends it to the server. The input emotional data is text information that indicates the emotional state. The device processes the data and converts it into a format that can be sent to the server. The input data is sent to the server, and the server receives the data for further processing.

[0737] Step 3:

[0738] The server analyzes the emotional data using an emotion engine. The server accepts the analyzed emotional data and determines the emotional state, such as "fatigue" or "stress." The input in this step is "user's emotional data," and the output is "analyzed emotional state."

[0739] Step 4:

[0740] The server distributes work improvement ideas to the generating AI agents. Based on the analyzed emotional state, the server sends requests to the generating AI agents for appropriate improvement proposals. The input is the "analyzed emotional state," and the output is "requests to multiple generating AI agents."

[0741] Step 5:

[0742] The generative AI agent generates work improvement suggestions based on the user's emotional state. Each agent (Dreamer AI, Hedonist AI, Realist AI, Critic AI) generates ideas from their own perspective. The input is a "request from the server" and the output is a "suggestion for work improvement."

[0743] Step 6:

[0744] The server aggregates the feedback from the generating AI agents. The server combines the feedback received from each generating AI agent into a single aggregated proposal. The input is the "feedback from the generating AI agent" and the output is the "aggregated proposal."

[0745] Step 7:

[0746] The server sends the integrated suggestion to the assist robot, which uses this information to provide feedback to the user. The input is the "integrated suggestion" and the output is "feedback information to the assist robot."

[0747] Step 8:

[0748] The assist robot makes a suggestion to the user. For example, the assist robot may suggest to the user, "You seem tired. I recommend you take a break." The input is "feedback information from the server," and the output is "feedback to the user."

[0749] 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.

[0750] 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.

[0751] 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.

[0752] [Second embodiment]

[0753] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0754] 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.

[0755] 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).

[0756] 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.

[0757] 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.

[0758] 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).

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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."

[0765] The embodiment of this invention is a specialized system for supporting generative AI contests, which effectively refines users' ideas and assists in the creation of presentation materials, mockup sites, and oral manuscripts. This system operates based on communications between a server, terminals, and users.

[0766] System Overview

[0767] The system has the following main functions:

[0768] 1. Idea brush-up (virtual brainstorming)

[0769] 2. Final round of the contest

[0770] 3. Presentation file creation support

[0771] 4. Automatic generation of mockup sites

[0772] 5. Preparation of oral presentation script

[0773] 1. Idea brush-up (virtual brainstorming)

[0774] 1. The user inputs an idea into the system from a terminal.

[0775] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[0776] 3. Visionary AI adds new ideas and big visions to ideas.

[0777] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[0778] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[0779] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[0780] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[0781] Example: When a user suggests a "new social networking app," the dreamer AI adds "VR integration," the enjoyer AI suggests "gamification elements," the realist AI adds "instant photo sharing functionality," and the critic AI points out "privacy concerns." The final integrated idea is sent back to the user.

[0782] 2. Final round of the contest

[0783] 1. The user submits an idea to the system from their device.

[0784] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0785] 3. The server returns the evaluation results to the user.

[0786] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[0787] 3. Presentation file creation support

[0788] 1. The user inputs the presentation content into the system from their device.

[0789] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[0790] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[0791] 4. The server generates the final presentation file and serves it to the user.

[0792] Example: A user inputs a "business plan" and the server automatically generates slides. When the user instructs "add a graph to this section," the server adds the graph.

[0793] 4. Automatic generation of mockup sites

[0794] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[0795] 2. The server analyzes the input information and selects a template for the mockup site.

[0796] 3. The server automatically generates a mockup site and provides it to the user.

[0797] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction and provides it to the user.

[0798] 5. Preparation of oral presentation script

[0799] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[0800] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[0801] 3. The server automatically generates a presentation transcript and provides it to the user.

[0802] 4. The server adjusts the manuscript based on user feedback.

[0803] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral manuscript that fits within 5 minutes. When the user instructs, "Please explain this part in more detail," the server adds content that details the relevant part.

[0804] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals.

[0805] The processing flow will be explained below.

[0806] Idea brush-up (virtual brainstorming)

[0807] Step 1:

[0808] The user inputs an idea from a terminal and sends it to the server.

[0809] Step 2:

[0810] A server receives ideas from users.

[0811] Step 3:

[0812] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[0813] Step 4:

[0814] The Visionary AI adds new ideas and big visions to ideas, specifically proposing future-oriented scenarios and new concepts to ideas.

[0815] Step 5:

[0816] The Hedonist AI adds elements to ideas that enrich the user experience, such as entertainment elements and improvements to user interaction.

[0817] Step 6:

[0818] Realistic AI considers the feasibility of ideas and gives them technical specificity, for example by proposing a tech stack and adding prototype designs.

[0819] Step 7:

[0820] The AI ​​critic points out the risks and weaknesses of an idea and suggests ways to improve it, specifically highlighting legal risks and market concerns.

[0821] Step 8:

[0822] The server integrates feedback from the four AI agents and generates refined ideas.

[0823] Step 9:

[0824] The server returns the synthesized ideas to the user.

[0825] The first round of the contest

[0826] Step 1:

[0827] The user inputs an idea from a terminal and sends it to the server.

[0828] Step 2:

[0829] A server receives the submitted ideas.

[0830] Step 3:

[0831] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[0832] Step 4:

[0833] The server assigns a score to each evaluation item.

[0834] Step 5:

[0835] The server calculates the overall score.

[0836] Step 6:

[0837] The server returns the evaluation results and feedback to the user.

[0838] Presentation file creation support

[0839] Step 1:

[0840] The user inputs the presentation content from the terminal and sends it to the server.

[0841] Step 2:

[0842] The server receives and analyzes the presentation content.

[0843] Step 3:

[0844] The server automatically selects a slide template.

[0845] Step 4:

[0846] The server generates the materials required for the presentation.

[0847] Step 5:

[0848] The user specifies the range or gives verbal instructions, which are then sent to the server.

[0849] Step 6:

[0850] The server adjusts the slides and materials based on the user's instructions.

[0851] Step 7:

[0852] The server generates the final presentation file and provides it to the user.

[0853] Automatic generation of mockup sites

[0854] Step 1:

[0855] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[0856] Step 2:

[0857] The server receives and analyzes the input information.

[0858] Step 3:

[0859] The server selects an appropriate mockup site template.

[0860] Step 4:

[0861] The server automatically generates a mockup site.

[0862] Step 5:

[0863] The server provides the generated mockup site to the user.

[0864] Presentation script creation

[0865] Step 1:

[0866] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[0867] Step 2:

[0868] The server receives and analyzes the presentation content and desired time.

[0869] Step 3:

[0870] The server calculates the appropriate time allocation for each slide or section.

[0871] Step 4:

[0872] The server automatically generates a presentation transcript.

[0873] Step 5:

[0874] The server provides the generated oral transcript to the user.

[0875] Step 6:

[0876] The user provides feedback and sends it to the server.

[0877] Step 7:

[0878] The server adjusts the manuscript based on the feedback.

[0879] The above are the detailed processing steps for each function of the Generative AI Contest Support System. Because the roles of the server, terminal, and user are clearly separated in each step, it is expected that the flow of the entire system will proceed smoothly.

[0880] Example 1

[0881] 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."

[0882] Conventional idea generation support systems and presentation material creation systems can only address user input from a single perspective, resulting in a lack of multifaceted refinement and optimization. Furthermore, automatic generation of presentation materials is problematic due to the difficulty of making appropriate adjustments based on specific user instructions, hindering efficient material creation. Therefore, there is a need for systems that can improve and evaluate ideas from multiple perspectives and support the creation of more flexible presentation materials.

[0883] 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.

[0884] In this invention, the server includes: means for receiving concepts entered by a user; means for distributing concepts to multiple AI agents with different characteristics, with each agent adding new perspectives and improvement suggestions; and means for integrating the concepts to which the new perspectives and improvement suggestions have been added and providing them to the user. This allows the user's ideas to be refined from multiple angles and improved to higher quality content. The server also includes means for evaluating the concepts submitted by the user based on evaluation criteria and means for returning the evaluation results to the user. This allows the submitted ideas to be objectively evaluated and the direction of improvement clarified. The server also includes means for analyzing presentation content and automatically generating visual materials, means for adjusting the visual materials based on user instructions, and means for generating and providing final presentation materials to the user. This allows presentation materials to be efficiently created and optimized in line with the user's intentions.

[0885] A "user" is a person or individual who accesses the system via a terminal and inputs concepts and instructions.

[0886] A "concept" refers to any or all of an idea or suggestion that a user inputs into the system.

[0887] "Multiple artificial intelligence agents with different characteristics" refers to multiple artificial intelligence-based software agents that have specific perspectives and characteristics and refine and consider ideas.

[0888] "Brushing up" refers to improving an idea or concept from multiple perspectives to raise its quality.

[0889] "Evaluation criteria" refers to the criteria or perspectives (e.g., creativity, feasibility, social impact, etc.) used to evaluate ideas and concepts.

[0890] "Visual materials" are visual documents such as slides, charts, and text generated for a presentation.

[0891] The embodiment of this invention is a system for effectively polishing and evaluating user ideas, creating presentation materials, generating mockup sites, and creating oral presentation scripts. This system operates based on communications between a server, terminals, and users.

[0892] The main hardware configuration of the system is as follows: The devices used by users include interface devices such as PCs, smartphones, and tablets. The server is a server machine equipped with a high-performance processor and large amount of memory, and it is also possible to use a cloud-based processing engine. The software consists of a generative AI model, a natural language processing (NLP) engine, and a database management system (DBMS).

[0893] Idea brush-up

[0894] 1. A user uses an input form on their device to enter their idea in text form into the system. For example, they enter their idea for a "new social networking app."

[0895] 2. The server receives the idea and stores it in a database. It then distributes the data to multiple AI agents (Dreamers, Enjoyers, Realists, and Critics). This process involves sending the idea data to each agent using an API.

[0896] 3. The Dreamer AI generates innovative ideas and big visions based on the prompt, "Add a new vision to this idea." For example, it adds "integration with VR."

[0897] 4. Based on the prompt, "Brush up this idea by adding entertainment elements," the Pleasure AI will output improvement proposals incorporating user experience and entertainment elements. For example, it will suggest "gamification elements."

[0898] 5. Based on the prompt, "Describe the technical steps required to realize this idea," the Realist AI will consider specific technical feasibility and propose technical implementations. For example, adding an "instant photo sharing function."

[0899] 6. Based on the prompt, "Please suggest the risks of this idea and how to improve it," the critic AI will extract risks and weaknesses and suggest ways to address them. For example, it will point out "privacy concerns."

[0900] 7. Finally, the server integrates the output of each agent and returns the integrated refinement idea to the user.

[0901] The first round of the contest

[0902] When a user submits an idea through an input form on their device, the server receives the idea and evaluates it based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.) using an AI model. The evaluation results are scored and sent back to the user as feedback.

[0903] Presentation file creation support

[0904] When a user inputs their presentation content from their device, the server receives it and analyzes it using a natural language processing engine. Based on the analysis results, it automatically selects a slide template and generates visual materials. If the user requests specific corrections or adjustments, the server adjusts the materials according to those instructions, generates the final presentation file, and provides it to the user.

[0905] Automatic generation of mockup sites

[0906] When a user inputs the specifications for a mockup website, the server receives them and selects a template. The server then automatically generates the mockup website and provides it to the user. For example, if a user requests, "Create a mockup website for a social networking app," the server generates a mockup website based on that information and provides it to the user as a URL or download link.

[0907] Presentation script creation

[0908] When a user inputs the content of their presentation and the desired presentation time, the server receives this, analyzes it, and allocates the appropriate time to each slide. Next, it automatically generates a presentation transcript and provides it to the user. If the user requests revisions, the server makes the revisions and provides it again. For example, if a user inputs a request for a "five-minute presentation," the server creates a transcript that fits within five minutes and provides it.

[0909] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0910] Idea brush-up

[0911] Step 1:

[0912] The user enters his / her idea into the system using an input form on the terminal.

[0913] Input: The user inputs an idea (e.g., "a new social networking app") in text format through the device.

[0914] Output: The entered text data is sent to the server.

[0915] Step 2:

[0916] The server receives the ideas, stores them in a database, and distributes the data to each AI agent.

[0917] Input: Idea data sent from the device.

[0918] Data processing: The server stores idea data in a database and distributes the data to multiple AI agents via API.

[0919] Output: Idea data is sent to each AI agent.

[0920] Step 3:

[0921] The Dreamer AI adds new perspectives and visions.

[0922] Input: Dreamer AI receives idea data.

[0923] Prompt: "Add a new vision to this idea"

[0924] Data Computation: Generative AI models add new perspectives and visions to ideas.

[0925] Output: Ideas with added novelty.

[0926] Step 4:

[0927] The enjoyment-loving AI improves ideas by taking into account user experience and entertainment elements.

[0928] Input: The Hedonist AI receives idea data.

[0929] Prompt: "Refine this idea by adding entertainment value."

[0930] Data Computation: Generative AI models make suggestions to improve the user experience.

[0931] Output: Ideas with an added entertainment element.

[0932] Step 5:

[0933] A realistic AI will consider feasibility and make specific technical proposals.

[0934] Input: Realist AI receives idea data.

[0935] Prompt: "Describe the technical steps required to realize this idea."

[0936] Data computation: Generative AI models propose technical implementations.

[0937] Output: Ideas with added technical feasibility.

[0938] Step 6:

[0939] The AI ​​critic points out risks and weaknesses and suggests areas for improvement.

[0940] Input: Critic AI receives idea data.

[0941] Prompt: "What are the risks of this idea and how can you improve it?"

[0942] Data calculation: The generative AI model analyzes risks and weaknesses and outputs improvement proposals.

[0943] Output: Ideas with added risks and weaknesses and suggestions for their improvement.

[0944] Step 7:

[0945] The server integrates the output of each AI agent, generates final refinement ideas, and provides them to the user.

[0946] Input: Ideas with refinements submitted by each AI agent.

[0947] Data processing: The server integrates all the improvement proposals and generates the final refinement ideas.

[0948] Output: The consolidated refinement ideas are returned to the user.

[0949] The first round of the contest

[0950] Step 1:

[0951] The user submits an idea through an input form on the device.

[0952] Input: User inputs their idea and clicks the submit button.

[0953] Output: The submitted ideas are sent to the server.

[0954] Step 2:

[0955] The server evaluates the submitted ideas based on the evaluation criteria.

[0956] Input: Idea data sent from the device.

[0957] Data calculation: The server generates an evaluation score based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.).

[0958] Output: Scoring data as the evaluation result.

[0959] Step 3:

[0960] The server returns the evaluation results to the user.

[0961] Input: Scoring data of evaluation results.

[0962] Data processing: The server compiles the evaluation results and generates feedback for the user.

[0963] Output: The evaluation results are sent to the user via email or notification.

[0964] Presentation file creation support

[0965] Step 1:

[0966] The user inputs the presentation content into the system from the terminal.

[0967] Input: The user inputs the presentation content in text format.

[0968] Output: The input presentation content is sent to the server.

[0969] Step 2:

[0970] The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[0971] Input: Presentation content data sent from the device.

[0972] Data Computing: Using natural language processing techniques, the presentation content is analyzed, appropriate slide templates are selected, and visual aids are generated.

[0973] Output: The generated visual aid.

[0974] Step 3:

[0975] The user indicates specific modifications or adjustments and the server adjusts the file accordingly.

[0976] Input: The user inputs correction instructions for a specific part.

[0977] Data calculation: The server modifies the visual materials based on the user's instructions.

[0978] Output: The corrected visual.

[0979] Step 4:

[0980] The server generates the final presentation file and provides it to the user.

[0981] Input: Visual data after corrections are complete.

[0982] Data processing: Generate the final presentation file.

[0983] Output: The generated presentation file is provided to the user.

[0984] Automatic generation of mockup sites

[0985] Step 1:

[0986] The user inputs the specifications of the mockup site into the system from a terminal.

[0987] Input: The user enters the specifications of the mockup site (page structure, functional requirements, etc.).

[0988] Output: The entered specification information is sent to the server.

[0989] Step 2:

[0990] The server analyzes the input information and selects a template.

[0991] Input: Specification information sent from the device.

[0992] Data calculation: The server analyzes the specification information and selects an appropriate template based on it.

[0993] Output: The selected template.

[0994] Step 3:

[0995] The server automatically generates a mockup site and provides it to the user.

