System

Abstract

To provide a system.SOLUTION: A system includes: means for receiving input information from a user; means for recognizing a feeling state of the user using a feeling engine; means for generating a prompt corresponding to the input information of the user and the feeling state of the user using a generative AI; means for generating the gist in a markup language form on the basis of the generated prompt using the generative AI; and means for outputting the gist to presentation software.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] Traditionally, creating materials has required a lot of time and effort, especially when it comes to creating prompts, creating Markdown slides, creating slide outlines, and outputting and writing the content in PowerPoint. Furthermore, these tasks require specialized knowledge, making them difficult for non-experts. [Means for solving the problem]

[0005] This invention provides a system for efficiently creating documents by using generative AI to create optimal prompts, creating markdown for VSCOrd with the generative AI, creating slide outlines with VSCOrd, and outputting the content in PowerPoint. This significantly reduces the effort required for document creation, making it easy for even non-experts to create documents. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0014] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0027] "Example 1"

[0028] This embodiment of the present invention has a means for generating optimal prompts using generative AI. Specifically, when a user inputs the information they need or the content they want to research, the generative AI automatically generates optimal prompts based on that information. For example, if a user inputs that they want to create a document about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[0029] "Example 2"

[0030] Furthermore, this embodiment of the present invention includes a means for generating markdown for VSCord using a generative AI. Specifically, the generative AI automatically generates markdown for VSCord based on a prompt. For example, based on the above prompt, the generative AI generates markdown including headings such as "Major Research on the Latest Trends in AI" and "Major Challenges."

[0031] "Example 3"

[0032] Furthermore, this embodiment of the present invention provides a means for creating a slide outline using VSCord. Specifically, the above markdown is pasted into VSCord, and a slide outline is created using VSCord's functions. For example, by using VSCord's "Create Slide" function, a slide outline is created in which the markdown heading is used as the slide title and the text below it is used as the slide content.

[0033] "Example 4"

[0034] Finally, this embodiment of the present invention includes a means for outputting the slides in PowerPoint and writing the necessary content. Specifically, the slide outline is output to PowerPoint and the necessary content is written therein. For example, PowerPoint slides corresponding to each slide in the slide outline are created and the content is written therein. This allows for efficient creation of materials.

[0035] The processing flow of each embodiment will be described below.

[0036] "Example 1"

[0037] Step 1: The user enters the information they need or the question they want to find into the system.

[0038] Step 2: Generative AI automatically generates optimal prompts based on this information.

[0039] Step 3: The generated prompt is presented to the user.

[0040] "Example 2"

[0041] Step 1: Generative AI automatically generates markdown for VSCOrd based on prompts.

[0042] Step 2: The generated markdown is presented to the user.

[0043] "Example 3"

[0044] Step 1: User pastes the generated markdown into VSCOrd.

[0045] Step 2: Create the outline of the slides using VSCOrd's functions.

[0046] Step 3: The created slide outline is presented to the user.

[0047] "Example 4"

[0048] Step 1: The user exports the slide outline to PowerPoint.

[0049] Step 2: Write down what users need on a PowerPoint slide.

[0050] Step 3: The completed document is presented to the user.

[0051] Example 1

[0052] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0053] Conventional information search systems have made it difficult for users to efficiently obtain the specific information they need. Furthermore, creating appropriate prompts for the content users want to search for requires a high level of specialized knowledge, making it difficult for average users to do so. This reduces the efficiency of information gathering and increases the time and effort required.

[0054] 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.

[0055] In this invention, the server includes a means for a user to use a terminal to input the content they want to search or the information they need, a means for the server to receive the user's input and analyze it using natural language processing technology, a means for the server to call a generative AI model based on the analysis results and pass the user's input as a prompt, a means for the generative AI model to generate an optimal prompt based on the user's input, and a means for the server to return the generated prompt to the user's terminal. This enables users to efficiently obtain the information they need even without specialized knowledge.

[0056] "User" means an individual or organization that uses the system to input information and obtain required information.

[0057] A "terminal" is an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter information.

[0058] A "server" is a computer system whose role is to receive input from a user, analyze it, invoke a generative AI model to generate prompts, and return the results.

[0059] "Natural language processing technology" is a technology for analyzing text data entered by users and understanding its meaning, and specifically includes tokenization, keyword extraction, grammar analysis, etc.

[0060] A "generative AI model" is an artificial intelligence model that generates optimal prompts based on user input, and refers to an advanced language model such as GPT-4 (registered trademark).

[0061] "Prompts" are questions or instructions that a generative AI model generates based on user input, helping users efficiently obtain the information they need.

[0062] "Analysis results" are the data obtained after the server analyzes the user's input using natural language processing technology, and are an intermediate product before being passed to the generative AI model.

[0063] "Return" is the process by which the server sends the prompt generated by the generative AI model back to the user's device.

[0064] This invention is a system for efficiently obtaining information required by a user, and generates optimal prompts using a generative AI model. Specific embodiments of this system are described below.

[0065] First, the user uses a device (such as a PC or smartphone) to input the content they want to research or the information they need. For example, the user might type, "I want to create a document about the latest trends in AI." This input is entered as text into the device's input field and sent to the server by clicking the send button.

[0066] Next, the server receives the user's input. The server analyzes the user's input text using natural language processing technologies such as the Python (registered trademark) NLTK library or spaCy. Specifically, the server tokenizes the input text and extracts important keywords. For example, keywords such as "AI," "latest trends," and "document creation" are extracted.

[0067] The server then calls a generative AI model (for example, GPT-4) based on the analysis results. The server passes the user's input as a prompt to the generative AI model. The generative AI model generates the optimal prompt based on the user's input. For example, it generates prompts such as "What are the major research topics regarding the latest trends in AI?" or "What are the major challenges in the latest trends in AI?"

[0068] Finally, the server returns the generated prompt to the user's device. The user can check the returned prompt on the device screen and make corrections or additions as necessary. This allows users to efficiently obtain the information they need, even if they do not have specialized knowledge.