[0996] Input: Selected template and specification information.

[0997] Data processing: Automatically generate a mockup site.

[0998] Output: The generated mockup site is provided to the user as a URL or download link.

[0999] Presentation script creation

[1000] Step 1:

[1001] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[1002] Input: The user inputs the presentation content and desired presentation time.

[1003] Output: The entered data is sent to the server.

[1004] Step 2:

[1005] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1006] Input: Presentation content sent from the device and desired presentation time.

[1007] Data calculation: Analyze the presentation content and calculate the appropriate time allocation for each slide.

[1008] Output: Time allocation data.

[1009] Step 3:

[1010] The server automatically generates a presentation manuscript and provides it to the user.

[1011] Input: Time allocation data and analysis results.

[1012] Data processing: Automatically generate oral presentation manuscripts.

[1013] Output: The generated transcript is provided to the user.

[1014] Step 4:

[1015] The user makes a correction request and the server adjusts the manuscript accordingly.

[1016] Input: The user inputs correction instructions for the oral manuscript.

[1017] Data calculation: The server adjusts the manuscript based on the correction instructions.

[1018] Output: The revised transcript is provided to the user again.

[1019] (Application example 1)

[1020] 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."

[1021] To efficiently create high-quality content, modern content creators need to collect, evaluate, and ensure consistency in various ideas. However, many creators face challenges such as limited ability to refine their own concepts and few opportunities to receive objective evaluation and feedback. Furthermore, creating optimal presentation materials and mockup websites takes time and effort. As a result, creative work stagnates, risking a decline in content quality.

[1022] 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.

[1023] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, means for evaluating and refining different content formats, and means for further evaluating and improving the idea integrated with improvements suggested by the user. This enables content creators to refine their ideas by receiving feedback from multiple perspectives and quickly create high-quality content.

[1024] "Means for receiving user-input ideas" refers to a function or module that receives, in digital form, ideas or concepts that users provide to the system.

[1025] "Multiple AI agents with different characteristics" are heterogeneous AI models, each with a specific perspective and role, that evaluate and improve ideas from different perspectives.

[1026] "Means for brushing up ideas" is a function that analyzes received ideas from multiple angles and adds improvements and new suggestions to further develop the ideas.

[1027] "Means for integrating refined ideas" is a function that synthesizes feedback and improvements from each AI agent and brings them together into a single integrated idea.

[1028] "Means to provide to users" refers to the ability to communicate the integrated ideas and proposed improvements to users in a clear and understandable format.

[1029] "A means to evaluate and refine different content formats" is a function that evaluates various forms of content, such as videos, articles, and podcasts, and suggests appropriate improvements for each.

[1030] "Suggestions for improving content quality based on feedback" is a function that provides specific advice for further improving content based on the evaluations and improvements received from users.

[1031] "Means for analyzing presentation content and automatically generating slides and materials" refers to a function that understands the content of a user's presentation and automatically creates appropriate slides and materials.

[1032] "Means for adjusting slides and materials based on user instructions" refers to a function for correcting and adjusting the content of already generated slides and materials in accordance with user requests and instructions.

[1033] The "means for automatically generating a content preview site" is a function that automatically creates a simple website or a preview page based on the user's ideas and content.

[1034] The present invention is a system that evaluates and improves ideas input by users from multiple angles and automatically generates high-quality content. Detailed embodiments of the system are described below.

[1035] System Configuration

[1036] The system operates based on communication between the server, terminals, and users, and uses smartphones (iOS or Android devices), Python, and OpenAI APIs as its main hardware and software.

[1037] Program processing

[1038] 1. A means of receiving user-entered ideas

[1039] Users input ideas into the system using their smartphones or PCs, and the ideas are sent to the server via the platform or application user interface.

[1040] 2. A way to share and refine ideas

[1041] The server distributes the received ideas to multiple AI agents with different characteristics. Each agent analyzes the idea from a specific perspective and generates improvements and new proposals. Specifically, the Dreamer AI is responsible for creative vision, the Hedonist AI for user experience, the Realist AI for feasibility, and the Critic AI for risk assessment.

[1042] 3. A way to integrate refined ideas

[1043] The feedback from each agent is integrated to generate a single improved idea. This integration process is carried out on the server and is reflected in the final result provided to the user.

[1044] 4. A way to evaluate and refine different content formats

[1045] The server provides feedback on various content formats, including videos, articles, and podcasts, and suggests appropriate improvements for each format, providing users with instructions to improve the quality of their content.

[1046] 5. A way to automatically generate a preview site for your content

[1047] The server automatically creates mockups and preview sites based on the generated ideas. These preview sites can be viewed in a browser, allowing users to see the final form of the content.

[1048] Usage example

[1049] As a specific example, a case will be described in which a user inputs an idea for an "introductory video for an environmentally friendly product." When the user inputs the idea into the system, the following process is carried out.

[1050] Visionary AI adds "vision of futuristic eco-technology"

[1051] The Hedonist AI recommends "visually appealing effects and music"

[1052] Realistic AI takes into account "specific product specifications and practical examples"

[1053] Critic AI points out "privacy and legal concerns"

[1054] This provides users with consolidated feedback, which allows them to create optimized content.

[1055] Prompt Sentence Examples

[1056] As a dreamer, please provide feedback on the following idea: A new cooking recipe sharing app

[1057] In this way, a system is provided that allows content creators to receive feedback from multiple perspectives and quickly create high-quality content.

[1058] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1059] Step 1:

[1060] The ideas entered by the user are sent from the device to the server. The user uses a smartphone or computer to enter their ideas and concepts into the system in text format. The entered ideas are sent to the server and stored in a database.

[1061] Input: Textual ideas from users

[1062] Output: Ideas stored in a database on the server

[1063] Step 2:

[1064] The server distributes ideas to multiple AI agents. The server retrieves ideas from a database and sends them to each agent (Dreamer, Enjoyer, Realist, Critic).

[1065] Input: Ideas retrieved from the database

[1066] Output: Ideas distributed to each agent

[1067] Step 3:

[1068] The Dreamer AI analyzes the idea and proposes a new creative vision. The server sends the idea to the Dreamer AI, and the Dreamer AI generates new visions and creative elements based on the idea.

[1069] Input: Ideas sent to the Dreamer AI

[1070] Output: Creative suggestions from the Dreamer AI

[1071] Step 4:

[1072] The Pleasure AI improves the idea by taking into account the user experience. The server sends the idea to the Pleasure AI, which then generates a proposal that incorporates entertainment elements and user experience into the idea.

[1073] Input: Idea sent to the Hedonist AI

[1074] Output: Suggestions from the Enjoyer AI to improve the user experience

[1075] Step 5:

[1076] The Realist AI considers the feasibility of the idea. The server sends the idea to the Realist AI, which then generates a concrete proposal that is feasible from a technical standpoint.

[1077] Input: Ideas sent to the Realist AI

[1078] Output: Feasible proposals from a realist AI

[1079] Step 6:

[1080] The critic AI evaluates the risk of ideas. The server sends ideas to the critic AI, which then points out risks and weaknesses and suggests ways to improve them.

[1081] Input: Ideas sent to the critic AI

[1082] Output: Risk assessment and improvement suggestions from the critic AI

[1083] Step 7:

[1084] The server integrates the feedback from each agent. The server receives feedback from each agent and synthesizes it into a single integrated idea, reconciling overlapping and contradictory points.

[1085] Input: Feedback from each agent

[1086] Output: Unified refinement proposal

[1087] Step 8:

[1088] The server provides the user with the integrated idea, which the user can then review and use. The user can then make further modifications as needed.

[1089] Input: Integrated refinement proposal

[1090] Output: Consolidated ideas provided to the user

[1091] Step 9:

[1092] The server evaluates and refines the content according to its format. It provides appropriate evaluation and feedback based on the format of the user-generated content (video, article, podcast, etc.) and generates suggestions to further improve the content.

[1093] Input: The format of the content provided by the user

[1094] Output: Evaluation and suggestions for improving the content

[1095] Step 10:

[1096] The server provides users with suggestions for improving the quality of content based on their feedback. The server reflects the feedback from each agent and proposes specific improvement actions to the user.

[1097] Input: Feedback from each agent

[1098] Output: Suggestions for improving the content provided to the user

[1099] 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.

[1100] This embodiment of the invention combines an emotion engine with a specialized system for supporting generative AI contests, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[1101] System Overview

[1102] The system has the following main functions:

[1103] 1. Idea brush-up (virtual brainstorming)

[1104] 2. Final round of the contest

[1105] 3. Presentation file creation support

[1106] 4. Automatic generation of mockup sites

[1107] 5. Preparation of oral presentation script

[1108] 6. Emotion Recognition and Adaptation with Emotion Engine

[1109] 1. Idea brush-up (virtual brainstorming)

[1110] 1. The user inputs an idea into the system from a terminal.

[1111] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[1112] 3. Visionary AI adds new ideas and big visions to ideas.

[1113] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[1114] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[1115] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[1116] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[1117] 8. The emotion engine analyzes the user's emotional data and makes adjustments based on the AI ​​agent's feedback.

[1118] Example: When a user suggests a "new social networking app," the Dreamer AI suggests "integration with VR," the Enjoyer AI suggests "gamification elements," the Realist AI adds "instant photo sharing functionality," and the Critic AI points out "privacy concerns." If the user expresses positive emotions toward the suggestion, the emotion engine takes this into account to further strengthen the idea.

[1119] 2. Final round of the contest

[1120] 1. The user submits an idea to the system from their device.

[1121] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1122] 3. The server returns the evaluation results to the user.

[1123] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[1124] 3. Presentation file creation support

[1125] 1. The user inputs the presentation content into the system from their device.

[1126] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[1127] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[1128] 4. The emotion engine analyzes the user's emotion data and adjusts the design and content of the material based on the user's emotions.

[1129] 5. The server generates the final presentation file and serves it to the user.

[1130] Example: A user inputs "business plan" and the server automatically generates slides. If the user says "add a graph to this part," the server adds the graph. Also, if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[1131] 4. Automatic generation of mockup sites

[1132] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[1133] 2. The server analyzes the input information and selects a template for the mockup site.

[1134] 3. The server automatically generates a mockup site.

[1135] 4. The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[1136] 5. The server serves the generated mockup site to the user.

[1137] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction, and the emotion engine observes the user's reaction, adjusts the color scheme and layout, and delivers the final site to the user.

[1138] 5. Preparation of oral presentation script

[1139] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[1140] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1141] 3. The server automatically generates the oral presentation script.

[1142] 4. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[1143] 5. The server provides the generated oral transcript to the user.

[1144] 6. The server adjusts the manuscript based on user feedback.

[1145] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral script that fits within 5 minutes. If the user instructs the server to "explain this part in more detail," the server adds content that details the relevant part. Also, if the user is nervous, the emotion engine detects this and generates a script with a more relaxed tone.

[1146] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals. By combining it with an emotion engine, it is expected to provide output optimized for the user's emotional state, improving the user experience.

[1147] The processing flow will be explained below.

[1148] Idea brush-up (including emotion engine)

[1149] Step 1:

[1150] The user inputs an idea from a terminal and sends it to the server.

[1151] Step 2:

[1152] A server receives ideas from users.

[1153] Step 3:

[1154] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[1155] Step 4:

[1156] The Visionary AI adds new ideas and big visions to ideas, for example, proposing innovative technologies and generating future-oriented scenarios.

[1157] Step 5:

[1158] The Pleasure AI adds elements to ideas that enrich the user experience, such as suggesting easy-to-use interfaces and entertainment elements.

[1159] Step 6:

[1160] Realistic AI considers the feasibility of ideas and gives them technical realization, for example proposing a technology stack and designing a prototype.

[1161] Step 7:

[1162] The AI ​​critics point out risks and weaknesses in ideas and suggest areas for improvement, such as legal risks and market concerns.

[1163] Step 8:

[1164] The emotion engine analyzes the user's emotional data, for example, whether the user is excited or skeptical about an idea.

[1165] Step 9:

[1166] The server integrates feedback from each AI agent and generates refined ideas.

[1167] Step 10:

[1168] The emotion engine adjusts the final ideas based on the user's emotional data, for example adding more challenging ideas if the user is excited.

[1169] Step 11:

[1170] The server is integrated and sends the coordinated ideas back to the user.

[1171] The first round of the contest

[1172] Step 1:

[1173] The user inputs an idea from a terminal and sends it to the server.

[1174] Step 2:

[1175] A server receives the submitted ideas.

[1176] Step 3:

[1177] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1178] Step 4:

[1179] The server assigns a score to each evaluation item.

[1180] Step 5:

[1181] The server calculates the overall score.

[1182] Step 6:

[1183] The server returns the evaluation results and feedback to the user.

[1184] Presentation file creation support

[1185] Step 1:

[1186] The user inputs the presentation content from the terminal and sends it to the server.

[1187] Step 2:

[1188] The server receives and analyzes the presentation content.

[1189] Step 3:

[1190] The server automatically selects a slide template.

[1191] Step 4:

[1192] The server generates the materials required for the presentation.

[1193] Step 5:

[1194] The user specifies the range or gives verbal instructions, which are then sent to the server.

[1195] Step 6:

[1196] The server adjusts the slides and materials based on the user's instructions.

[1197] Step 7:

[1198] The emotion engine analyzes the user's emotional data and adjusts the design and content of the materials based on the user's emotions. For example, if the user is nervous, it uses colors and designs that are relaxing.

[1199] Step 8:

[1200] The server generates the final presentation file and provides it to the user.

[1201] Automatic generation of mockup sites

[1202] Step 1:

[1203] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[1204] Step 2:

[1205] The server receives and analyzes the input information.

[1206] Step 3:

[1207] The server selects an appropriate mockup site template.

[1208] Step 4:

[1209] The server automatically generates a mockup site.

[1210] Step 5:

[1211] The emotion engine analyzes user emotion data and adjusts the site design and element placement. For example, if a user expresses positive emotions, the engine adds design elements that emphasize those emotions.

[1212] Step 6:

[1213] The server provides the generated mockup site to the user.

[1214] Presentation script creation

[1215] Step 1:

[1216] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[1217] Step 2:

[1218] The server receives and analyzes the presentation content and desired time.

[1219] Step 3:

[1220] The server calculates the appropriate time allocation for each slide or section.

[1221] Step 4:

[1222] The server automatically generates a presentation transcript.

[1223] Step 5:

[1224] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript. For example, if the user is nervous, the engine will generate a manuscript with a relaxed tone.

[1225] Step 6:

[1226] The server provides the generated oral transcript to the user.

[1227] Step 7:

[1228] The user provides feedback and sends it to the server.

[1229] Step 8:

[1230] The server adjusts the manuscript based on the feedback.

[1231] The above are the detailed processing steps for each function of the generative AI contest support system that combines an emotion engine. In each step, the roles of the server, terminal, and user are clearly separated, and it is expected that the overall system will proceed smoothly. The incorporation of an emotion engine makes it possible to adapt to the user's emotional state, providing more effective and personalized support.

[1232] Example 2

[1233] 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."

[1234] This invention relates to a system that can provide optimal feedback and output by taking into account the user's emotional state during processes such as refining and evaluating ideas in contests and supporting the creation of presentations. Conventional systems often refine ideas or create presentation materials without taking the user's emotions into account, making it difficult to achieve user-friendly and effective results. Furthermore, because they are unable to optimally adjust to the user's emotional state, they are unable to improve user satisfaction or the quality of proposals.

[1235] 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.

[1236] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, and emotion engine means for analyzing the user's emotion data and making adjustments based on feedback from the AI ​​agents. This makes it possible to provide feedback and output optimized for the user's emotional state, enabling user-friendly and effective idea refinement and the creation of presentation materials.

[1237] "User" refers to the entity that inputs ideas and presentation content into the system and receives feedback and output based on them.

[1238] "Terminal" refers to an apparatus or device for transmitting information entered by a user to a system.

[1239] "Server" refers to a central system that receives and processes information sent by users.

[1240] An "artificial intelligence agent" is a program that has specific characteristics and roles, analyzes input information, and refines ideas based on those characteristics.

[1241] A "dreamer agent" refers to an artificial intelligence agent that has the ability to add new ideas and big visions.

[1242] A "pleasure agent" refers to an artificial intelligence agent that has the ability to improve ideas by taking into account user experience and entertainment elements.

[1243] A "realist agent" is an artificial intelligence agent that has the ability to consider the feasibility of ideas and bring them to technical realization.

[1244] A "critic agent" is an artificial intelligence agent that has the ability to point out the risks and weaknesses of an idea and suggest areas for improvement.

[1245] An "emotion engine" is a program that analyzes the user's emotional data and makes optimal adjustments based on feedback from the AI ​​agent.

[1246] "Brushing up" refers to the process of making improvements and additions to an input idea to make it better.

[1247] "Presentation" refers to materials and presentations that visually and verbally express the information or proposals that a user wants to show.

[1248] A "mockup site" is a prototype of a website or application that does not replicate actual functionality but instead provides a visual representation of the design and user interface.

[1249] "Preliminary judging" refers to the first idea evaluation process in a contest.

[1250] This invention combines an emotion engine with a specialized system for generative AI contest support, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[1251] To implement this system, the following major components are required:

[1252] 1. Idea brush-up (virtual brainstorming)

[1253] 2. Final round of the contest

[1254] 3. Presentation file creation support

[1255] 4. Automatic generation of mockup sites

[1256] 5. Preparation of oral presentation script

[1257] 6. Emotion Recognition and Adaptation with Emotion Engine

[1258] Idea brush-up (virtual brainstorming)

[1259] When a user inputs a new idea into the system from a terminal, the server receives the idea. The server distributes the idea to several artificial intelligence (AI) agents with different characteristics: the Dreamer, the Hedonist, the Realist, and the Critic. Each AI agent behaves according to its characteristics as follows:

[1260] Visionary agents add new ideas and big visions to ideas.

[1261] The hedonist agent improves ideas by taking into account user experience and entertainment factors.

[1262] The realist agent considers the feasibility of the idea and gives it technical realization.

[1263] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[1264] The server integrates these outputs and presents the refined idea to the user. The emotion engine also analyzes the user's emotional data and makes adjustments based on the AI ​​agents' feedback. For example, if a user suggests a "new social media app," the dreamer agent might suggest "integration with VR," the hedonist agent might suggest "gamification elements," the realist agent might add "instant photo sharing functionality," and the critic agent might point out "privacy concerns." If the user expresses positive emotions toward the proposal, the emotion engine takes this into account to further strengthen the idea.

[1265] The first round of the contest

[1266] When a user submits an idea to the system from their device, the server receives the idea. The server evaluates the idea based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.) and returns the evaluation results to the user. For example, if a user submits an "environmentally friendly product," the server will evaluate it based on creativity, feasibility, and social impact, and provide the evaluation results as feedback to the user.

[1267] Presentation file creation support

[1268] When a user inputs the content of their presentation into the system from their device, the server analyzes the content, automatically selects a slide template, and generates the presentation material. The user specifies the range or gives verbal instructions, and the server adjusts the file accordingly. The emotion engine also analyzes the user's emotional data and adjusts the design and content of the presentation material based on the user's emotions. The server generates the final presentation file and provides it to the user. For example, a user inputs "business plan" and the server automatically generates slides. If the user instructs "add a graph to this part," the server adds the graph, and if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[1269] Automatic generation of mockup sites

[1270] When a user inputs the specifications of a mockup site into the system from their device, the server analyzes the input information and selects a template for the mockup site. The server then automatically generates the mockup site, and the emotion engine analyzes the user's emotional data and adjusts the site's design and element placement. Finally, the server provides the generated mockup site to the user. For example, if a user instructs the server to "create a mockup site for a social networking app," the server generates the mockup site based on that information, and the emotion engine adjusts the color scheme and layout based on the user's reaction, and provides the final site to the user.

[1271] Presentation script creation

[1272] When a user inputs the presentation content and desired presentation time into the system from their device, the server analyzes the presentation content and calculates the appropriate time allocation for each slide and section. The server then automatically generates an oral presentation script. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the script. The final oral presentation script is provided to the user, and the server adjusts the script based on feedback from the user. For example, if a user inputs a request for a "five-minute presentation," the server will create and provide an oral presentation script that fits within five minutes. If the user instructs the server to "explain this part in more detail," the server will add content that details the relevant part, and if the user is nervous, the emotion engine will detect this and generate a script with a more relaxed tone.

[1273] In this way, the present invention can provide optimal feedback and output according to the user's emotional state, thereby improving the quality of ideas, reducing the burden of creating presentation materials, and being extremely useful in making competitive proposals.

[1274] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1275] Idea brush-up (virtual brainstorming)

[1276] Step 1:

[1277] The user inputs an idea from the terminal.

[1278] Enter: an idea for a new social media app.

[1279] Output: Idea data sent to the system.

[1280] Specific operation: The user enters their idea for a "new SNS app" into the input form on the device and clicks the "Submit" button.

[1281] Step 2:

[1282] The server receives the idea.

[1283] Input: Idea data submitted by the user.

[1284] Output: Idea data distributed to multiple artificial intelligence agents with different characteristics.

[1285] Specific operation: The server analyzes the received idea data and sends it to the dreamer agent, the hedonist agent, the realist agent, and the critic agent.

[1286] Step 3:

[1287] Visionary agents add new ideas and big visions to your ideas.

[1288] Input: Idea data sent to the Dreamer Agent.

[1289] Output: Idea data with new ideas and visions added.

[1290] Specific operation: In response to the prompt "Propose a new vision or idea for a social networking app," the dreamer agent generates and outputs an idea for VR integration.

[1291] Step 4:

[1292] The hedonistic agent considers user experience and entertainment elements to improve the idea.

[1293] Input: Idea data sent to the hedonist agent.

[1294] Output: Idea data with improved user experience and entertainment elements added.

[1295] Specific operation: The hedonist agent proposes gamification elements based on the prompt "Elements that will enrich the user experience" and outputs them.

[1296] Step 5:

[1297] A realist agent considers the feasibility of the idea and gives it technical realization.

[1298] Input: Idea data sent to the Realist agent.

[1299] Output: Technically embodied idea data.

[1300] Specific behavior: The realist agent receives the prompt "technically feasible specific proposal," generates a proposal to add an instant photo sharing function, and outputs it.

[1301] Step 6:

[1302] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[1303] Input: Idea data sent to the critic agent.

[1304] Output: Idea data with risks and weaknesses pointed out and improvements added.

[1305] Specific behavior: Based on the prompt "Point out risks and weaknesses," the critic agent points out privacy concerns and outputs suggestions for improvement.

[1306] Step 7:

[1307] The server integrates the output of each agent, generates refined ideas, and provides them to the user.

[1308] Input: Refined idea data sent by each agent.

[1309] Output: A final, consolidated and refined idea.

[1310] Specific operation: The server integrates the data received from each agent and generates a final idea to send back to the user.

[1311] Step 8:

[1312] The emotion engine analyzes the user's emotional data and makes adjustments based on the feedback.

[1313] Input: User emotion data and final idea data.

[1314] Output: Final ideas adjusted based on user sentiment.

[1315] Specific operation: The emotion engine analyzes the user's emotion data, and if the user expresses positive emotions, it makes adjustments to further strengthen the idea.

[1316] The first round of the contest

[1317] Step 1:

[1318] A user submits an idea to the system from a terminal.

[1319] Input: Idea data to be submitted.

[1320] Output: The idea data sent to the system.

[1321] Specific operation: The user enters their idea for an "environmentally friendly product" into the input form on the device and clicks the "Submit" button.

[1322] Step 2:

[1323] The server evaluates the ideas based on the contest's evaluation criteria.

[1324] Input: Submitted idea data.

[1325] Output: Evaluation results based on the evaluation criteria.

[1326] Specific operation: The server evaluates the received idea data based on evaluation criteria (creativity, feasibility, social impact, etc.) and tally up the evaluation scores.

[1327] Step 3:

[1328] The server returns the evaluation results to the user.

[1329] Input: Evaluation result data.

[1330] Output: The evaluation results that are displayed to the user.

[1331] Specific operation: The server generates the evaluation results, displays them to the user, and sends them as feedback.

[1332] Presentation file creation support

[1333] Step 1:

[1334] The user inputs the presentation content into the system from the terminal.

[1335] Input: Presentation content data.

[1336] Output: Presentation content data sent to the system.

[1337] Specific operation: The user enters the details of the "business plan" into the input form on the terminal and clicks the "Submit" button.

[1338] Step 2:

[1339] The server analyzes the presentation content, automatically selects a slide template, and generates materials.

[1340] Input: Presentation content data.

[1341] Output: Selected slide templates and generated data.

[1342] Specific operation: The server analyzes the presentation content, selects an appropriate slide template, and generates the materials.

[1343] Step 3:

[1344] The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[1345] Input: Range specification or verbal instruction data from the user.

[1346] Output: Adjusted presentation data.

[1347] Specific operation: When the user instructs, for example, "Add a graph to this part," the server adds the graph based on that instruction.

[1348] Step 4:

[1349] The emotion engine analyzes the user's emotional data and adjusts the design and content of the document.

[1350] Input: User emotion data and presentation data.

[1351] Output: Presentation materials tailored based on user sentiment.

[1352] What it does: The emotion engine analyzes the user's emotions and, for example, if the user is excited, adds more attractive visualizations to the slides.

[1353] Step 5:

[1354] The server generates the final presentation file and provides it to the user.

[1355] Input: Adjusted presentation data.

[1356] Output: Final presentation file.

[1357] What happens: The server assembles the final presentation file and serves it to the user.

[1358] Automatic generation of mockup sites

[1359] Step 1:

[1360] The user inputs the specifications of the mockup site into the system from a terminal.

[1361] Input: Mockup site specification data.

[1362] Output: The specification data sent to the system.

[1363] Specific operation: The user enters, for example, "I would like you to create a mockup site for a social networking app" into the input form on the device and clicks the "Submit" button.

[1364] Step 2:

[1365] The server analyzes the input information and selects a template for the mockup site.

[1366] Input: Mockup site specification data.

[1367] Output: The selected template data.

[1368] Specific operation: The server analyzes the input specification data and selects an appropriate mockup site template.

[1369] Step 3:

[1370] The server automatically generates a mockup site.

[1371] Input: Selected template data and specification data.

[1372] Output: An automatically generated mockup site.

[1373] What happens: The server generates a mockup site based on the template and specification data.

[1374] Step 4:

[1375] The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[1376] Input: User emotion data and generated mockup site.

[1377] Output: A tailored mockup site.

[1378] Specific behavior: The emotion engine analyzes the user's emotion data and adjusts the color scheme and layout.

[1379] Step 5:

[1380] The server provides the generated mockup site to the user.

[1381] Input: The adjusted mockup site.

[1382] Output: The final mockup site that is provided to the user.

[1383] Specific operation: The server generates the final mockup site and provides it to the user.

[1384] Presentation script creation

[1385] Step 1:

[1386] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[1387] Input: Presentation content data and desired time data.

[1388] Output: Presentation content and desired time data sent to the system.

[1389] Specific operation: The user enters the presentation content and desired time (e.g., "5-minute presentation") into the input form on the device and clicks the "Send" button.

[1390] Step 2:

[1391] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1392] Input: Presentation content data and desired time data.

[1393] Output: A presentation outline based on appropriate time allocation.

[1394] What it does: The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1395] Step 3:

[1396] The server automatically generates a presentation transcript.

[1397] Input: Presentation content data and time allocation data.

[1398] Output: The generated oral presentation transcript.

[1399] Specific operation: The server automatically creates a presentation manuscript based on the time allocation.

[1400] Step 4:

[1401] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[1402] Input: User emotion data and generated oral presentation script.

[1403] Output: Adjusted oral presentation transcript.

[1404] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the manuscript according to the emotion, such as by using a relaxed tone of voice.

[1405] Step 5:

[1406] The server provides the generated oral transcript to the user.

[1407] Input: Adjusted oral presentation transcript.

[1408] Output: The final presentation transcript provided to the user.

[1409] Specific operation: The server generates the final presentation transcript and provides it to the user.

[1410] Step 6:

[1411] The server adjusts the manuscript according to the user's feedback.

[1412] Input: Feedback data from users.

[1413] Output: Adjusted oral presentation transcript.

[1414] Specific operation: When the user gives feedback such as "Please explain this part in more detail," the server adds or corrects the relevant part in detail based on the user's instructions.

[1415] This process not only allows users to improve the quality of their ideas, but also allows them to receive feedback and output that is optimized for their emotional state, enabling them to create effective presentations and attractive mockup sites.

[1416] (Application example 2)

[1417] 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."

[1418] There is a need for technology to improve productivity and safety when using assistive robots in factories today. Furthermore, there are few systems that provide feedback or suggest work improvements that take into account the emotional state of workers, making it difficult to provide appropriate assistance based on their emotional state. There is a need for a system that can solve this problem.

[1419] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1420] In this invention, the server includes a means for analyzing the user's emotional data and adjusting the feedback of the generating AI agent based on the emotion, a means for receiving ideas input by the user, a means for distributing the ideas to multiple AI agents with different characteristics and having each agent refine the idea, and a means for integrating the refined ideas and providing them to the user. This makes it possible to propose appropriate work improvements and improve safety based on the worker's emotional state.

[1421] 1. "User" means a person or group who uses the system to input ideas, evaluate them, and receive feedback.

[1422] 2. "Emotional data" refers to information that indicates a user's emotional state, such as text, audio, images, or data obtained from sensors.

[1423] 3. "Generative AI agents" are multiple artificial intelligences that analyze users' ideas from different perspectives and provide improvement suggestions and feedback.

[1424] 4. "Feedback" refers to improvement suggestions and evaluation results for ideas refined by the generating AI agent.

[1425] 5. "Agents with different characteristics" are AIs that analyze ideas from different perspectives and criteria, such as dreamers, hedonists, realists, and critics.

[1426] 6. "Idea brush-up" is a process in which multiple AI agents improve an idea entered by a user and turn it into a better version.

[1427] 7. "Idea distribution" is the process of sending a user's input ideas to multiple artificial intelligence agents with different characteristics.

[1428] 8. A "system" is a complex collection of machines and software that handles everything from user idea input to evaluation, refinement, and feedback.

[1429] 9. A "refined idea" is an idea that has been improved by multiple AI agents with different perspectives.

[1430] 10. "Presentation Materials" means materials such as slides and documents used by Users when giving presentations.

[1431] 11. "Final presentation file" refers to the presentation materials that are finally generated based on the user's instructions and emotional data.

[1432] This paper describes a system applied to an assistive robot that supports workers in a factory. The system's program processing is explained in natural language below, and the specific names of the hardware and software used are specified.

[1433] Hardware:

[1434] 1. Emotion data acquisition devices: Wearable devices and cameras for acquiring workers' emotional data.

[1435] 2. Assistive robots: Physical robots that interact directly with workers.

[1436] software:

[1437] 1. Emotion engine: A module that analyzes user emotion data.

[1438] 2. Generative AI Agents: Artificial intelligence agents with multiple characteristics (e.g., Dreamer AI, Hedonist AI, Realist AI, Critic AI).

[1439] 3. Integrated system: A system that integrates feedback from different agents and provides it to the user.

[1440] Data processing and calculation:

[1441] 1. Emotion data acquisition: The terminal acquires the worker's emotion data from a wearable device or camera.

[1442] 2. Emotion analysis: The server analyzes the emotion data using an emotion engine to determine the worker's current emotional state.

[1443] 3. Idea sharing and polishing:

[1444] The server distributes work improvement ideas to the generated AI agents.

[1445] Each agent improves the idea from a different perspective and generates feedback.

[1446] 4. Feedback integration: The server integrates the feedback from each generated AI agent and provides it to the user.

[1447] 5. Emotion-based adjustment: The emotion engine adjusts the generated feedback and presentation materials based on the user's emotional state.

[1448] Examples:

[1449] If a worker feels "tired today," enter the following prompt:

[1450] Prompt: "I'm feeling tired today. How can I improve my work efficiency?"

[1451] Based on this prompt, the server does the following:

[1452] The emotion engine detects "fatigue" and notifies the generative AI agent of this emotional state.

[1453] The generative AI agent generates specific support suggestions, such as "take a break" or "recheck your work procedures."

[1454] The server integrates these suggestions and provides feedback to the worker via the assist robot.

[1455] Ultimately, workers can receive appropriate support according to their emotional state, improving work efficiency and safety.

[1456] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1457] Step 1:

[1458] The user inputs emotional data using a terminal. For example, the user inputs, "I feel tired today. How can I improve my work efficiency?" This input becomes the initial data for the system.