[0069] As a concrete example, if a user inputs, "I want to create a document about the latest trends in AI," the generative AI model will generate the following prompt:

[0070] "What are the major research findings on the latest trends in AI?"

[0071] "What are the major challenges in the latest trends in AI?"

[0072] This system allows users to efficiently collect information and create the necessary materials.

[0073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0074] Step 1:

[0075] The user uses the device to enter the information they want to find out and the information they need.

[0076] Input: The user enters "I would like to create a document about the latest trends in AI" into the input field on their device and clicks the send button.

[0077] Output: User input is sent to the server.

[0078] Specific behavior: The user enters text using the device keyboard and clicks the send button, which sends the input to the server.

[0079] Step 2:

[0080] The server receives the user's input and analyzes it using natural language processing techniques.

[0081] Input: User input (e.g., "I want to create a document about the latest developments in AI").

[0082] Output: Analyzed keywords (e.g., "AI", "latest trends", "document creation").

[0083] How it works: The server uses Python's NLTK library and spaCy to tokenize the input text and extract important keywords.

[0084] Step 3:

[0085] The server calls the generative AI model based on the analysis results and passes the user's input as a prompt.

[0086] Input: Analyzed keywords (e.g., "AI," "latest trends," "document creation").

[0087] Output: The prompt passed to the generative AI model (e.g., "I would like to create a paper about the latest developments in AI").

[0088] Specific operation: Based on the analysis results, the server calls a generative AI model (e.g., GPT-4) and passes the user's input as a prompt.

[0089] Step 4:

[0090] A generative AI model generates optimal prompts based on user input.

[0091] Input: The prompt passed to the generative AI model (e.g., "I want to create a paper about the latest developments in AI").

[0092] Output: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[0093] What it does: A generative AI model analyzes user input and generates the most appropriate prompt.

[0094] Step 5:

[0095] The server generates a prompt and returns it to the user's terminal.

[0096] Input: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[0097] Output: The prompt returned to the user's terminal.

[0098] What happens: The server sends the generated prompt to the user's device, allowing the user to view the prompt on their device's screen.

[0099] (Application example 1)

[0100] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0101] Conventional prompt creation systems using generative AI can generate optimal prompts based on the information a user needs or the content they want to research, but they lack the ability to automatically generate and provide relevant content to users based on the generated prompts. This means that users must manually create content based on the generated prompts, which is inefficient.

[0102] 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.

[0103] In this invention, the server includes means for creating an optimal prompt using generative AI, means for creating Markdown using generative AI, means for creating a slide outline, means for outputting and writing content using presentation software, means for generating an optimal prompt based on a topic entered by a user, means for automatically generating related content based on the generated prompt, and means for displaying the generated content to the user. This makes it possible to generate an optimal prompt based on a topic entered by a user, and automatically generate related content based on the prompt and provide it to the user.

[0104] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on information entered by the user.

[0105] A "prompt" is a question or instruction generated by generative AI in response to a user's request, and is the input data used to generate related information and content.

[0106] Markdown is a lightweight markup language for easily formatting text, and is one of the formats for content generated by generative AI.

[0107] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is automatically created by generative AI.

[0108] "Presentation software" is software for visually displaying information in slide format, and is used to output the outline of slides created by generative AI.

[0109] A "topic" is a subject or theme that a user is interested in and requests generative AI to generate information about.

[0110] "Content" refers to information and materials that generative AI automatically generates based on prompts, including in the form of articles, blog posts, reports, presentations, etc.

[0111] A "user" is an individual or organization that requests the generation of information or content using a generative AI system.

[0112] The system for implementing this invention uses generative AI to create optimal prompts, automatically generates related content based on those prompts, and provides it to users. Specific embodiments of this system are described below.

[0113] Hardware and software used

[0114] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0115] Software: Python, OpenAI® API, presentation software (e.g., Microsoft® PowerPoint®)

[0116] System configuration

[0117] 1. How to use generative AI to create optimal prompts:

[0118] The server generates the most appropriate prompts based on the topic entered by the user. For example, if a user wants to know about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[0119] 2. How to create Markdown using generative AI:

[0120] The server automatically generates relevant content in Markdown format based on the generated prompt, allowing users to easily get formatted text.

[0121] 3. How to create a slide outline:

[0122] The server automatically creates a slide outline that shows the basic structure and content of the presentation materials based on the generated content.

[0123] 4. How to output and write content using presentation software:

[0124] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the contents.

[0125] 5. How to generate the best prompt based on the topic entered by the user:

[0126] The server generates the most appropriate prompt based on the topic entered by the user. For example, for the topic "Latest trends in AI," the generative AI generates a prompt such as "What are the major research topics related to the latest trends in AI?"

[0127] 6. A way to auto-generate relevant content based on generated prompts:

[0128] The server automatically generates relevant content based on the generated prompts, for example, articles and reports on the latest trends in AI.

[0129] 7. How to display generated content to users:

[0130] The server displays the generated content to the user, who can view the generated content through his / her smartphone.

[0131] Specific examples

[0132] If a user wants to know about "The Latest in AI," the following prompt will be generated:

[0133] "What are the major research findings on the latest trends in AI?"

[0134] "What are the major challenges in the latest trends in AI?"

[0135] Based on these prompts, the generative AI generates relevant articles and reports and provides them to users, who can then view the content on their smartphones and use it as presentation materials if needed.

[0136] In this way, it is possible to generate optimal prompts based on the topic entered by the user, and automatically generate related content based on those prompts to provide to the user.

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

[0138] Step 1:

[0139] A user uses a smartphone to input topics of interest. The input topics are sent to the server. The input data is text data containing the information the user wants to know or research.

[0140] Step 2:

[0141] The server uses a generative AI to generate optimal prompts based on the received topic. Specifically, it uses a generative AI model (e.g., OpenAI's GPT-3 (registered trademark)) to generate questions and instructions related to the topic. The input data is the topic entered by the user, and the output data is the generated prompt.