[1459] Step 2:

[1460] The device collects emotional data and sends it to the server. The input emotional data is text information that indicates the emotional state. The device processes the data and converts it into a format that can be sent to the server. The input data is sent to the server, and the server receives the data for further processing.

[1461] Step 3:

[1462] The server analyzes the emotional data using an emotion engine. The server accepts the analyzed emotional data and determines the emotional state, such as "fatigue" or "stress." The input in this step is "user's emotional data," and the output is "analyzed emotional state."

[1463] Step 4:

[1464] The server distributes work improvement ideas to the generating AI agents. Based on the analyzed emotional state, the server sends requests to the generating AI agents for appropriate improvement proposals. The input is the "analyzed emotional state," and the output is "requests to multiple generating AI agents."

[1465] Step 5:

[1466] The generative AI agent generates work improvement suggestions based on the user's emotional state. Each agent (Dreamer AI, Hedonist AI, Realist AI, Critic AI) generates ideas from their own perspective. The input is a "request from the server" and the output is a "suggestion for work improvement."

[1467] Step 6:

[1468] The server aggregates the feedback from the generating AI agents. The server combines the feedback received from each generating AI agent into a single aggregated proposal. The input is the "feedback from the generating AI agent" and the output is the "aggregated proposal."

[1469] Step 7:

[1470] The server sends the integrated suggestion to the assist robot, which uses this information to provide feedback to the user. The input is the "integrated suggestion" and the output is "feedback information to the assist robot."

[1471] Step 8:

[1472] The assist robot makes a suggestion to the user. For example, the assist robot may suggest to the user, "You seem tired. I recommend you take a break." The input is "feedback information from the server," and the output is "feedback to the user."

[1473] 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.

[1474] 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.

[1475] 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.

[1476] [Third embodiment]

[1477] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1478] 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.

[1479] 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).

[1480] 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.

[1481] 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.

[1482] 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).

[1483] 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.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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."

[1489] The embodiment of this invention is a specialized system for supporting generative AI contests, which effectively refines users' ideas and assists in the creation of presentation materials, mockup sites, and oral manuscripts. This system operates based on communications between a server, terminals, and users.

[1490] System Overview

[1491] The system has the following main functions:

[1492] 1. Idea brush-up (virtual brainstorming)

[1493] 2. Final round of the contest

[1494] 3. Presentation file creation support

[1495] 4. Automatic generation of mockup sites

[1496] 5. Preparation of oral presentation script

[1497] 1. Idea brush-up (virtual brainstorming)

[1498] 1. The user inputs an idea into the system from a terminal.

[1499] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[1500] 3. Visionary AI adds new ideas and big visions to ideas.

[1501] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[1502] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[1503] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[1504] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[1505] Example: When a user suggests a "new social networking app," the dreamer AI adds "VR integration," the enjoyer AI suggests "gamification elements," the realist AI adds "instant photo sharing functionality," and the critic AI points out "privacy concerns." The final integrated idea is sent back to the user.

[1506] 2. Final round of the contest

[1507] 1. The user submits an idea to the system from their device.

[1508] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1509] 3. The server returns the evaluation results to the user.

[1510] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[1511] 3. Presentation file creation support

[1512] 1. The user inputs the presentation content into the system from their device.

[1513] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[1514] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[1515] 4. The server generates the final presentation file and serves it to the user.

[1516] Example: A user inputs a "business plan" and the server automatically generates slides. When the user instructs "add a graph to this section," the server adds the graph.

[1517] 4. Automatic generation of mockup sites

[1518] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[1519] 2. The server analyzes the input information and selects a template for the mockup site.

[1520] 3. The server automatically generates a mockup site and provides it to the user.

[1521] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction and provides it to the user.

[1522] 5. Preparation of oral presentation script

[1523] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[1524] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1525] 3. The server automatically generates a presentation transcript and provides it to the user.

[1526] 4. The server adjusts the manuscript based on user feedback.

[1527] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral manuscript that fits within 5 minutes. When the user instructs, "Please explain this part in more detail," the server adds content that details the relevant part.

[1528] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals.

[1529] The processing flow will be explained below.

[1530] Idea brush-up (virtual brainstorming)

[1531] Step 1:

[1532] The user inputs an idea from a terminal and sends it to the server.

[1533] Step 2:

[1534] A server receives ideas from users.

[1535] Step 3:

[1536] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[1537] Step 4:

[1538] The Visionary AI adds new ideas and big visions to ideas, specifically proposing future-oriented scenarios and new concepts to ideas.

[1539] Step 5:

[1540] The Hedonist AI adds elements to ideas that enrich the user experience, such as entertainment elements and improvements to user interaction.

[1541] Step 6:

[1542] Realistic AI considers the feasibility of ideas and gives them technical specificity, for example by proposing a tech stack and adding prototype designs.

[1543] Step 7:

[1544] The AI ​​critic points out the risks and weaknesses of an idea and suggests ways to improve it, specifically highlighting legal risks and market concerns.

[1545] Step 8:

[1546] The server integrates feedback from the four AI agents and generates refined ideas.

[1547] Step 9:

[1548] The server returns the synthesized ideas to the user.

[1549] The first round of the contest

[1550] Step 1:

[1551] The user inputs an idea from a terminal and sends it to the server.

[1552] Step 2:

[1553] A server receives the submitted ideas.

[1554] Step 3:

[1555] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1556] Step 4:

[1557] The server assigns a score to each evaluation item.

[1558] Step 5:

[1559] The server calculates the overall score.

[1560] Step 6:

[1561] The server returns the evaluation results and feedback to the user.

[1562] Presentation file creation support

[1563] Step 1:

[1564] The user inputs the presentation content from the terminal and sends it to the server.

[1565] Step 2:

[1566] The server receives and analyzes the presentation content.

[1567] Step 3:

[1568] The server automatically selects a slide template.

[1569] Step 4:

[1570] The server generates the materials required for the presentation.

[1571] Step 5:

[1572] The user specifies the range or gives verbal instructions, which are then sent to the server.

[1573] Step 6:

[1574] The server adjusts the slides and materials based on the user's instructions.

[1575] Step 7:

[1576] The server generates the final presentation file and provides it to the user.

[1577] Automatic generation of mockup sites

[1578] Step 1:

[1579] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[1580] Step 2:

[1581] The server receives and analyzes the input information.

[1582] Step 3:

[1583] The server selects an appropriate mockup site template.

[1584] Step 4:

[1585] The server automatically generates a mockup site.

[1586] Step 5:

[1587] The server provides the generated mockup site to the user.

[1588] Presentation script creation

[1589] Step 1:

[1590] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[1591] Step 2:

[1592] The server receives and analyzes the presentation content and desired time.

[1593] Step 3:

[1594] The server calculates the appropriate time allocation for each slide or section.

[1595] Step 4:

[1596] The server automatically generates a presentation transcript.

[1597] Step 5:

[1598] The server provides the generated oral transcript to the user.

[1599] Step 6:

[1600] The user provides feedback and sends it to the server.

[1601] Step 7:

[1602] The server adjusts the manuscript based on the feedback.

[1603] The above are the detailed processing steps for each function of the Generative AI Contest Support System. Because the roles of the server, terminal, and user are clearly separated in each step, it is expected that the flow of the entire system will proceed smoothly.

[1604] Example 1

[1605] 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."

[1606] Conventional idea generation support systems and presentation material creation systems can only address user input from a single perspective, resulting in a lack of multifaceted refinement and optimization. Furthermore, automatic generation of presentation materials is problematic due to the difficulty of making appropriate adjustments based on specific user instructions, hindering efficient material creation. Therefore, there is a need for systems that can improve and evaluate ideas from multiple perspectives and support the creation of more flexible presentation materials.

[1607] 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.

[1608] In this invention, the server includes: means for receiving concepts entered by a user; means for distributing concepts to multiple AI agents with different characteristics, with each agent adding new perspectives and improvement suggestions; and means for integrating the concepts to which the new perspectives and improvement suggestions have been added and providing them to the user. This allows the user's ideas to be refined from multiple angles and improved to higher quality content. The server also includes means for evaluating the concepts submitted by the user based on evaluation criteria and means for returning the evaluation results to the user. This allows the submitted ideas to be objectively evaluated and the direction of improvement clarified. The server also includes means for analyzing presentation content and automatically generating visual materials, means for adjusting the visual materials based on user instructions, and means for generating and providing final presentation materials to the user. This allows presentation materials to be efficiently created and optimized in line with the user's intentions.

[1609] A "user" is a person or individual who accesses the system via a terminal and inputs concepts and instructions.

[1610] A "concept" refers to any or all of an idea or suggestion that a user inputs into the system.

[1611] "Multiple artificial intelligence agents with different characteristics" refers to multiple artificial intelligence-based software agents that have specific perspectives and characteristics and refine and consider ideas.

[1612] "Brushing up" refers to improving an idea or concept from multiple perspectives to raise its quality.

[1613] "Evaluation criteria" refers to the criteria or perspectives (e.g., creativity, feasibility, social impact, etc.) used to evaluate ideas and concepts.

[1614] "Visual materials" are visual documents such as slides, charts, and text generated for a presentation.

[1615] The embodiment of this invention is a system for effectively polishing and evaluating user ideas, creating presentation materials, generating mockup sites, and creating oral presentation scripts. This system operates based on communications between a server, terminals, and users.

[1616] The main hardware configuration of the system is as follows: The devices used by users include interface devices such as PCs, smartphones, and tablets. The server is a server machine equipped with a high-performance processor and large amount of memory, and it is also possible to use a cloud-based processing engine. The software consists of a generative AI model, a natural language processing (NLP) engine, and a database management system (DBMS).

[1617] Idea brush-up

[1618] 1. A user uses an input form on their device to enter their idea in text form into the system. For example, they enter their idea for a "new social networking app."

[1619] 2. The server receives the idea and stores it in a database. It then distributes the data to multiple AI agents (Dreamers, Enjoyers, Realists, and Critics). This process involves sending the idea data to each agent using an API.

[1620] 3. The Dreamer AI generates innovative ideas and big visions based on the prompt, "Add a new vision to this idea." For example, it adds "integration with VR."

[1621] 4. Based on the prompt, "Brush up this idea by adding entertainment elements," the Pleasure AI will output improvement proposals incorporating user experience and entertainment elements. For example, it will suggest "gamification elements."

[1622] 5. Based on the prompt, "Describe the technical steps required to realize this idea," the Realist AI will consider specific technical feasibility and propose technical implementations. For example, adding an "instant photo sharing function."

[1623] 6. Based on the prompt, "Please suggest the risks of this idea and how to improve it," the critic AI will extract risks and weaknesses and suggest ways to address them. For example, it will point out "privacy concerns."

[1624] 7. Finally, the server integrates the output of each agent and returns the integrated refinement idea to the user.

[1625] The first round of the contest

[1626] When a user submits an idea through an input form on their device, the server receives the idea and evaluates it based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.) using an AI model. The evaluation results are scored and sent back to the user as feedback.

[1627] Presentation file creation support

[1628] When a user inputs their presentation content from their device, the server receives it and analyzes it using a natural language processing engine. Based on the analysis results, it automatically selects a slide template and generates visual materials. If the user requests specific corrections or adjustments, the server adjusts the materials according to those instructions, generates the final presentation file, and provides it to the user.

[1629] Automatic generation of mockup sites

[1630] When a user inputs the specifications for a mockup website, the server receives them and selects a template. The server then automatically generates the mockup website and provides it to the user. For example, if a user requests, "Create a mockup website for a social networking app," the server generates a mockup website based on that information and provides it to the user as a URL or download link.

[1631] Presentation script creation

[1632] When a user inputs the content of their presentation and the desired presentation time, the server receives this, analyzes it, and allocates the appropriate time to each slide. Next, it automatically generates a presentation transcript and provides it to the user. If the user requests revisions, the server makes the revisions and provides it again. For example, if a user inputs a request for a "five-minute presentation," the server creates a transcript that fits within five minutes and provides it.

[1633] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1634] Idea brush-up

[1635] Step 1:

[1636] The user enters his / her idea into the system using an input form on the terminal.

[1637] Input: The user inputs an idea (e.g., "a new social networking app") in text format through the device.

[1638] Output: The entered text data is sent to the server.

[1639] Step 2:

[1640] The server receives the ideas, stores them in a database, and distributes the data to each AI agent.

[1641] Input: Idea data sent from the device.

[1642] Data processing: The server stores idea data in a database and distributes the data to multiple AI agents via API.

[1643] Output: Idea data is sent to each AI agent.

[1644] Step 3:

[1645] The Dreamer AI adds new perspectives and visions.

[1646] Input: Dreamer AI receives idea data.

[1647] Prompt: "Add a new vision to this idea"

[1648] Data Computation: Generative AI models add new perspectives and visions to ideas.

[1649] Output: Ideas with added novelty.

[1650] Step 4:

[1651] The enjoyment-loving AI improves ideas by taking into account user experience and entertainment elements.

[1652] Input: The Hedonist AI receives idea data.

[1653] Prompt: "Refine this idea by adding entertainment value."

[1654] Data Computation: Generative AI models make suggestions to improve the user experience.

[1655] Output: Ideas with an added entertainment element.

[1656] Step 5:

[1657] A realistic AI will consider feasibility and make specific technical proposals.

[1658] Input: Realist AI receives idea data.

[1659] Prompt: "Describe the technical steps required to realize this idea."

[1660] Data computation: Generative AI models propose technical implementations.

[1661] Output: Ideas with added technical feasibility.

[1662] Step 6:

[1663] The AI ​​critic points out risks and weaknesses and suggests areas for improvement.

[1664] Input: Critic AI receives idea data.

[1665] Prompt: "What are the risks of this idea and how can you improve it?"

[1666] Data calculation: The generative AI model analyzes risks and weaknesses and outputs improvement proposals.

[1667] Output: Ideas with added risks and weaknesses and suggestions for their improvement.

[1668] Step 7:

[1669] The server integrates the output of each AI agent, generates final refinement ideas, and provides them to the user.

[1670] Input: Ideas with refinements submitted by each AI agent.

[1671] Data processing: The server integrates all the improvement proposals and generates the final refinement ideas.

[1672] Output: The consolidated refinement ideas are returned to the user.

[1673] The first round of the contest

[1674] Step 1:

[1675] The user submits an idea through an input form on the device.

[1676] Input: User inputs their idea and clicks the submit button.

[1677] Output: The submitted ideas are sent to the server.

[1678] Step 2:

[1679] The server evaluates the submitted ideas based on the evaluation criteria.

[1680] Input: Idea data sent from the device.

[1681] Data calculation: The server generates an evaluation score based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.).

[1682] Output: Scoring data as the evaluation result.

[1683] Step 3:

[1684] The server returns the evaluation results to the user.

[1685] Input: Scoring data of evaluation results.

[1686] Data processing: The server compiles the evaluation results and generates feedback for the user.

[1687] Output: The evaluation results are sent to the user via email or notification.

[1688] Presentation file creation support

[1689] Step 1:

[1690] The user inputs the presentation content into the system from the terminal.

[1691] Input: The user inputs the presentation content in text format.

[1692] Output: The input presentation content is sent to the server.

[1693] Step 2:

[1694] The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[1695] Input: Presentation content data sent from the device.

[1696] Data Computing: Using natural language processing techniques, the presentation content is analyzed, appropriate slide templates are selected, and visual aids are generated.

[1697] Output: The generated visual aid.

[1698] Step 3:

[1699] The user indicates specific modifications or adjustments and the server adjusts the file accordingly.

[1700] Input: The user inputs correction instructions for a specific part.

[1701] Data calculation: The server modifies the visual materials based on the user's instructions.

[1702] Output: The corrected visual.

[1703] Step 4:

[1704] The server generates the final presentation file and provides it to the user.

[1705] Input: Visual data after corrections are complete.

[1706] Data processing: Generate the final presentation file.

[1707] Output: The generated presentation file is provided to the user.

[1708] Automatic generation of mockup sites

[1709] Step 1:

[1710] The user inputs the specifications of the mockup site into the system from a terminal.

[1711] Input: The user enters the specifications of the mockup site (page structure, functional requirements, etc.).

[1712] Output: The entered specification information is sent to the server.

[1713] Step 2:

[1714] The server analyzes the input information and selects a template.

[1715] Input: Specification information sent from the device.

[1716] Data calculation: The server analyzes the specification information and selects an appropriate template based on it.