[0142] Step 3:

[0143] The server automatically generates relevant content based on the generated prompt. It uses a generative AI model again to generate content that includes answers to the prompt and related information. The input data is the generated prompt, and the output data is the generated content (e.g., article, report).

[0144] Step 4:

[0145] The server formats the generated content in Markdown, which makes the content easy to read and organized. The input data is the generated content and the output data is the Markdown formatted content.

[0146] Step 5:

[0147] The server automatically creates slide outlines for presentation materials based on the generated content. Specifically, it extracts key points from the generated content and places them on each page of the slides. The input data is content in Markdown format, and the output data is the slide outlines.

[0148] Step 6:

[0149] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the content. The input data is the slide outline, and the output data is the completed presentation material.

[0150] Step 7:

[0151] The server displays the generated content and presentation materials to the user. The user can view the content through their smartphone and download or edit it as needed. The input data is the generated content and presentation materials, and the output data is the information displayed to the user.

[0152] Example 2

[0153] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0154] In conventional document creation systems, users manually input prompts and create documents based on them, which required a lot of time and effort. Furthermore, the quality of the generated documents was often inconsistent, and they sometimes failed to meet user expectations. Furthermore, transferring the generated documents to other software was also a problem.

[0155] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for creating a markup language file for a text editor using the generative AI, means for creating a document outline using the text editor, means for outputting and describing the content using presentation software, means for receiving a prompt sentence entered by a user and passing it to the generative AI model, and means for receiving a markup language file generated from the generative AI model and displaying it to the user. This enables users to efficiently automatically generate high-quality documents and easily transfer them to other software.

[0156] "Generative AI" is an artificial intelligence technology that automatically generates documents and code based on prompts entered by the user.

[0157] A "prompt" is an instruction that a user inputs to a generative AI, and is used to determine the content of the document or code that is generated.

[0158] A "text editor" is software that allows users to create and edit text documents.

[0159] A "markup language file" is a text file used to define the structure and format of a document, including, for example, Markdown and HTML.

[0160] A "document outline" is an outline that shows the basic structure and main points of a document.

[0161] "Presentation software" means software for creating, editing, and displaying slide presentations.

[0162] A "server" is a computer system that receives and processes requests from clients over a network.

[0163] A "user" is someone who uses the system to enter prompts and receive generated documents and code.

[0164] This invention relates to a system for automatically generating markup language files for text editors using a generative AI model. Specific embodiments of this system are described below.

[0165] Hardware and software used

[0166] Subject: Server

[0167] The server is a computer system for running a generative AI model. Specifically, OpenAI's GPT-3 is used as the generative AI model. The server receives prompts sent by the user and passes them to the generative AI model. It also receives markup language files generated by the generative AI model and returns them to the user.

[0168] Subject: Terminal

[0169] The terminal is a device that allows a user to input a prompt text and send it to a server. Terminals include computer devices such as PCs, tablets, and smartphones. The terminal sends the prompt text input by the user to the server, receives the markup language file returned from the server, and displays it.

[0170] Subject: User

[0171] A user is a person who uses a terminal to enter a prompt and receive the generated markup language file. The user enters a prompt based on a specific theme or content and consumes a document automatically generated by a generative AI model.

[0172] Data processing and calculation

[0173] Subject: Server

[0174] The server passes the prompt received from the user to the generative AI model, which generates a markup language file based on the prompt, then sends the file back to the server, which then sends it to the user.

[0175] Specific examples

[0176] Prompt Sentence Examples

[0177] The user enters the following prompt text:

[0178] Major research on the latest trends in AI

[0179] Example of a generated markup language file

[0180] The generative AI model generates a Markdown file that looks like this:

[0181] markdown

[0182] Major research on the latest trends in AI

[0183] Key Challenges

[0184] 1. Data quality and quantity

[0185] 2. Model Interpretability

[0186] 3. Efficient use of computing resources

[0187] 4. Ethical Issues

[0188] In this way, based on the prompts entered by the user, the server automatically generates markup language files using a generative AI model and provides them to the user via their terminal. This system allows users to efficiently generate high-quality documents that can be easily transferred to other software.

[0189] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0190] Step 1:

[0191] The user enters a prompt into an input field on the device, for example, "Major research on the latest trends in AI." The entered prompt is temporarily stored in the device's memory.

[0192] Step 2:

[0193] The user presses the send button to send the entered prompt text to the server. The terminal sends the prompt text to the server using an HTTP POST request. The input is the prompt text, and the output is an HTTP request to the server.

[0194] Step 3:

[0195] The server receives the prompt sent from the device. The server extracts the prompt from the body of the HTTP request and prepares to pass it to the generative AI model. The input is the HTTP request, and the output is the prompt.

[0196] Step 4:

[0197] The server passes the received prompt sentence to the generative AI model. Specifically, it calls the API of the generative AI model and passes the prompt sentence as a parameter. The input is the prompt sentence, and the output is an API request to the generative AI model.

[0198] Step 5:

[0199] The generative AI model generates a markup language file based on the prompt. The generative AI model uses an internal database and algorithms to generate the optimal document for the prompt. The input is the prompt, and the output is a markup language file.

[0200] Step 6:

[0201] The server receives the markup language file generated from the generative AI model. The server parses the data returned as an API response and extracts the markup language file. The input is the API response, and the output is the markup language file.

[0202] Step 7:

[0203] The server sends the generated markup language file to the terminal. The server returns the markup language file as an HTTP response. The input is the markup language file, and the output is the HTTP response to the terminal.

[0204] Step 8:

[0205] The terminal receives the markup language file sent from the server. The terminal extracts the markup language file from the body of the HTTP response and prepares it to be displayed to the user. The input is the HTTP response and the output is the markup language file.

[0206] Step 9:

[0207] The terminal displays the received markup language file to the user. Specifically, the markup language file is displayed in a text area or a dedicated viewer. The input is the markup language file, and the output is the document displayed to the user.

[0208] (Application example 2)

[0209] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0210] Conventional content generation systems require users to manually create prompts and edit the generated content, resulting in inefficiencies. Furthermore, the generated content lacked preview and saving / sharing functionality, resulting in poor user convenience. This made it difficult to quickly and efficiently generate content, especially technical documentation and blog posts.

[0211] 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.

[0212] In this invention, the server includes means for generating optimal prompts using generative AI, means for generating documents in markup language format using the generative AI, means for previewing the documents in markup language format in real time, means for editing the generated documents, and means for saving and sharing the generated documents, thereby enabling users to efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[0213] "Generative AI" is artificial intelligence that automatically generates content based on prompts entered by the user.

[0214] A "prompt" is input information that instructs generative AI on the content and direction of the content to be generated.

[0215] A "document in a markup language" is a language for writing documents with a specific structure and style, including Markdown and HTML.

[0216] The "means for displaying a preview in real time" is a function for displaying a generated document in a markup language format so that the document can be immediately visually confirmed.

[0217] "Means for editing" refers to the functionality that allows users to manually correct or modify the generated document.

[0218] "Means for saving and sharing" refers to the functionality for saving generated documents to local storage or cloud services and sharing them with other users.

[0219] An embodiment of this invention is a system that uses generative AI to create optimal prompts, creates documents in markup language format using generative AI, displays previews in real time, and allows editing, saving, and sharing.

[0220] System Program

[0221] This system is realized using the following hardware and software.

[0222] Hardware: Smartphones, head-mounted displays, servers

[0223] Software: Flask (a Python web framework), OpenAI API, markdown2 (a library that converts Markdown to HTML)

[0224] Processing flow

[0225] 1. Prompt input: The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt.

[0226] 2. Content generation using generative AI: The server generates a document in markup language format using the OpenAI API based on the input prompt.

[0227] 3. Real-time preview: The generated document is converted to HTML using the markdown2 library and previewed in real time on the user's device.

[0228] 4. Editing function: Users can manually edit the generated documents.

[0229] 5. Save and share function: Once edited, the document can be saved to local storage or cloud services and shared with other users.

[0230] Specific examples

[0231] For example, if a user types, "I want to generate a blog post about the latest developments in AI," the following prompt sentence might be used:

[0232] Prompt Sentence Examples

[0233] Produce blog posts on the latest developments in AI, including key research and challenges.

[0234] Based on this prompt, the generative AI generates a document in the following markup language format:

[0235] markdown

[0236] Major research on the latest trends in AI

[0237] Key Challenges

[0238] 1. Data bias

[0239] 2. Model Interpretability

[0240] 3. Privacy and Security

[0241] Latest research findings

[0242] New Models in Natural Language Processing

[0243] Advances in image recognition technology

[0244] Applications of reinforcement learning

[0245] In this way, users can efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[0246] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0247] Step 1:

[0248] The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt. The input prompt is sent to the server, where it is converted into a format that can be understood by the generative AI.

[0249] Step 2:

[0250] The server calls the OpenAI API based on the received prompt. The OpenAI API generates a document in markup language format based on the prompt. The generated document is returned to the server. Data processing involves parsing the prompt text and converting it into appropriate tokens.

[0251] Step 3:

[0252] The server converts the generated markup language document into HTML using the Markdown2 library. The converted HTML is sent to the user's device and displayed as a real-time preview. The markup language to HTML conversion process is performed as a data calculation.

[0253] Step 4:

[0254] The user can manually edit the previewed document. The edited content is sent back to the server. The input data is the user's edited content, and the output data is the updated document in markup language format.

[0255] Step 5:

[0256] The server saves the edited document to a local storage or a cloud service. The saved document can be shared with other users. Specific operations include saving the file and generating a shared link.

[0257] Example 3

[0258] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0259] The traditional process of creating presentation materials required a lot of manual work, which made it inefficient. Furthermore, transferring data between a text editor and presentation software was cumbersome, placing a heavy burden on users. Furthermore, maintaining consistency when editing slide content was difficult.

[0260] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0261] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and writing content using presentation software, means for importing the created slide outline into the presentation software, and means for editing the content of the slides using the presentation software, thereby enabling the creation of efficient and consistent presentation materials.

[0262] "Generative AI" is an AI technology that automatically generates optimal input sentences and code based on user input.

[0263] An "input sentence" is a text-format instruction sentence that the generative artificial intelligence creates in response to a user request.

[0264] A "text editor" is software for creating and editing text files.

[0265] A "markup language" is a language for adding structure and meaning to text, and is used to describe the outline of presentation materials.

[0266] A "slide outline" is an early stage slide that shows the basic structure and content of a presentation material.

[0267] "Presentation software" means software for creating, editing, and displaying slide-format materials.

[0268] "Import" is the operation of taking in data from other software or files.

[0269] "Editing" is the operation of changing or modifying existing data or content.

[0270] The present invention is a system for efficiently creating presentation materials using generative artificial intelligence. Specific embodiments of this system will be described below.

[0271] First, the user writes the content of the slides in Markdown format. Markdown is a markup language that can be easily edited with a text editor. For example, create a Markdown file like the one below.

[0272] markdown

[0273] Title slide

[0274] This slide is the title slide.

[0275] Slide 1

[0276] This slide is the first slide.

[0277] Slide 2

[0278] This is the second slide.

[0279] Next, the user pastes this Markdown file into a text editor. A general text editing software can be used as the text editor. Here, VSCode (registered trademark) is used as a specific example.

[0280] Users generate slide outlines using the VSCode "Markdown Slide Generator" extension, which parses Markdown files, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[0281] The generated slide outline is imported into presentation software. Any general presentation creation software can be used as the presentation software. Here, we will use "PowerPoint" as a specific example.

[0282] Users can load slide outlines generated in VSCode using PowerPoint's "import" feature, which converts Markdown files into PowerPoint slides.

[0283] Finally, the user edits the slides in PowerPoint to create the final presentation, reviewing each slide and adding text and images as needed.

[0284] As a concrete example, the following prompt sentence can be input to the generative artificial intelligence:

[0285] Paste the Markdown file into a text editor to create the outline of your slides, then import it into your presentation software and edit each slide to create your final presentation.