[1717] Output: The selected template.

[1718] Step 3:

[1719] The server automatically generates a mockup site and provides it to the user.

[1720] Input: Selected template and specification information.

[1721] Data processing: Automatically generate a mockup site.

[1722] Output: The generated mockup site is provided to the user as a URL or download link.

[1723] Presentation script creation

[1724] Step 1:

[1725] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[1726] Input: The user inputs the presentation content and desired presentation time.

[1727] Output: The entered data is sent to the server.

[1728] Step 2:

[1729] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1730] Input: Presentation content sent from the device and desired presentation time.

[1731] Data calculation: Analyze the presentation content and calculate the appropriate time allocation for each slide.

[1732] Output: Time allocation data.

[1733] Step 3:

[1734] The server automatically generates a presentation manuscript and provides it to the user.

[1735] Input: Time allocation data and analysis results.

[1736] Data processing: Automatically generate oral presentation manuscripts.

[1737] Output: The generated transcript is provided to the user.

[1738] Step 4:

[1739] The user makes a correction request and the server adjusts the manuscript accordingly.

[1740] Input: The user inputs correction instructions for the oral manuscript.

[1741] Data calculation: The server adjusts the manuscript based on the correction instructions.

[1742] Output: The revised transcript is provided to the user again.

[1743] (Application example 1)

[1744] 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."

[1745] To efficiently create high-quality content, modern content creators need to collect, evaluate, and ensure consistency in various ideas. However, many creators face challenges such as limited ability to refine their own concepts and few opportunities to receive objective evaluation and feedback. Furthermore, creating optimal presentation materials and mockup websites takes time and effort. As a result, creative work stagnates, risking a decline in content quality.

[1746] 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.

[1747] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, means for evaluating and refining different content formats, and means for further evaluating and improving the idea integrated with improvements suggested by the user. This enables content creators to refine their ideas by receiving feedback from multiple perspectives and quickly create high-quality content.

[1748] "Means for receiving user-input ideas" refers to a function or module that receives, in digital form, ideas or concepts that users provide to the system.

[1749] "Multiple AI agents with different characteristics" are heterogeneous AI models, each with a specific perspective and role, that evaluate and improve ideas from different perspectives.

[1750] "Means for brushing up ideas" is a function that analyzes received ideas from multiple angles and adds improvements and new suggestions to further develop the ideas.

[1751] "Means for integrating refined ideas" is a function that synthesizes feedback and improvements from each AI agent and brings them together into a single integrated idea.

[1752] "Means to provide to users" refers to the ability to communicate the integrated ideas and proposed improvements to users in a clear and understandable format.

[1753] "A means to evaluate and refine different content formats" is a function that evaluates various forms of content, such as videos, articles, and podcasts, and suggests appropriate improvements for each.

[1754] "Suggestions for improving content quality based on feedback" is a function that provides specific advice for further improving content based on the evaluations and improvements received from users.

[1755] "Means for analyzing presentation content and automatically generating slides and materials" refers to a function that understands the content of a user's presentation and automatically creates appropriate slides and materials.

[1756] "Means for adjusting slides and materials based on user instructions" refers to a function for correcting and adjusting the content of already generated slides and materials in accordance with user requests and instructions.

[1757] The "means for automatically generating a content preview site" is a function that automatically creates a simple website or a preview page based on the user's ideas and content.

[1758] The present invention is a system that evaluates and improves ideas input by users from multiple angles and automatically generates high-quality content. Detailed embodiments of the system are described below.

[1759] System Configuration

[1760] The system operates based on communication between the server, terminals, and users, and uses smartphones (iOS or Android devices), Python, and OpenAI APIs as its main hardware and software.

[1761] Program processing

[1762] 1. A means of receiving user-entered ideas

[1763] Users input ideas into the system using their smartphones or PCs, and the ideas are sent to the server via the platform or application user interface.

[1764] 2. A way to share and refine ideas

[1765] The server distributes the received ideas to multiple AI agents with different characteristics. Each agent analyzes the idea from a specific perspective and generates improvements and new proposals. Specifically, the Dreamer AI is responsible for creative vision, the Hedonist AI for user experience, the Realist AI for feasibility, and the Critic AI for risk assessment.

[1766] 3. A way to integrate refined ideas

[1767] The feedback from each agent is integrated to generate a single improved idea. This integration process is carried out on the server and is reflected in the final result provided to the user.

[1768] 4. A way to evaluate and refine different content formats

[1769] The server provides feedback on various content formats, including videos, articles, and podcasts, and suggests appropriate improvements for each format, providing users with instructions to improve the quality of their content.

[1770] 5. A way to automatically generate a preview site for your content

[1771] The server automatically creates mockups and preview sites based on the generated ideas. These preview sites can be viewed in a browser, allowing users to see the final form of the content.

[1772] Usage example

[1773] As a specific example, a case will be described in which a user inputs an idea for an "introductory video for an environmentally friendly product." When the user inputs the idea into the system, the following process is carried out.

[1774] Visionary AI adds "vision of futuristic eco-technology"

[1775] The Hedonist AI recommends "visually appealing effects and music"

[1776] Realistic AI takes into account "specific product specifications and practical examples"

[1777] Critic AI points out "privacy and legal concerns"

[1778] This provides users with consolidated feedback, which allows them to create optimized content.

[1779] Prompt Sentence Examples

[1780] As a dreamer, please provide feedback on the following idea: A new cooking recipe sharing app

[1781] In this way, a system is provided that allows content creators to receive feedback from multiple perspectives and quickly create high-quality content.

[1782] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1783] Step 1:

[1784] The ideas entered by the user are sent from the device to the server. The user uses a smartphone or computer to enter their ideas and concepts into the system in text format. The entered ideas are sent to the server and stored in a database.

[1785] Input: Textual ideas from users

[1786] Output: Ideas stored in a database on the server

[1787] Step 2:

[1788] The server distributes ideas to multiple AI agents. The server retrieves ideas from a database and sends them to each agent (Dreamer, Enjoyer, Realist, Critic).

[1789] Input: Ideas retrieved from the database

[1790] Output: Ideas distributed to each agent

[1791] Step 3:

[1792] The Dreamer AI analyzes the idea and proposes a new creative vision. The server sends the idea to the Dreamer AI, and the Dreamer AI generates new visions and creative elements based on the idea.

[1793] Input: Ideas sent to the Dreamer AI

[1794] Output: Creative suggestions from the Dreamer AI

[1795] Step 4:

[1796] The Pleasure AI improves the idea by taking into account the user experience. The server sends the idea to the Pleasure AI, which then generates a proposal that incorporates entertainment elements and user experience into the idea.

[1797] Input: Idea sent to the Hedonist AI

[1798] Output: Suggestions from the Enjoyer AI to improve the user experience

[1799] Step 5:

[1800] The Realist AI considers the feasibility of the idea. The server sends the idea to the Realist AI, which then generates a concrete proposal that is feasible from a technical standpoint.

[1801] Input: Ideas sent to the Realist AI

[1802] Output: Feasible proposals from a realist AI

[1803] Step 6:

[1804] The critic AI evaluates the risk of ideas. The server sends ideas to the critic AI, which then points out risks and weaknesses and suggests ways to improve them.

[1805] Input: Ideas sent to the critic AI

[1806] Output: Risk assessment and improvement suggestions from the critic AI

[1807] Step 7:

[1808] The server integrates the feedback from each agent. The server receives feedback from each agent and synthesizes it into a single integrated idea, reconciling overlapping and contradictory points.

[1809] Input: Feedback from each agent

[1810] Output: Unified refinement proposal

[1811] Step 8:

[1812] The server provides the user with the integrated idea, which the user can then review and use. The user can then make further modifications as needed.

[1813] Input: Integrated refinement proposal

[1814] Output: Consolidated ideas provided to the user

[1815] Step 9:

[1816] The server evaluates and refines the content according to its format. It provides appropriate evaluation and feedback based on the format of the user-generated content (video, article, podcast, etc.) and generates suggestions to further improve the content.

[1817] Input: The format of the content provided by the user

[1818] Output: Evaluation and suggestions for improving the content

[1819] Step 10:

[1820] The server provides users with suggestions for improving the quality of content based on their feedback. The server reflects the feedback from each agent and proposes specific improvement actions to the user.

[1821] Input: Feedback from each agent

[1822] Output: Suggestions for improving the content provided to the user

[1823] 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.

[1824] This embodiment of the invention combines an emotion engine with a specialized system for supporting generative AI contests, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[1825] System Overview

[1826] The system has the following main functions:

[1827] 1. Idea brush-up (virtual brainstorming)

[1828] 2. Final round of the contest

[1829] 3. Presentation file creation support

[1830] 4. Automatic generation of mockup sites

[1831] 5. Preparation of oral presentation script

[1832] 6. Emotion Recognition and Adaptation with Emotion Engine

[1833] 1. Idea brush-up (virtual brainstorming)

[1834] 1. The user inputs an idea into the system from a terminal.

[1835] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[1836] 3. Visionary AI adds new ideas and big visions to ideas.

[1837] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[1838] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[1839] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[1840] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[1841] 8. The emotion engine analyzes the user's emotional data and makes adjustments based on the AI ​​agent's feedback.

[1842] Example: When a user suggests a "new social networking app," the Dreamer AI suggests "integration with VR," the Enjoyer AI suggests "gamification elements," the Realist AI adds "instant photo sharing functionality," and the Critic AI points out "privacy concerns." If the user expresses positive emotions toward the suggestion, the emotion engine takes this into account to further strengthen the idea.

[1843] 2. Final round of the contest

[1844] 1. The user submits an idea to the system from their device.

[1845] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1846] 3. The server returns the evaluation results to the user.

[1847] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[1848] 3. Presentation file creation support

[1849] 1. The user inputs the presentation content into the system from their device.

[1850] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[1851] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[1852] 4. The emotion engine analyzes the user's emotion data and adjusts the design and content of the material based on the user's emotions.

[1853] 5. The server generates the final presentation file and serves it to the user.

[1854] Example: A user inputs "business plan" and the server automatically generates slides. If the user says "add a graph to this part," the server adds the graph. Also, if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[1855] 4. Automatic generation of mockup sites

[1856] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[1857] 2. The server analyzes the input information and selects a template for the mockup site.

[1858] 3. The server automatically generates a mockup site.

[1859] 4. The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[1860] 5. The server serves the generated mockup site to the user.

[1861] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction, and the emotion engine observes the user's reaction, adjusts the color scheme and layout, and delivers the final site to the user.

[1862] 5. Preparation of oral presentation script

[1863] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[1864] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[1865] 3. The server automatically generates the oral presentation script.

[1866] 4. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[1867] 5. The server provides the generated oral transcript to the user.

[1868] 6. The server adjusts the manuscript based on user feedback.

[1869] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral script that fits within 5 minutes. If the user instructs the server to "explain this part in more detail," the server adds content that details the relevant part. Also, if the user is nervous, the emotion engine detects this and generates a script with a more relaxed tone.

[1870] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals. By combining it with an emotion engine, it is expected to provide output optimized for the user's emotional state, improving the user experience.

[1871] The processing flow will be explained below.

[1872] Idea brush-up (including emotion engine)

[1873] Step 1:

[1874] The user inputs an idea from a terminal and sends it to the server.

[1875] Step 2:

[1876] A server receives ideas from users.

[1877] Step 3:

[1878] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[1879] Step 4:

[1880] The Visionary AI adds new ideas and big visions to ideas, for example, proposing innovative technologies and generating future-oriented scenarios.

[1881] Step 5:

[1882] The Pleasure AI adds elements to ideas that enrich the user experience, such as suggesting easy-to-use interfaces and entertainment elements.

[1883] Step 6:

[1884] Realistic AI considers the feasibility of ideas and gives them technical realization, for example proposing a technology stack and designing a prototype.

[1885] Step 7:

[1886] The AI ​​critics point out risks and weaknesses in ideas and suggest areas for improvement, such as legal risks and market concerns.

[1887] Step 8:

[1888] The emotion engine analyzes the user's emotional data, for example, whether the user is excited or skeptical about an idea.

[1889] Step 9:

[1890] The server integrates feedback from each AI agent and generates refined ideas.

[1891] Step 10:

[1892] The emotion engine adjusts the final ideas based on the user's emotional data, for example adding more challenging ideas if the user is excited.

[1893] Step 11:

[1894] The server is integrated and sends the coordinated ideas back to the user.

[1895] The first round of the contest

[1896] Step 1:

[1897] The user inputs an idea from a terminal and sends it to the server.

[1898] Step 2:

[1899] A server receives the submitted ideas.

[1900] Step 3:

[1901] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[1902] Step 4:

[1903] The server assigns a score to each evaluation item.

[1904] Step 5:

[1905] The server calculates the overall score.

[1906] Step 6:

[1907] The server returns the evaluation results and feedback to the user.

[1908] Presentation file creation support

[1909] Step 1:

[1910] The user inputs the presentation content from the terminal and sends it to the server.

[1911] Step 2:

[1912] The server receives and analyzes the presentation content.

[1913] Step 3:

[1914] The server automatically selects a slide template.

[1915] Step 4:

[1916] The server generates the materials required for the presentation.

[1917] Step 5:

[1918] The user specifies the range or gives verbal instructions, which are then sent to the server.

[1919] Step 6:

[1920] The server adjusts the slides and materials based on the user's instructions.

[1921] Step 7:

[1922] The emotion engine analyzes the user's emotional data and adjusts the design and content of the materials based on the user's emotions. For example, if the user is nervous, it uses colors and designs that are relaxing.

[1923] Step 8:

[1924] The server generates the final presentation file and provides it to the user.

[1925] Automatic generation of mockup sites

[1926] Step 1:

[1927] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[1928] Step 2:

[1929] The server receives and analyzes the input information.

[1930] Step 3:

[1931] The server selects an appropriate mockup site template.

[1932] Step 4:

[1933] The server automatically generates a mockup site.

[1934] Step 5:

[1935] The emotion engine analyzes user emotion data and adjusts the site design and element placement. For example, if a user expresses positive emotions, the engine adds design elements that emphasize those emotions.

[1936] Step 6:

[1937] The server provides the generated mockup site to the user.

[1938] Presentation script creation

[1939] Step 1:

[1940] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[1941] Step 2:

[1942] The server receives and analyzes the presentation content and desired time.

[1943] Step 3:

[1944] The server calculates the appropriate time allocation for each slide or section.

[1945] Step 4:

[1946] The server automatically generates a presentation transcript.

[1947] Step 5:

[1948] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript. For example, if the user is nervous, the engine will generate a manuscript with a relaxed tone.

[1949] Step 6:

[1950] The server provides the generated oral transcript to the user.

[1951] Step 7:

[1952] The user provides feedback and sends it to the server.

[1953] Step 8:

[1954] The server adjusts the manuscript based on the feedback.

[1955] The above are the detailed processing steps for each function of the generative AI contest support system that combines an emotion engine. In each step, the roles of the server, terminal, and user are clearly separated, and it is expected that the overall system will proceed smoothly. The incorporation of an emotion engine makes it possible to adapt to the user's emotional state, providing more effective and personalized support.

[1956] Example 2

[1957] 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."

[1958] This invention relates to a system that can provide optimal feedback and output by taking into account the user's emotional state during processes such as refining and evaluating ideas in contests and supporting the creation of presentations. Conventional systems often refine ideas or create presentation materials without taking the user's emotions into account, making it difficult to achieve user-friendly and effective results. Furthermore, because they are unable to optimally adjust to the user's emotional state, they are unable to improve user satisfaction or the quality of proposals.

[1959] 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.

[1960] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, and emotion engine means for analyzing the user's emotion data and making adjustments based on feedback from the AI ​​agents. This makes it possible to provide feedback and output optimized for the user's emotional state, enabling user-friendly and effective idea refinement and the creation of presentation materials.

[1961] "User" refers to the entity that inputs ideas and presentation content into the system and receives feedback and output based on them.

[1962] "Terminal" refers to an apparatus or device for transmitting information entered by a user to a system.

[1963] "Server" refers to a central system that receives and processes information sent by users.

[1964] An "artificial intelligence agent" is a program that has specific characteristics and roles, analyzes input information, and refines ideas based on those characteristics.

[1965] A "dreamer agent" refers to an artificial intelligence agent that has the ability to add new ideas and big visions.

[1966] A "pleasure agent" refers to an artificial intelligence agent that has the ability to improve ideas by taking into account user experience and entertainment elements.