[0286] By using this prompt sentence, the user can create slide materials efficiently. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[0287] Step 1:

[0288] A user creates a Markdown file.

[0289] Input: The user writes the content of the slide in Markdown format.

[0290] Specific behavior: A user uses a text editor to create a Markdown file like the one below.

[0291] markdown

[0292] Title slide

[0293] This slide is the title slide.

[0294] Slide 1

[0295] This slide is the first slide.

[0296] Slide 2

[0297] This is the second slide.

[0298] Output: A Markdown file is generated.

[0299] Step 2:

[0300] The user pastes the Markdown file into a text editor.

[0301] Input: A user-created Markdown file.

[0302] Specific behavior: The user opens a text editor (e.g., VSCode) and pastes a Markdown file.

[0303] Output: A Markdown file displayed in a text editor.

[0304] Step 3:

[0305] A user generates a slide outline using the "Markdown Slide Generator" extension in a text editor.

[0306] Input: Markdown file pasted into a text editor.

[0307] What it does: A user opens the VSCode command palette and selects "Markdown Slide Generator," which parses a Markdown file, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[0308] Output: A slide skeleton is generated.

[0309] Step 4:

[0310] The user imports the generated slide outline into presentation software.

[0311] Input: The generated slide skeleton.

[0312] What happens: A user opens presentation software (e.g., PowerPoint) and uses the "Import" function to load a slide outline file.

[0313] Output: The slide outline will be displayed in your presentation software.

[0314] Step 5:

[0315] The user edits the slide content in the presentation software to complete the final presentation material.

[0316] Input: Slide outline imported into presentation software.

[0317] What it does: The user selects each slide, adds and edits text boxes and images, and adjusts the slide layout and design as needed.

[0318] Output: The final presentation material is completed.

[0319] (Application example 3)

[0320] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] There is a need to efficiently display work procedures and safety instructions in factories and help workers understand them. However, conventional methods require a lot of time and effort to create slides manually, making it difficult to communicate information efficiently.

[0322] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0323] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for a text editor using generative AI, means for creating a slide outline using a text editor, means for outputting and describing the content using presentation software, and means for displaying work procedures and safety instructions in slide format as an application installed on a factory robot. This makes it possible to efficiently display work procedures and safety instructions in a factory and help workers understand them.

[0324] "Generative AI" is a system that uses artificial intelligence technology to generate text and data for specific purposes.

[0325] A "prompt" is an instruction or question entered into a generative AI to obtain a specific output.

[0326] A "text editor" is software for creating and editing text data.

[0327] A "markup language" is a language for adding structure and meaning to text, and includes HTML and Markdown.

[0328] A "slide outline" is an outline that shows the basic components of a presentation.

[0329] "Presentation software" refers to software for visually displaying information in slide format, including PowerPoint.

[0330] A "factory robot" is a mechanical device used to automate work in a factory.

[0331] A "task procedure" is an instruction that shows the steps or method for performing a particular task.

[0332] "Safety instructions" are precautions and instructions for workers to carry out their work safely.

[0333] The system for implementing this invention includes a series of processes that use generative AI to create optimal prompts, generate markup language for a text editor, create slide outlines, and output them using presentation software.Furthermore, as an application installed on a factory robot, it has the function of displaying work procedures and safety instructions in slide format.

[0334] System program generation

[0335] The server uses generative AI to create optimal prompts based on the information the user enters. The generative AI then uses the prompts to generate markup language (Markdown format) for a text editor, which contains work procedures and safety instructions for the factory.

[0336] The generated Markdown text is pasted into a text editor (e.g., VSCode) to create a slide outline, where the heading is the slide title and the text below it is the slide content.

[0337] Next, presentation software (e.g., PowerPoint) is used to convert the outline into the final slide format and write the content, allowing for efficient creation of materials.

[0338] Hardware and software used

[0339] Hardware: Factory robot display

[0340] Software: VSCode, Python, markdown library, pptx library

[0341] Data processing and calculation

[0342] The server uses generative AI to create prompts, then generates Markdown text based on the prompts, which is then converted into slide outlines in a text editor and then into the final slide format in presentation software.

[0343] Specific examples

[0344] For example, you can write down work procedures in a factory in Markdown format, create a slide outline using VSCode, and output it to PowerPoint using the following prompt text, which can be input to a generative AI model.

[0345] Prompt Sentence Examples

[0346] "Please tell me how to write down the work procedures in the factory in Markdown format, create the outline of the slides using VSCode, and output them to PowerPoint."

[0347] This system makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[0348] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0349] Step 1:

[0350] The server receives information input by the user and creates an optimal prompt for the generative AI. This prompt is an instruction sentence for generating content including work procedures and safety instructions within the factory. The input is an outline of the work procedures and safety instructions provided by the user, and the output is a prompt sentence passed to the generative AI.

[0351] Step 2:

[0352] The server uses a generative AI to generate markup language (Markdown format) for a text editor based on the prompt created in step 1. The input is the prompt text, and the output is text in Markdown format. The generative AI analyzes the prompt text and outputs work procedures and safety instructions in Markdown format with appropriate headings and lists.

[0353] Step 3:

[0354] The server pastes the generated Markdown text into a text editor (e.g., VSCode) to create a slide outline. The input is Markdown text, and the output is a slide outline. The text editor automatically places the Markdown heading as the slide title and the text below it as the slide content.

[0355] Step 4:

[0356] The server outputs the slide outline to presentation software (e.g., PowerPoint) and converts it into the final slide format. The input is the slide outline, and the output is the completed slide presentation. The presentation software creates and fills in each slide based on the slide outline.

[0357] Step 5:

[0358] The factory robot receives the completed slide presentation sent from the server and displays it on its display. The input is the completed slide presentation, and the output is the slides displayed on the factory robot's display. The factory robot displays work procedures and safety instructions in slide format to help workers understand them.

[0359] This series of processes makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[0360] 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.

[0361] "Example 1"

[0362] In one embodiment of the present invention, the system incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and provides feedback to the generative AI. For example, if the user senses stress, the generative AI is adjusted to generate more concise and clear prompts. This allows for more appropriate support tailored to the user's emotional state.

[0363] "Example 2"

[0364] The emotion engine is also used by the generative AI when generating markdown for VSCOrd. For example, if the user senses joy or excitement, the generative AI will be adjusted to generate more creative code. This allows for more appropriate code generation according to the user's emotional state.

[0365] "Example 3"

[0366] Furthermore, the emotion engine is also used when creating slide outlines in VSCord and when outputting and writing content in PowerPoint. For example, if the user senses anxiety or tension, the generative AI will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content. This makes it possible to create more appropriate materials based on the user's emotional state.

[0367] The processing flow of each embodiment will be described below.

[0368] "Example 1"

[0369] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[0370] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[0371] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[0372] Step 4: The generative AI adjusts the prompt generation based on the feedback. For example, if it senses that the user is stressed, it will adjust to generate more concise and clear prompts.

[0373] "Example 2"

[0374] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[0375] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[0376] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[0377] Step 4: The generative AI adjusts the markdown generated for VSCOrd based on the feedback. For example, if it senses that the user is happy or excited, it will adjust to generate more creative code.

[0378] "Example 3"

[0379] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[0380] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[0381] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[0382] Step 4: Based on the feedback, the generative AI makes adjustments when creating the slide outline in VSCord and when outputting and writing content in PowerPoint. For example, if it senses that the user is feeling anxious or nervous, it will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content.

[0383] Example 1

[0384] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0385] Conventional prompt generation systems using generative AI generate prompts without considering the user's emotional state, which means that they do not provide appropriate support according to the user's stress or emotional state. Furthermore, if the generated prompts do not match the user's emotional state, the user's work efficiency may decrease.

[0386] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for analyzing the user's emotional state using an emotion analysis engine, means for feeding back the emotion analysis result to the generative AI and adjusting the prompt generation, and means for providing the generated prompt to the user's terminal. This makes it possible to generate an appropriate prompt according to the user's emotional state and improve the user's work efficiency.

[0387] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts based on user input.

[0388] An "emotion analysis engine" is a system that analyzes emotions from a user's tone of voice, facial expressions, choice of words, etc.

[0389] A "prompt" is a question or instruction that specifically indicates the information the user needs or the content they want to find out.

[0390] "Feedback" is the process of returning the results of emotion analysis to the generative AI and adjusting the prompt generation.

[0391] A "terminal" is a device such as a computer or smartphone that a user uses to input and output data.

[0392] This invention is a system that combines generative AI and an emotion analysis engine to generate optimal prompts according to the user's emotional state. Specific embodiments of this system are described below.

[0393] Hardware and software used

[0394] Hardware: Servers, devices (PCs, smartphones, etc.)

[0395] Software: Generative AI (e.g., GPT-4), sentiment analysis engine

[0396] System configuration

[0397] 1. User Input

[0398] The user uses the device to input the content they want to research or the information they need. For example, the user might type "I want to create a document about the latest trends in AI" into the input field on their PC or smartphone.

[0399] 2. Emotion analysis using an emotion analysis engine

[0400] The server uses an emotion analysis engine to analyze the user's input, tone of voice, facial expressions, and choice of words. For example, the server calls the emotion analysis engine's API and analyzes the user's input data and voice data. The analysis result is returned as "Stress level: High."

[0401] 3. Prompt generation using generative AI

[0402] The server instructs the generative AI to generate the optimal prompt based on the analysis results of the emotion analysis engine. For example, the server calls the generative AI's API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: High." The generative AI automatically generates an appropriate prompt, taking into account the user's input and emotional state.

[0403] 4. Providing prompts

[0404] The server sends the generated prompt to the user's device, where the user can check the generated prompt and use it to create documents or gather information. For example, the user can search for related information on the Internet based on the prompt they received.

[0405] Specific examples

[0406] Example user input: "I want to create a document about the latest trends in AI."

[0407] Example of a generative AI prompt:

[0408] "What are the major research findings on the latest trends in AI?"

[0409] "What are the major challenges in the latest trends in AI?"

[0410] "What are the latest statistics on the latest trends in AI?"

[0411] This system allows users to efficiently gather the necessary information and create materials, and provides more appropriate support by generating prompts according to the user's emotional state.

[0412] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0413] Step 1:

[0414] The user uses the terminal to input the information they want to find out and the information they need.

[0415] Specifically, the user enters "I would like to create a document about the latest trends in AI" into the input field on their PC or smartphone and clicks the send button.

[0416] The input data is the text "I would like to create a document about the latest trends in AI."

[0417] The terminal transmits this input data to the server.

[0418] Step 2:

[0419] The server receives the user's input data and passes it to the sentiment analysis engine.

[0420] Specifically, the server calls the API of the emotion analysis engine and analyzes the user's input data and voice data.

[0421] The input data is the user's text input and voice data.

[0422] The sentiment analysis engine analyzes this data to determine the user's emotional state (e.g., stress level).

[0423] The output data is the analysis result "Stress level: High".

[0424] Step 3:

[0425] Based on the analysis results of the emotion analysis engine, the server instructs the generative AI to generate the optimal prompt.

[0426] Specifically, the server calls the generative AI API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: high."

[0427] The input data is the user's text input and the emotion analysis results.

[0428] Based on this data, generative AI automatically generates appropriate prompts.

[0429] The output data is a prompt such as "What are the major research findings on the latest trends in AI?"

[0430] Step 4:

[0431] The server sends the generated prompt to the user's terminal.

[0432] As a specific operation, the server returns the generated prompt to the user's terminal as an HTTP response.

[0433] The input data is a prompt sentence from the generative AI.

[0434] The output data is a prompt that is displayed on the user's terminal.

[0435] The user checks the prompts generated on the terminal and uses them to create documents and gather information.

[0436] (Application example 1)

[0437] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0438] Conventional prompt creation systems using generative AI generate prompts without considering the user's emotional state, which means they are unable to provide optimal support according to the user's situation. Furthermore, it is difficult to recommend appropriate content when the user is feeling stressed or in a specific emotional state.