[1967] A "realist agent" is an artificial intelligence agent that has the ability to consider the feasibility of ideas and bring them to technical realization.

[1968] A "critic agent" is an artificial intelligence agent that has the ability to point out the risks and weaknesses of an idea and suggest areas for improvement.

[1969] An "emotion engine" is a program that analyzes the user's emotional data and makes optimal adjustments based on feedback from the AI ​​agent.

[1970] "Brushing up" refers to the process of making improvements and additions to an input idea to make it better.

[1971] "Presentation" refers to materials and presentations that visually and verbally express the information or proposals that a user wants to show.

[1972] A "mockup site" is a prototype of a website or application that does not replicate actual functionality but instead provides a visual representation of the design and user interface.

[1973] "Preliminary judging" refers to the first idea evaluation process in a contest.

[1974] This invention combines an emotion engine with a specialized system for generative AI contest support, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[1975] To implement this system, the following major components are required:

[1976] 1. Idea brush-up (virtual brainstorming)

[1977] 2. Final round of the contest

[1978] 3. Presentation file creation support

[1979] 4. Automatic generation of mockup sites

[1980] 5. Preparation of oral presentation script

[1981] 6. Emotion Recognition and Adaptation with Emotion Engine

[1982] Idea brush-up (virtual brainstorming)

[1983] When a user inputs a new idea into the system from a terminal, the server receives the idea. The server distributes the idea to several artificial intelligence (AI) agents with different characteristics: the Dreamer, the Hedonist, the Realist, and the Critic. Each AI agent behaves according to its characteristics as follows:

[1984] Visionary agents add new ideas and big visions to ideas.

[1985] The hedonist agent improves ideas by taking into account user experience and entertainment factors.

[1986] The realist agent considers the feasibility of the idea and gives it technical realization.

[1987] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[1988] The server integrates these outputs and presents the refined idea to the user. The emotion engine also analyzes the user's emotional data and makes adjustments based on the AI ​​agents' feedback. For example, if a user suggests a "new social media app," the dreamer agent might suggest "integration with VR," the hedonist agent might suggest "gamification elements," the realist agent might add "instant photo sharing functionality," and the critic agent might point out "privacy concerns." If the user expresses positive emotions toward the proposal, the emotion engine takes this into account to further strengthen the idea.

[1989] The first round of the contest

[1990] When a user submits an idea to the system from their device, the server receives the idea. The server evaluates the idea based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.) and returns the evaluation results to the user. For example, if a user submits an "environmentally friendly product," the server will evaluate it based on creativity, feasibility, and social impact, and provide the evaluation results as feedback to the user.

[1991] Presentation file creation support

[1992] When a user inputs the content of their presentation into the system from their device, the server analyzes the content, automatically selects a slide template, and generates the presentation material. The user specifies the range or gives verbal instructions, and the server adjusts the file accordingly. The emotion engine also analyzes the user's emotional data and adjusts the design and content of the presentation material based on the user's emotions. The server generates the final presentation file and provides it to the user. For example, a user inputs "business plan" and the server automatically generates slides. If the user instructs "add a graph to this part," the server adds the graph, and if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[1993] Automatic generation of mockup sites

[1994] When a user inputs the specifications of a mockup site into the system from their device, the server analyzes the input information and selects a template for the mockup site. The server then automatically generates the mockup site, and the emotion engine analyzes the user's emotional data and adjusts the site's design and element placement. Finally, the server provides the generated mockup site to the user. For example, if a user instructs the server to "create a mockup site for a social networking app," the server generates the mockup site based on that information, and the emotion engine adjusts the color scheme and layout based on the user's reaction, and provides the final site to the user.

[1995] Presentation script creation

[1996] When a user inputs the presentation content and desired presentation time into the system from their device, the server analyzes the presentation content and calculates the appropriate time allocation for each slide and section. The server then automatically generates an oral presentation script. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the script. The final oral presentation script is provided to the user, and the server adjusts the script based on feedback from the user. For example, if a user inputs a request for a "five-minute presentation," the server will create and provide an oral presentation script that fits within five minutes. If the user instructs the server to "explain this part in more detail," the server will add content that details the relevant part, and if the user is nervous, the emotion engine will detect this and generate a script with a more relaxed tone.

[1997] In this way, the present invention can provide optimal feedback and output according to the user's emotional state, thereby improving the quality of ideas, reducing the burden of creating presentation materials, and being extremely useful in making competitive proposals.

[1998] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1999] Idea brush-up (virtual brainstorming)

[2000] Step 1:

[2001] The user inputs an idea from the terminal.

[2002] Enter: an idea for a new social media app.

[2003] Output: Idea data sent to the system.

[2004] Specific operation: The user enters their idea for a "new SNS app" into the input form on the device and clicks the "Submit" button.

[2005] Step 2:

[2006] The server receives the idea.

[2007] Input: Idea data submitted by the user.

[2008] Output: Idea data distributed to multiple artificial intelligence agents with different characteristics.

[2009] Specific operation: The server analyzes the received idea data and sends it to the dreamer agent, the hedonist agent, the realist agent, and the critic agent.

[2010] Step 3:

[2011] Visionary agents add new ideas and big visions to your ideas.

[2012] Input: Idea data sent to the Dreamer Agent.

[2013] Output: Idea data with new ideas and visions added.

[2014] Specific operation: In response to the prompt "Propose a new vision or idea for a social networking app," the dreamer agent generates and outputs an idea for VR integration.

[2015] Step 4:

[2016] The hedonistic agent considers user experience and entertainment elements to improve the idea.

[2017] Input: Idea data sent to the hedonist agent.

[2018] Output: Idea data with improved user experience and entertainment elements added.

[2019] Specific operation: The hedonist agent proposes gamification elements based on the prompt "Elements that will enrich the user experience" and outputs them.

[2020] Step 5:

[2021] A realist agent considers the feasibility of the idea and gives it technical realization.

[2022] Input: Idea data sent to the Realist agent.

[2023] Output: Technically embodied idea data.

[2024] Specific behavior: The realist agent receives the prompt "technically feasible specific proposal," generates a proposal to add an instant photo sharing function, and outputs it.

[2025] Step 6:

[2026] Critic agents point out the risks and weaknesses of an idea and suggest areas for improvement.

[2027] Input: Idea data sent to the critic agent.

[2028] Output: Idea data with risks and weaknesses pointed out and improvements added.

[2029] Specific behavior: Based on the prompt "Point out risks and weaknesses," the critic agent points out privacy concerns and outputs suggestions for improvement.

[2030] Step 7:

[2031] The server integrates the output of each agent, generates refined ideas, and provides them to the user.

[2032] Input: Refined idea data sent by each agent.

[2033] Output: A final, consolidated and refined idea.

[2034] Specific operation: The server integrates the data received from each agent and generates a final idea to send back to the user.

[2035] Step 8:

[2036] The emotion engine analyzes the user's emotional data and makes adjustments based on the feedback.

[2037] Input: User emotion data and final idea data.

[2038] Output: Final ideas adjusted based on user sentiment.

[2039] Specific operation: The emotion engine analyzes the user's emotion data, and if the user expresses positive emotions, it makes adjustments to further strengthen the idea.

[2040] The first round of the contest

[2041] Step 1:

[2042] A user submits an idea to the system from a terminal.

[2043] Input: Idea data to be submitted.

[2044] Output: The idea data sent to the system.

[2045] Specific operation: The user enters their idea for an "environmentally friendly product" into the input form on the device and clicks the "Submit" button.

[2046] Step 2:

[2047] The server evaluates the ideas based on the contest's evaluation criteria.

[2048] Input: Submitted idea data.

[2049] Output: Evaluation results based on the evaluation criteria.

[2050] Specific operation: The server evaluates the received idea data based on evaluation criteria (creativity, feasibility, social impact, etc.) and tally up the evaluation scores.

[2051] Step 3:

[2052] The server returns the evaluation results to the user.

[2053] Input: Evaluation result data.

[2054] Output: The evaluation results that are displayed to the user.

[2055] Specific operation: The server generates the evaluation results, displays them to the user, and sends them as feedback.

[2056] Presentation file creation support

[2057] Step 1:

[2058] The user inputs the presentation content into the system from the terminal.

[2059] Input: Presentation content data.

[2060] Output: Presentation content data sent to the system.

[2061] Specific operation: The user enters the details of the "business plan" into the input form on the terminal and clicks the "Submit" button.

[2062] Step 2:

[2063] The server analyzes the presentation content, automatically selects a slide template, and generates materials.

[2064] Input: Presentation content data.

[2065] Output: Selected slide templates and generated data.

[2066] Specific operation: The server analyzes the presentation content, selects an appropriate slide template, and generates the materials.

[2067] Step 3:

[2068] The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[2069] Input: Range specification or verbal instruction data from the user.

[2070] Output: Adjusted presentation data.

[2071] Specific operation: When the user instructs, for example, "Add a graph to this part," the server adds the graph based on that instruction.

[2072] Step 4:

[2073] The emotion engine analyzes the user's emotional data and adjusts the design and content of the document.

[2074] Input: User emotion data and presentation data.

[2075] Output: Presentation materials tailored based on user sentiment.

[2076] What it does: The emotion engine analyzes the user's emotions and, for example, if the user is excited, adds more attractive visualizations to the slides.

[2077] Step 5:

[2078] The server generates the final presentation file and provides it to the user.

[2079] Input: Adjusted presentation data.

[2080] Output: Final presentation file.

[2081] What happens: The server assembles the final presentation file and serves it to the user.

[2082] Automatic generation of mockup sites

[2083] Step 1:

[2084] The user inputs the specifications of the mockup site into the system from a terminal.

[2085] Input: Mockup site specification data.

[2086] Output: The specification data sent to the system.

[2087] Specific operation: The user enters, for example, "I would like you to create a mockup site for a social networking app" into the input form on the device and clicks the "Submit" button.

[2088] Step 2:

[2089] The server analyzes the input information and selects a template for the mockup site.

[2090] Input: Mockup site specification data.

[2091] Output: The selected template data.

[2092] Specific operation: The server analyzes the input specification data and selects an appropriate mockup site template.

[2093] Step 3:

[2094] The server automatically generates a mockup site.

[2095] Input: Selected template data and specification data.

[2096] Output: An automatically generated mockup site.

[2097] What happens: The server generates a mockup site based on the template and specification data.

[2098] Step 4:

[2099] The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[2100] Input: User emotion data and generated mockup site.

[2101] Output: A tailored mockup site.

[2102] Specific behavior: The emotion engine analyzes the user's emotion data and adjusts the color scheme and layout.

[2103] Step 5:

[2104] The server provides the generated mockup site to the user.

[2105] Input: The adjusted mockup site.

[2106] Output: The final mockup site that is provided to the user.

[2107] Specific operation: The server generates the final mockup site and provides it to the user.

[2108] Presentation script creation

[2109] Step 1:

[2110] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[2111] Input: Presentation content data and desired time data.

[2112] Output: Presentation content and desired time data sent to the system.

[2113] Specific operation: The user enters the presentation content and desired time (e.g., "5-minute presentation") into the input form on the device and clicks the "Send" button.

[2114] Step 2:

[2115] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[2116] Input: Presentation content data and desired time data.

[2117] Output: A presentation outline based on appropriate time allocation.

[2118] What it does: The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[2119] Step 3:

[2120] The server automatically generates a presentation transcript.

[2121] Input: Presentation content data and time allocation data.

[2122] Output: The generated oral presentation transcript.

[2123] Specific operation: The server automatically creates a presentation manuscript based on the time allocation.

[2124] Step 4:

[2125] The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[2126] Input: User emotion data and generated oral presentation script.

[2127] Output: Adjusted oral presentation transcript.

[2128] Specific operation: The emotion engine analyzes the user's emotional data and adjusts the manuscript according to the emotion, such as by using a relaxed tone of voice.

[2129] Step 5:

[2130] The server provides the generated oral transcript to the user.

[2131] Input: Adjusted oral presentation transcript.

[2132] Output: The final presentation transcript provided to the user.

[2133] Specific operation: The server generates the final presentation transcript and provides it to the user.

[2134] Step 6:

[2135] The server adjusts the manuscript according to the user's feedback.

[2136] Input: Feedback data from users.

[2137] Output: Adjusted oral presentation transcript.

[2138] Specific operation: When the user gives feedback such as "Please explain this part in more detail," the server adds or corrects the relevant part in detail based on the user's instructions.

[2139] This process not only allows users to improve the quality of their ideas, but also allows them to receive feedback and output that is optimized for their emotional state, enabling them to create effective presentations and attractive mockup sites.

[2140] (Application example 2)

[2141] 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."

[2142] There is a need for technology to improve productivity and safety when using assistive robots in factories today. Furthermore, there are few systems that provide feedback or suggest work improvements that take into account the emotional state of workers, making it difficult to provide appropriate assistance based on their emotional state. There is a need for a system that can solve this problem.

[2143] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2144] In this invention, the server includes a means for analyzing the user's emotional data and adjusting the feedback of the generating AI agent based on the emotion, a means for receiving ideas input by the user, a means for distributing the ideas to multiple AI agents with different characteristics and having each agent refine the idea, and a means for integrating the refined ideas and providing them to the user. This makes it possible to propose appropriate work improvements and improve safety based on the worker's emotional state.

[2145] 1. "User" means a person or group who uses the system to input ideas, evaluate them, and receive feedback.

[2146] 2. "Emotional data" refers to information that indicates a user's emotional state, such as text, audio, images, or data obtained from sensors.

[2147] 3. "Generative AI agents" are multiple artificial intelligences that analyze users' ideas from different perspectives and provide improvement suggestions and feedback.

[2148] 4. "Feedback" refers to improvement suggestions and evaluation results for ideas refined by the generating AI agent.

[2149] 5. "Agents with different characteristics" are AIs that analyze ideas from different perspectives and criteria, such as dreamers, hedonists, realists, and critics.

[2150] 6. "Idea brush-up" is a process in which multiple AI agents improve an idea entered by a user and turn it into a better version.

[2151] 7. "Idea distribution" is the process of sending a user's input ideas to multiple artificial intelligence agents with different characteristics.

[2152] 8. A "system" is a complex collection of machines and software that handles everything from user idea input to evaluation, refinement, and feedback.

[2153] 9. A "refined idea" is an idea that has been improved by multiple AI agents with different perspectives.

[2154] 10. "Presentation Materials" means materials such as slides and documents used by Users when giving presentations.

[2155] 11. "Final presentation file" refers to the presentation materials that are finally generated based on the user's instructions and emotional data.

[2156] This paper describes a system applied to an assistive robot that supports workers in a factory. The system's program processing is explained in natural language below, and the specific names of the hardware and software used are specified.

[2157] Hardware:

[2158] 1. Emotion data acquisition devices: Wearable devices and cameras for acquiring workers' emotional data.

[2159] 2. Assistive robots: Physical robots that interact directly with workers.

[2160] software:

[2161] 1. Emotion engine: A module that analyzes user emotion data.

[2162] 2. Generative AI Agents: Artificial intelligence agents with multiple characteristics (e.g., Dreamer AI, Hedonist AI, Realist AI, Critic AI).

[2163] 3. Integrated system: A system that integrates feedback from different agents and provides it to the user.

[2164] Data processing and calculation:

[2165] 1. Emotion data acquisition: The terminal acquires the worker's emotion data from a wearable device or camera.

[2166] 2. Emotion analysis: The server analyzes the emotion data using an emotion engine to determine the worker's current emotional state.

[2167] 3. Idea sharing and polishing:

[2168] The server distributes work improvement ideas to the generated AI agents.

[2169] Each agent improves the idea from a different perspective and generates feedback.

[2170] 4. Feedback integration: The server integrates the feedback from each generated AI agent and provides it to the user.

[2171] 5. Emotion-based adjustment: The emotion engine adjusts the generated feedback and presentation materials based on the user's emotional state.

[2172] Examples:

[2173] If a worker feels "tired today," enter the following prompt:

[2174] Prompt: "I'm feeling tired today. How can I improve my work efficiency?"

[2175] Based on this prompt, the server does the following:

[2176] The emotion engine detects "fatigue" and notifies the generative AI agent of this emotional state.

[2177] The generative AI agent generates specific support suggestions, such as "take a break" or "recheck your work procedures."

[2178] The server integrates these suggestions and provides feedback to the worker via the assist robot.