[0439] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing content using presentation software, and an emotion engine for analyzing the user's emotional state. This makes it possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[0440] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on user input.

[0441] A "prompt" is an instruction or question that a generative AI creates based on user input.

[0442] A "markup language" is a language used in document creation tools to describe the structure and format of a document.

[0443] A "document creation tool" is software for creating the outline of slides or documents.

[0444] "Presentation software" is software for displaying and editing created slides and documents.

[0445] The "emotion engine" is a system that analyzes emotions from the user's tone of voice, facial expressions, choice of words, etc.

[0446] A system for implementing this invention includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing the content using presentation software, and an emotion engine for analyzing the user's emotional state.

[0447] System configuration

[0448] 1. Generative AI:

[0449] Software: Generative AI models (e.g., GPT-4)

[0450] What it does: Auto-generates optimal prompts based on user input.

[0451] 2. Emotion Engine:

[0452] Hardware: Smartphone camera, microphone

[0453] Software: Sentiment analysis software

[0454] Function: Analyzes emotions from the user's tone of voice, facial expressions, and choice of words.

[0455] 3. Document creation tools:

[0456] Software: Word processing tools

[0457] Function: Creates a slide skeleton.

[0458] 4. Presentation software:

[0459] Software: Presentation software (e.g., Microsoft PowerPoint)

[0460] Functions: View and edit created slides and documents.

[0461] Program processing

[0462] The server uses the smartphone's camera and microphone to collect the user's facial expressions and tone of voice in real time to analyze the user's emotional state. The emotion analysis software analyzes this data to identify the user's emotional state. For example, if the user is feeling stressed, the emotion engine feeds that information back to the generative AI.

[0463] The generative AI uses emotional data obtained from the emotion engine to generate prompts that best fit the user's emotional state. For example, if a user is feeling stressed, it will generate a prompt such as "Tell me some relaxing movies."

[0464] The generated prompts are output as markup language that can be pasted into a word processing tool, which then creates slide outlines that can be viewed and edited in presentation software.

[0465] Specific examples

[0466] While a user is using their smartphone, an emotion engine detects stress from their facial expressions. A generative AI model generates prompts such as "Tell me some relaxing movies" and outputs code that can be pasted into a word processor. The word processor then uses this code to create a slide deck that can be viewed and edited in presentation software.

[0467] Example prompt sentence:

[0468] Generate prompts to recommend movies that will help users relax when they're feeling stressed.

[0469] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[0470] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0471] Step 1:

[0472] When a user uses a smartphone, the device uses a camera and microphone to collect the user's facial expressions and tone of voice in real time, and this data is fed into the emotion engine.

[0473] Step 2:

[0474] The device's emotion engine analyzes the collected facial expression and tone of voice data to identify the user's emotional state. For example, if the user is feeling stressed, that information will be output as the analysis result.

[0475] Step 3:

[0476] The server receives the user's emotional state data obtained from the emotion engine and inputs it into the generative AI. Based on this emotional state data, the generative AI generates a prompt that is optimal for the user's emotional state. For example, a prompt such as "Tell me about a relaxing movie" may be generated.

[0477] Step 4:

[0478] The prompts generated by the generative AI are output by the server as markup language to be pasted into a document creation tool. This markup language is then input into the document creation tool.

[0479] Step 5:

[0480] The document creation tool creates a slide outline based on the input markup language, and the created slide outline is output to the presentation software.

[0481] Step 6:

[0482] The presentation software provides the user with a viewable and editable version of the slide outlines output from the word processing tool, allowing the user to create a presentation based on the slides.

[0483] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[0484] Example 2

[0485] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0486] Conventional document generation systems using generative AI generate uniform content without considering the user's emotional state, making it difficult to fully meet the user's needs. Furthermore, if the generated document does not meet the user's expectations, the user must re-enter the prompt text, which is inefficient.

[0487] 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.

[0488] In this invention, the server includes means for creating an optimal input sentence using a generative artificial intelligence, means for creating a markup language for a text editor using the generative artificial intelligence, means for analyzing the emotional state of a user and providing feedback to the generative artificial intelligence, and means for the generative artificial intelligence to adjust the markup language by reflecting the feedback from the emotion analysis, thereby enabling more appropriate and creative document generation according to the emotional state of the user.

[0489] "Generative AI" is an AI technology that automatically generates text and code based on user input.

[0490] An "input sentence" is a text that a user inputs to give instructions to a generative artificial intelligence.

[0491] A "text editor" is software that allows a user to edit text or code.

[0492] A "markup language" is a language for adding structure and style to text, and includes, for example, Markdown.

[0493] "Presentation software" is software for visually displaying information in the form of slides.

[0494] An "emotional state" refers to the emotions a user is feeling, such as happiness, excitement, sadness, etc.

[0495] "Feedback" refers to information the system provides to the generative artificial intelligence based on the user's emotional state and other information.

[0496] A "document outline" is an outline that shows the basic structure and main points of a document.

[0497] The present invention is a system for generating a markup language for a text editor according to the emotional state of a user using generative artificial intelligence. Specific embodiments of this system will be described below.

[0498] Hardware and software used

[0499] server

[0500] The server hosts a generative AI model and an emotion engine. The generative AI model receives prompts from the user and generates markup language based on them. The emotion engine analyzes the user's emotional state and feeds that information back to the generative AI model.

[0501] Terminal

[0502] The terminal provides an interface for the user to input a prompt sentence, sends the input prompt sentence to the server, and displays the generated result returned from the server to the user.

[0503] Data processing and calculation

[0504] Entering a prompt statement

[0505] The user enters a prompt in the device's input field specifying the content and structure of the markup language they want to generate, for example, "Generate Markdown for key research and challenges related to the latest developments in AI."

[0506] Sending a prompt

[0507] The terminal sends the prompt text entered by the user to the server. Specifically, the terminal sends the prompt text to the server using an HTTP request.