[2179] Ultimately, workers can receive appropriate support according to their emotional state, improving work efficiency and safety.

[2180] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2181] Step 1:

[2182] The user inputs emotional data using a terminal. For example, the user inputs, "I feel tired today. How can I improve my work efficiency?" This input becomes the initial data for the system.

[2183] Step 2:

[2184] The device collects emotional data and sends it to the server. The input emotional data is text information that indicates the emotional state. The device processes the data and converts it into a format that can be sent to the server. The input data is sent to the server, and the server receives the data for further processing.

[2185] Step 3:

[2186] The server analyzes the emotional data using an emotion engine. The server accepts the analyzed emotional data and determines the emotional state, such as "fatigue" or "stress." The input in this step is "user's emotional data," and the output is "analyzed emotional state."

[2187] Step 4:

[2188] The server distributes work improvement ideas to the generating AI agents. Based on the analyzed emotional state, the server sends requests to the generating AI agents for appropriate improvement proposals. The input is the "analyzed emotional state," and the output is "requests to multiple generating AI agents."

[2189] Step 5:

[2190] The generative AI agent generates work improvement suggestions based on the user's emotional state. Each agent (Dreamer AI, Hedonist AI, Realist AI, Critic AI) generates ideas from their own perspective. The input is a "request from the server" and the output is a "suggestion for work improvement."

[2191] Step 6:

[2192] The server aggregates the feedback from the generating AI agents. The server combines the feedback received from each generating AI agent into a single aggregated proposal. The input is the "feedback from the generating AI agent" and the output is the "aggregated proposal."

[2193] Step 7:

[2194] The server sends the integrated suggestion to the assist robot, which uses this information to provide feedback to the user. The input is the "integrated suggestion" and the output is "feedback information to the assist robot."

[2195] Step 8:

[2196] The assist robot makes a suggestion to the user. For example, the assist robot may suggest to the user, "You seem tired. I recommend you take a break." The input is "feedback information from the server," and the output is "feedback to the user."

[2197] 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.

[2198] 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.

[2199] 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.

[2200] [Fourth embodiment]

[2201] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2202] 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.

[2203] 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).

[2204] 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.

[2205] 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.

[2206] 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).

[2207] 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.

[2208] 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.

[2209] 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.

[2210] 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.

[2211] 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.

[2212] 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.

[2213] 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."

[2214] The embodiment of this invention is a specialized system for supporting generative AI contests, which effectively refines users' ideas and assists in the creation of presentation materials, mockup sites, and oral manuscripts. This system operates based on communications between a server, terminals, and users.

[2215] System Overview

[2216] The system has the following main functions:

[2217] 1. Idea brush-up (virtual brainstorming)

[2218] 2. Final round of the contest

[2219] 3. Presentation file creation support

[2220] 4. Automatic generation of mockup sites

[2221] 5. Preparation of oral presentation script

[2222] 1. Idea brush-up (virtual brainstorming)

[2223] 1. The user inputs an idea into the system from a terminal.

[2224] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[2225] 3. Visionary AI adds new ideas and big visions to ideas.

[2226] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[2227] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[2228] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[2229] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[2230] Example: When a user suggests a "new social networking app," the dreamer AI adds "VR integration," the enjoyer AI suggests "gamification elements," the realist AI adds "instant photo sharing functionality," and the critic AI points out "privacy concerns." The final integrated idea is sent back to the user.

[2231] 2. Final round of the contest

[2232] 1. The user submits an idea to the system from their device.

[2233] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[2234] 3. The server returns the evaluation results to the user.

[2235] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[2236] 3. Presentation file creation support

[2237] 1. The user inputs the presentation content into the system from their device.

[2238] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[2239] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[2240] 4. The server generates the final presentation file and serves it to the user.

[2241] Example: A user inputs a "business plan" and the server automatically generates slides. When the user instructs "add a graph to this section," the server adds the graph.

[2242] 4. Automatic generation of mockup sites

[2243] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[2244] 2. The server analyzes the input information and selects a template for the mockup site.

[2245] 3. The server automatically generates a mockup site and provides it to the user.

[2246] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction and provides it to the user.

[2247] 5. Preparation of oral presentation script

[2248] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[2249] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[2250] 3. The server automatically generates a presentation transcript and provides it to the user.

[2251] 4. The server adjusts the manuscript based on user feedback.

[2252] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral manuscript that fits within 5 minutes. When the user instructs, "Please explain this part in more detail," the server adds content that details the relevant part.

[2253] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals.

[2254] The processing flow will be explained below.

[2255] Idea brush-up (virtual brainstorming)

[2256] Step 1:

[2257] The user inputs an idea from a terminal and sends it to the server.

[2258] Step 2:

[2259] A server receives ideas from users.

[2260] Step 3:

[2261] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[2262] Step 4:

[2263] The Visionary AI adds new ideas and big visions to ideas, specifically proposing future-oriented scenarios and new concepts to ideas.

[2264] Step 5:

[2265] The Hedonist AI adds elements to ideas that enrich the user experience, such as entertainment elements and improvements to user interaction.

[2266] Step 6:

[2267] Realistic AI considers the feasibility of ideas and gives them technical specificity, for example by proposing a tech stack and adding prototype designs.

[2268] Step 7:

[2269] The AI ​​critic points out the risks and weaknesses of an idea and suggests ways to improve it, specifically highlighting legal risks and market concerns.

[2270] Step 8:

[2271] The server integrates feedback from the four AI agents and generates refined ideas.

[2272] Step 9:

[2273] The server returns the synthesized ideas to the user.

[2274] The first round of the contest

[2275] Step 1:

[2276] The user inputs an idea from a terminal and sends it to the server.

[2277] Step 2:

[2278] A server receives the submitted ideas.

[2279] Step 3:

[2280] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[2281] Step 4:

[2282] The server assigns a score to each evaluation item.

[2283] Step 5:

[2284] The server calculates the overall score.

[2285] Step 6:

[2286] The server returns the evaluation results and feedback to the user.

[2287] Presentation file creation support

[2288] Step 1:

[2289] The user inputs the presentation content from the terminal and sends it to the server.

[2290] Step 2:

[2291] The server receives and analyzes the presentation content.

[2292] Step 3:

[2293] The server automatically selects a slide template.

[2294] Step 4:

[2295] The server generates the materials required for the presentation.

[2296] Step 5:

[2297] The user specifies the range or gives verbal instructions, which are then sent to the server.

[2298] Step 6:

[2299] The server adjusts the slides and materials based on the user's instructions.

[2300] Step 7:

[2301] The server generates the final presentation file and provides it to the user.

[2302] Automatic generation of mockup sites

[2303] Step 1:

[2304] The user inputs the specifications of the mockup site from the terminal and sends them to the server.

[2305] Step 2:

[2306] The server receives and analyzes the input information.

[2307] Step 3:

[2308] The server selects an appropriate mockup site template.

[2309] Step 4:

[2310] The server automatically generates a mockup site.

[2311] Step 5:

[2312] The server provides the generated mockup site to the user.

[2313] Presentation script creation

[2314] Step 1:

[2315] The user inputs the content of the presentation and the desired presentation time from the terminal and transmits them to the server.

[2316] Step 2:

[2317] The server receives and analyzes the presentation content and desired time.

[2318] Step 3:

[2319] The server calculates the appropriate time allocation for each slide or section.

[2320] Step 4:

[2321] The server automatically generates a presentation transcript.

[2322] Step 5:

[2323] The server provides the generated oral transcript to the user.

[2324] Step 6:

[2325] The user provides feedback and sends it to the server.

[2326] Step 7:

[2327] The server adjusts the manuscript based on the feedback.

[2328] The above are the detailed processing steps for each function of the Generative AI Contest Support System. Because the roles of the server, terminal, and user are clearly separated in each step, it is expected that the flow of the entire system will proceed smoothly.

[2329] Example 1

[2330] 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."

[2331] Conventional idea generation support systems and presentation material creation systems can only address user input from a single perspective, resulting in a lack of multifaceted refinement and optimization. Furthermore, automatic generation of presentation materials is problematic due to the difficulty of making appropriate adjustments based on specific user instructions, hindering efficient material creation. Therefore, there is a need for systems that can improve and evaluate ideas from multiple perspectives and support the creation of more flexible presentation materials.

[2332] 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.

[2333] In this invention, the server includes: means for receiving concepts entered by a user; means for distributing concepts to multiple AI agents with different characteristics, with each agent adding new perspectives and improvement suggestions; and means for integrating the concepts to which the new perspectives and improvement suggestions have been added and providing them to the user. This allows the user's ideas to be refined from multiple angles and improved to higher quality content. The server also includes means for evaluating the concepts submitted by the user based on evaluation criteria and means for returning the evaluation results to the user. This allows the submitted ideas to be objectively evaluated and the direction of improvement clarified. The server also includes means for analyzing presentation content and automatically generating visual materials, means for adjusting the visual materials based on user instructions, and means for generating and providing final presentation materials to the user. This allows presentation materials to be efficiently created and optimized in line with the user's intentions.

[2334] A "user" is a person or individual who accesses the system via a terminal and inputs concepts and instructions.

[2335] A "concept" refers to any or all of an idea or suggestion that a user inputs into the system.

[2336] "Multiple artificial intelligence agents with different characteristics" refers to multiple artificial intelligence-based software agents that have specific perspectives and characteristics and refine and consider ideas.

[2337] "Brushing up" refers to improving an idea or concept from multiple perspectives to raise its quality.

[2338] "Evaluation criteria" refers to the criteria or perspectives (e.g., creativity, feasibility, social impact, etc.) used to evaluate ideas and concepts.

[2339] "Visual materials" are visual documents such as slides, charts, and text generated for a presentation.

[2340] The embodiment of this invention is a system for effectively polishing and evaluating user ideas, creating presentation materials, generating mockup sites, and creating oral presentation scripts. This system operates based on communications between a server, terminals, and users.

[2341] The main hardware configuration of the system is as follows: The devices used by users include interface devices such as PCs, smartphones, and tablets. The server is a server machine equipped with a high-performance processor and large amount of memory, and it is also possible to use a cloud-based processing engine. The software consists of a generative AI model, a natural language processing (NLP) engine, and a database management system (DBMS).

[2342] Idea brush-up

[2343] 1. A user uses an input form on their device to enter their idea in text form into the system. For example, they enter their idea for a "new social networking app."

[2344] 2. The server receives the idea and stores it in a database. It then distributes the data to multiple AI agents (Dreamers, Enjoyers, Realists, and Critics). This process involves sending the idea data to each agent using an API.

[2345] 3. The Dreamer AI generates innovative ideas and big visions based on the prompt, "Add a new vision to this idea." For example, it adds "integration with VR."

[2346] 4. Based on the prompt, "Brush up this idea by adding entertainment elements," the Pleasure AI will output improvement proposals incorporating user experience and entertainment elements. For example, it will suggest "gamification elements."

[2347] 5. Based on the prompt, "Describe the technical steps required to realize this idea," the Realist AI will consider specific technical feasibility and propose technical implementations. For example, adding an "instant photo sharing function."

[2348] 6. Based on the prompt, "Please suggest the risks of this idea and how to improve it," the critic AI will extract risks and weaknesses and suggest ways to address them. For example, it will point out "privacy concerns."

[2349] 7. Finally, the server integrates the output of each agent and returns the integrated refinement idea to the user.

[2350] The first round of the contest

[2351] When a user submits an idea through an input form on their device, the server receives the idea and evaluates it based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.) using an AI model. The evaluation results are scored and sent back to the user as feedback.

[2352] Presentation file creation support

[2353] When a user inputs their presentation content from their device, the server receives it and analyzes it using a natural language processing engine. Based on the analysis results, it automatically selects a slide template and generates visual materials. If the user requests specific corrections or adjustments, the server adjusts the materials according to those instructions, generates the final presentation file, and provides it to the user.

[2354] Automatic generation of mockup sites

[2355] When a user inputs the specifications for a mockup website, the server receives them and selects a template. The server then automatically generates the mockup website and provides it to the user. For example, if a user requests, "Create a mockup website for a social networking app," the server generates a mockup website based on that information and provides it to the user as a URL or download link.

[2356] Presentation script creation

[2357] When a user inputs the content of their presentation and the desired presentation time, the server receives this, analyzes it, and allocates the appropriate time to each slide. Next, it automatically generates a presentation transcript and provides it to the user. If the user requests revisions, the server makes the revisions and provides it again. For example, if a user inputs a request for a "five-minute presentation," the server creates a transcript that fits within five minutes and provides it.

[2358] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2359] Idea brush-up

[2360] Step 1:

[2361] The user enters his / her idea into the system using an input form on the terminal.

[2362] Input: The user inputs an idea (e.g., "a new social networking app") in text format through the device.

[2363] Output: The entered text data is sent to the server.

[2364] Step 2:

[2365] The server receives the ideas, stores them in a database, and distributes the data to each AI agent.

[2366] Input: Idea data sent from the device.

[2367] Data processing: The server stores idea data in a database and distributes the data to multiple AI agents via API.

[2368] Output: Idea data is sent to each AI agent.

[2369] Step 3:

[2370] The Dreamer AI adds new perspectives and visions.

[2371] Input: Dreamer AI receives idea data.

[2372] Prompt: "Add a new vision to this idea"

[2373] Data Computation: Generative AI models add new perspectives and visions to ideas.

[2374] Output: Ideas with added novelty.

[2375] Step 4:

[2376] The enjoyment-loving AI improves ideas by taking into account user experience and entertainment elements.

[2377] Input: The Hedonist AI receives idea data.

[2378] Prompt: "Refine this idea by adding entertainment value."

[2379] Data Computation: Generative AI models make suggestions to improve the user experience.

[2380] Output: Ideas with an added entertainment element.

[2381] Step 5:

[2382] A realistic AI will consider feasibility and make specific technical proposals.

[2383] Input: Realist AI receives idea data.

[2384] Prompt: "Describe the technical steps required to realize this idea."

[2385] Data computation: Generative AI models propose technical implementations.

[2386] Output: Ideas with added technical feasibility.

[2387] Step 6:

[2388] The AI ​​critic points out risks and weaknesses and suggests areas for improvement.

[2389] Input: Critic AI receives idea data.

[2390] Prompt: "What are the risks of this idea and how can you improve it?"

[2391] Data calculation: The generative AI model analyzes risks and weaknesses and outputs improvement proposals.

[2392] Output: Ideas with added risks and weaknesses and suggestions for their improvement.

[2393] Step 7:

[2394] The server integrates the output of each AI agent, generates final refinement ideas, and provides them to the user.

[2395] Input: Ideas with refinements submitted by each AI agent.

[2396] Data processing: The server integrates all the improvement proposals and generates the final refinement ideas.

[2397] Output: The consolidated refinement ideas are returned to the user.

[2398] The first round of the contest

[2399] Step 1:

[2400] The user submits an idea through an input form on the device.

[2401] Input: User inputs their idea and clicks the submit button.

[2402] Output: The submitted ideas are sent to the server.

[2403] Step 2:

[2404] The server evaluates the submitted ideas based on the evaluation criteria.

[2405] Input: Idea data sent from the device.

[2406] Data calculation: The server generates an evaluation score based on pre-set evaluation criteria (creativity, feasibility, social impact, etc.).

[2407] Output: Scoring data as the evaluation result.

[2408] Step 3:

[2409] The server returns the evaluation results to the user.

[2410] Input: Scoring data of evaluation results.

[2411] Data processing: The server compiles the evaluation results and generates feedback for the user.

[2412] Output: The evaluation results are sent to the user via email or notification.

[2413] Presentation file creation support

[2414] Step 1:

[2415] The user inputs the presentation content into the system from the terminal.

[2416] Input: The user inputs the presentation content in text format.

[2417] Output: The input presentation content is sent to the server.

[2418] Step 2:

[2419] The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[2420] Input: Presentation content data sent from the device.

[2421] Data Computing: Using natural language processing techniques, the presentation content is analyzed, appropriate slide templates are selected, and visual aids are generated.

[2422] Output: The generated visual aid.

[2423] Step 3:

[2424] The user indicates specific modifications or adjustments and the server adjusts the file accordingly.

[2425] Input: The user inputs correction instructions for a specific part.

[2426] Data calculation: The server modifies the visual materials based on the user's instructions.

[2427] Output: The corrected visual.

[2428] Step 4:

[2429] The server generates the final presentation file and provides it to the user.

[2430] Input: Visual data after corrections are complete.

[2431] Data processing: Generate the final presentation file.

[2432] Output: The generated presentation file is provided to the user.

[2433] Automatic generation of mockup sites

[2434] Step 1:

[2435] The user inputs the specifications of the mockup site into the system from a terminal.

[2436] Input: The user enters the specifications of the mockup site (page structure, functional requirements, etc.).

[2437] Output: The entered specification information is sent to the server.

[2438] Step 2:

[2439] The server analyzes the input information and selects a template.

[2440] Input: Specification information sent from the device.

[2441] Data calculation: The server analyzes the specification information and selects an appropriate template based on it.

[2442] Output: The selected template.

[2443] Step 3:

[2444] The server automatically generates a mockup site and provides it to the user.

[2445] Input: Selected template and specification information.

[2446] Data processing: Automatically generate a mockup site.

[2447] Output: The generated mockup site is provided to the user as a URL or download link.

[2448] Presentation script creation

[2449] Step 1:

[2450] The user inputs the content of the presentation and the desired presentation time into the system from the terminal.

[2451] Input: The user inputs the presentation content and desired presentation time.

[2452] Output: The entered data is sent to the server.

[2453] Step 2:

[2454] The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[2455] Input: Presentation content sent from the device and desired presentation time.

[2456] Data calculation: Analyze the presentation content and calculate the appropriate time allocation for each slide.

[2457] Output: Time allocation data.

[2458] Step 3:

[2459] The server automatically generates a presentation manuscript and provides it to the user.

[2460] Input: Time allocation data and analysis results.

[2461] Data processing: Automatically generate oral presentation manuscripts.

[2462] Output: The generated transcript is provided to the user.

[2463] Step 4:

[2464] The user makes a correction request and the server adjusts the manuscript accordingly.

[2465] Input: The user inputs correction instructions for the oral manuscript.

[2466] Data calculation: The server adjusts the manuscript based on the correction instructions.

[2467] Output: The revised transcript is provided to the user again.

[2468] (Application example 1)

[2469] 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."

[2470] To efficiently create high-quality content, modern content creators need to collect, evaluate, and ensure consistency in various ideas. However, many creators face challenges such as limited ability to refine their own concepts and few opportunities to receive objective evaluation and feedback. Furthermore, creating optimal presentation materials and mockup websites takes time and effort. As a result, creative work stagnates, risking a decline in content quality.

[2471] 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.

[2472] In this invention, the server includes means for receiving ideas input by a user, means for distributing the ideas to a plurality of AI agents with different characteristics and having each agent refine the idea, means for integrating the refined ideas and providing them to the user, means for evaluating and refining different content formats, and means for further evaluating and improving the idea integrated with improvements suggested by the user. This enables content creators to refine their ideas by receiving feedback from multiple perspectives and quickly create high-quality content.

[2473] "Means for receiving user-input ideas" refers to a function or module that receives, in digital form, ideas or concepts that users provide to the system.

[2474] "Multiple AI agents with different characteristics" are heterogeneous AI models, each with a specific perspective and role, that evaluate and improve ideas from different perspectives.

[2475] "Means for brushing up ideas" is a function that analyzes received ideas from multiple angles and adds improvements and new suggestions to further develop the ideas.

[2476] "Means for integrating refined ideas" is a function that synthesizes feedback and improvements from each AI agent and brings them together into a single integrated idea.

[2477] "Means to provide to users" refers to the ability to communicate the integrated ideas and proposed improvements to users in a clear and understandable format.

[2478] "A means to evaluate and refine different content formats" is a function that evaluates various forms of content, such as videos, articles, and podcasts, and suggests appropriate improvements for each.

[2479] "Suggestions for improving content quality based on feedback" is a function that provides specific advice for further improving content based on the evaluations and improvements received from users.

[2480] "Means for analyzing presentation content and automatically generating slides and materials" refers to a function that understands the content of a user's presentation and automatically creates appropriate slides and materials.

[2481] "Means for adjusting slides and materials based on user instructions" refers to a function for correcting and adjusting the content of already generated slides and materials in accordance with user requests and instructions.

[2482] The "means for automatically generating a content preview site" is a function that automatically creates a simple website or a preview page based on the user's ideas and content.

[2483] The present invention is a system that evaluates and improves ideas input by users from multiple angles and automatically generates high-quality content. Detailed embodiments of the system are described below.

[2484] System Configuration

[2485] The system operates based on communication between the server, terminals, and users, and uses smartphones (iOS or Android devices), Python, and OpenAI APIs as its main hardware and software.

[2486] Program processing

[2487] 1. A means of receiving user-entered ideas

[2488] Users input ideas into the system using their smartphones or PCs, and the ideas are sent to the server via the platform or application user interface.

[2489] 2. A way to share and refine ideas

[2490] The server distributes the received ideas to multiple AI agents with different characteristics. Each agent analyzes the idea from a specific perspective and generates improvements and new proposals. Specifically, the Dreamer AI is responsible for creative vision, the Hedonist AI for user experience, the Realist AI for feasibility, and the Critic AI for risk assessment.

[2491] 3. A way to integrate refined ideas

[2492] The feedback from each agent is integrated to generate a single improved idea. This integration process is carried out on the server and is reflected in the final result provided to the user.

[2493] 4. A way to evaluate and refine different content formats

[2494] The server provides feedback on various content formats, including videos, articles, and podcasts, and suggests appropriate improvements for each format, providing users with instructions to improve the quality of their content.

[2495] 5. A way to automatically generate a preview site for your content

[2496] The server automatically creates mockups and preview sites based on the generated ideas. These preview sites can be viewed in a browser, allowing users to see the final form of the content.

[2497] Usage example

[2498] As a specific example, a case will be described in which a user inputs an idea for an "introductory video for an environmentally friendly product." When the user inputs the idea into the system, the following process is carried out.

[2499] Visionary AI adds "vision of futuristic eco-technology"

[2500] The Hedonist AI recommends "visually appealing effects and music"

[2501] Realistic AI takes into account "specific product specifications and practical examples"

[2502] Critic AI points out "privacy and legal concerns"

[2503] This provides users with consolidated feedback, which allows them to create optimized content.

[2504] Prompt Sentence Examples

[2505] As a dreamer, please provide feedback on the following idea: A new cooking recipe sharing app

[2506] In this way, a system is provided that allows content creators to receive feedback from multiple perspectives and quickly create high-quality content.

[2507] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2508] Step 1:

[2509] The ideas entered by the user are sent from the device to the server. The user uses a smartphone or computer to enter their ideas and concepts into the system in text format. The entered ideas are sent to the server and stored in a database.

[2510] Input: Textual ideas from users

[2511] Output: Ideas stored in a database on the server

[2512] Step 2:

[2513] The server distributes ideas to multiple AI agents. The server retrieves ideas from a database and sends them to each agent (Dreamer, Enjoyer, Realist, Critic).

[2514] Input: Ideas retrieved from the database

[2515] Output: Ideas distributed to each agent

[2516] Step 3:

[2517] The Dreamer AI analyzes the idea and proposes a new creative vision. The server sends the idea to the Dreamer AI, and the Dreamer AI generates new visions and creative elements based on the idea.

[2518] Input: Ideas sent to the Dreamer AI

[2519] Output: Creative suggestions from the Dreamer AI

[2520] Step 4:

[2521] The Pleasure AI improves the idea by taking into account the user experience. The server sends the idea to the Pleasure AI, which then generates a proposal that incorporates entertainment elements and user experience into the idea.

[2522] Input: Idea sent to the Hedonist AI

[2523] Output: Suggestions from the Enjoyer AI to improve the user experience

[2524] Step 5:

[2525] The Realist AI considers the feasibility of the idea. The server sends the idea to the Realist AI, which then generates a concrete proposal that is feasible from a technical standpoint.

[2526] Input: Ideas sent to the Realist AI

[2527] Output: Feasible proposals from a realist AI

[2528] Step 6:

[2529] The critic AI evaluates the risk of ideas. The server sends ideas to the critic AI, which then points out risks and weaknesses and suggests ways to improve them.

[2530] Input: Ideas sent to the critic AI

[2531] Output: Risk assessment and improvement suggestions from the critic AI

[2532] Step 7:

[2533] The server integrates the feedback from each agent. The server receives feedback from each agent and synthesizes it into a single integrated idea, reconciling overlapping and contradictory points.

[2534] Input: Feedback from each agent

[2535] Output: Unified refinement proposal

[2536] Step 8:

[2537] The server provides the user with the integrated idea, which the user can then review and use. The user can then make further modifications as needed.

[2538] Input: Integrated refinement proposal

[2539] Output: Consolidated ideas provided to the user

[2540] Step 9:

[2541] The server evaluates and refines the content according to its format. It provides appropriate evaluation and feedback based on the format of the user-generated content (video, article, podcast, etc.) and generates suggestions to further improve the content.

[2542] Input: The format of the content provided by the user

[2543] Output: Evaluation and suggestions for improving the content

[2544] Step 10:

[2545] The server provides users with suggestions for improving the quality of content based on their feedback. The server reflects the feedback from each agent and proposes specific improvement actions to the user.

[2546] Input: Feedback from each agent

[2547] Output: Suggestions for improving the content provided to the user

[2548] 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.

[2549] This embodiment of the invention combines an emotion engine with a specialized system for supporting generative AI contests, incorporating an approach based on user emotion data, making idea refinement, presentation creation, and mockup site generation more effective and user-friendly.

[2550] System Overview

[2551] The system has the following main functions:

[2552] 1. Idea brush-up (virtual brainstorming)

[2553] 2. Final round of the contest

[2554] 3. Presentation file creation support

[2555] 4. Automatic generation of mockup sites

[2556] 5. Preparation of oral presentation script

[2557] 6. Emotion Recognition and Adaptation with Emotion Engine

[2558] 1. Idea brush-up (virtual brainstorming)

[2559] 1. The user inputs an idea into the system from a terminal.

[2560] 2. The server receives the ideas and sends them to multiple AI agents with different characteristics (dreamers, hedonists, realists, and critics).

[2561] 3. Visionary AI adds new ideas and big visions to ideas.

[2562] 4. The enjoyment AI takes into account user experience and entertainment elements to improve the idea.

[2563] 5. Realistic AI will consider the feasibility of the idea and bring it to technical fruition.

[2564] 6. Critic AI points out risks and weaknesses in ideas and suggests areas for improvement.

[2565] 7. The server integrates the output of each AI, generates refined ideas, and provides them to the user.

[2566] 8. The emotion engine analyzes the user's emotional data and makes adjustments based on the AI ​​agent's feedback.

[2567] Example: When a user suggests a "new social networking app," the Dreamer AI suggests "integration with VR," the Enjoyer AI suggests "gamification elements," the Realist AI adds "instant photo sharing functionality," and the Critic AI points out "privacy concerns." If the user expresses positive emotions toward the suggestion, the emotion engine takes this into account to further strengthen the idea.

[2568] 2. Final round of the contest

[2569] 1. The user submits an idea to the system from their device.

[2570] 2. The server evaluates the ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[2571] 3. The server returns the evaluation results to the user.

[2572] Example: When a user submits an "environmentally friendly product," the server evaluates it based on creativity, feasibility, and social impact, and provides the evaluation results as feedback to the user.

[2573] 3. Presentation file creation support

[2574] 1. The user inputs the presentation content into the system from their device.

[2575] 2. The server analyzes the presentation content, automatically selects a slide template, and generates the materials.

[2576] 3. The user specifies a range or gives verbal instructions, and the server adjusts the file accordingly.

[2577] 4. The emotion engine analyzes the user's emotion data and adjusts the design and content of the material based on the user's emotions.

[2578] 5. The server generates the final presentation file and serves it to the user.

[2579] Example: A user inputs "business plan" and the server automatically generates slides. If the user says "add a graph to this part," the server adds the graph. Also, if the user is excited, the emotion engine detects this and adds more visual effects to the presentation.

[2580] 4. Automatic generation of mockup sites

[2581] 1. The user inputs the specifications of the mockup site into the system from a terminal.

[2582] 2. The server analyzes the input information and selects a template for the mockup site.

[2583] 3. The server automatically generates a mockup site.

[2584] 4. The emotion engine analyzes user emotional data and adjusts the site design and element placement.

[2585] 5. The server serves the generated mockup site to the user.

[2586] Example: When a user instructs the server to "create a mockup site for a social networking app," the server generates a mockup site based on that instruction, and the emotion engine observes the user's reaction, adjusts the color scheme and layout, and delivers the final site to the user.

[2587] 5. Preparation of oral presentation script

[2588] 1. The user enters the content of the presentation and the desired presentation time into the system from their terminal.

[2589] 2. The server analyzes the presentation content and calculates the appropriate time allocation for each slide and section.

[2590] 3. The server automatically generates the oral presentation script.

[2591] 4. The emotion engine analyzes the user's emotional data and adjusts the content and tone of the manuscript.

[2592] 5. The server provides the generated oral transcript to the user.

[2593] 6. The server adjusts the manuscript based on user feedback.

[2594] Example: When a user inputs a request for a "5-minute presentation," the server creates and provides an oral script that fits within 5 minutes. If the user instructs the server to "explain this part in more detail," the server adds content that details the relevant part. Also, if the user is nervous, the emotion engine detects this and generates a script with a more relaxed tone.

[2595] This system enables users to improve the quality of their ideas, reduce the burden of creating presentation materials, and make more competitive proposals. By combining it with an emotion engine, it is expected to provide output optimized for the user's emotional state, improving the user experience.

[2596] The processing flow will be explained below.

[2597] Idea brush-up (including emotion engine)

[2598] Step 1:

[2599] The user inputs an idea from a terminal and sends it to the server.

[2600] Step 2:

[2601] A server receives ideas from users.

[2602] Step 3:

[2603] The server distributes ideas to four different AI agents: dreamers, hedonists, realists, and critics.

[2604] Step 4:

[2605] The Visionary AI adds new ideas and big visions to ideas, for example, proposing innovative technologies and generating future-oriented scenarios.

[2606] Step 5:

[2607] The Pleasure AI adds elements to ideas that enrich the user experience, such as suggesting easy-to-use interfaces and entertainment elements.

[2608] Step 6:

[2609] Realistic AI considers the feasibility of ideas and gives them technical realization, for example proposing a technology stack and designing a prototype.

[2610] Step 7:

[2611] The AI ​​critics point out risks and weaknesses in ideas and suggest areas for improvement, such as legal risks and market concerns.

[2612] Step 8:

[2613] The emotion engine analyzes the user's emotional data, for example, whether the user is excited or skeptical about an idea.

[2614] Step 9:

[2615] The server integrates feedback from each AI agent and generates refined ideas.

[2616] Step 10:

[2617] The emotion engine adjusts the final ideas based on the user's emotional data, for example adding more challenging ideas if the user is excited.

[2618] Step 11:

[2619] The server is integrated and sends the coordinated ideas back to the user.

[2620] The first round of the contest

[2621] Step 1:

[2622] The user inputs an idea from a terminal and sends it to the server.

[2623] Step 2:

[2624] A server receives the submitted ideas.

[2625] Step 3:

[2626] The server evaluates ideas based on the contest's evaluation criteria (creativity, feasibility, social impact, etc.).

[2627] Step 4:

[2628] The server assigns a score to each evaluation item.

[2629] Step 5:

[2630] The server calculates the overall score.

[2631] Step 6:

[2632] The server returns the evaluation results and feedback to the user.

[2633] Presentation file creation support

[2634] Step 1:

[2635] The user inputs the presentation content from the terminal and sends it to the server.

[2636] Step 2:

[2637] The server receives and analyzes the presentation content. ...

Claims

1. means for receiving user-entered ideas; A method for distributing ideas to multiple AI agents with different characteristics and allowing each agent to refine their ideas. A means to integrate the refined ideas and provide them to users, A system including:

2. a means for evaluating user-submitted ideas; means for returning the evaluation results to the user; The system of claim 1 , comprising:

3. A means to analyze presentation content and automatically generate slides and materials, means for adjusting slides and materials based on user instructions; a means for generating and providing a final presentation file to a user; The system of claim 1 , comprising:

4. A means for automatically generating a mockup site based on the specifications of the mockup site specified by the user; means for providing the generated mockup site to a user; The system of claim 1 , comprising:

5. A means for automatically generating an oral transcript based on the content and desired time of the presentation; means for providing the generated transcript to the user and adjusting it in response to feedback; The system of claim 1 , comprising:

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