[0508] Parsing and generating prompts

[0509] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The generative AI model automatically generates markup language for the text editor based on the prompt. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[0510] markdown

[0511] Major research on the latest trends in AI

[0512] Key Challenges

[0513] Emotional state analysis and feedback

[0514] The emotion engine monitors the user's input and actions to analyze their emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[0515] Adjusting the generated results

[0516] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[0517] Returning and displaying generated results

[0518] The server receives the markup language generated by the generative AI model and returns it to the terminal. The terminal displays the markup language received from the server to the user. The user can check the generated markup language and edit or save it as necessary.

[0519] Specific examples

[0520] Prompt Sentence Examples

[0521] The user enters the following prompt text:

[0522] Generate Markdown for key research and challenges related to the latest trends in AI.

[0523] Example of generated Markdown

[0524] The generative AI model generates the following Markdown:

[0525] markdown

[0526] Major research on the latest trends in AI

[0527] Key Challenges

[0528] In this way, the system generates markup language based on prompt statements in cooperation with the server, terminal, and user.

[0529] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0530] Step 1:

[0531] The user enters a prompt statement.

[0532] The user enters a prompt in the device's input field, specifying the content and structure of the markup language they want to generate. For example, they might enter, "Please generate Markdown for major research and issues related to the latest trends in AI." The entered prompt is then sent to the server in the next step.

[0533] Step 2:

[0534] The terminal sends the prompt to the server.

[0535] The terminal sends the prompt text entered by the user to the server using an HTTP request. The input data is the prompt text, and the output is a request sent to the server.

[0536] Step 3:

[0537] The server receives the prompt sentence and passes it to the generative artificial intelligence model.

[0538] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The input data is the prompt, and the output is the input data for the generative AI model. Specifically, the server converts the prompt into an appropriate format and inputs it into the generative AI model.

[0539] Step 4:

[0540] A generative artificial intelligence model generates markup language based on the prompt sentence.

[0541] The generative artificial intelligence model automatically generates markup language for a text editor based on a prompt received from the server. The input data is the prompt, and the output is the generated markup language. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[0542] markdown

[0543] Major research on the latest trends in AI

[0544] Key Challenges

[0545] Step 5:

[0546] The emotion engine analyzes the user's emotional state and provides feedback to the generative artificial intelligence model.

[0547] The emotion engine monitors the user's input and behavior to analyze the user's emotional state. The input data is the user's behavioral data, and the output is the analysis result of the user's emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[0548] Step 6:

[0549] A generative artificial intelligence model adjusts the markup language based on feedback from the emotion engine.

[0550] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. The input data is the analysis result of the emotional state, and the output is the adjusted markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[0551] Step 7:

[0552] The server returns the generated markup language to the terminal.

[0553] The server receives the markup language generated by the generative AI model and sends it back to the terminal using an HTTP response. The input data is the generated markup language, and the output is the response sent to the terminal.

[0554] Step 8:

[0555] The terminal displays the generated markup language to the user.

[0556] The terminal displays the markup language received from the server to the user. The input data is the generated markup language, and the output is the display to the user. The user checks the generated markup language and edits or saves it as necessary.

[0557] (Application example 2)

[0558] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0559] Conventional content generation systems using generative AI have the problem of being unable to fully meet user needs because they generate content in a uniform tone and style without considering the user's emotional state. Furthermore, there was a lack of means to properly display the generated content on devices such as smartphones, which led to issues with reduced usability.

[0560] 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.

[0561] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markdown for VSCode using generative AI, means for creating slide outlines in VSCode, means for outputting and describing content in PowerPoint, means for recognizing the user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated markdown content on a smartphone. This makes it possible to generate content in an appropriate tone and style according to the user's emotional state and display it appropriately on devices such as smartphones.

[0562] "Generative AI" is an artificial intelligence technology that automatically generates content such as text and code based on user input.

[0563] A "prompt" is input data or instructions given to generative AI, and serves as the basis for determining the content and format of the content to be generated.

[0564] "VSCode" is a source code editor provided by Microsoft and is a tool used for programming and editing Markdown.

[0565] "Markdown" is a lightweight markup language for easily formatting text, and is widely used, especially for creating technical documentation and blog posts.

[0566] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is used to efficiently organize the content of the slides.

[0567] "PowerPoint" is presentation software provided by Microsoft, and is a tool for visually presenting information in slide format.

[0568] An "emotion engine" is a technology that recognizes a user's emotional state and adjusts the tone and style of the generated content accordingly.

[0569] A "smartphone" is a multi-functional mobile device that can access the Internet and run applications in addition to the functions of a mobile phone.

[0570] "Tone" refers to the overall atmosphere or mood of a piece of text or content, and is adjusted according to the user's emotions and intentions.

[0571] "Style" refers to the way in which text or content is expressed or formatted, and is adjusted according to the user's feelings and intentions.

[0572] A system for implementing this invention includes means for generating optimal prompts using generative AI, creating Markdown for VSCode using the generative AI, creating slide outlines in VSCode, and outputting and writing the content in PowerPoint. It also includes means for recognizing a user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated Markdown content on a smartphone.

[0573] System Program

[0574] The program of this system operates as follows.

[0575] Hardware and Software

[0576] Hardware: Smartphones, servers

[0577] Software: Python, OpenAI API, Emotion Recognition API, VSCode, PowerPoint

[0578] Data processing and calculation

[0579] 1. User prompt input:

[0580] The user uses a smartphone to input a prompt, for example, "I want you to write an article about the latest developments in AI."

[0581] 2. Emotion Recognition with Emotion Engine:

[0582] The server uses an emotion recognition API to recognize the user's emotional state, for example, recognizing that the user is expressing the emotion "joy."

[0583] 3. Adjust the prompt:

[0584] The server will tailor the prompt based on the perceived emotion, for example, "Please write an article about the latest developments in AI. Please make the content more creative and engaging."

[0585] 4. Generative AI Markdown Generation:

[0586] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. For example, the following Markdown is generated:

[0587] Major research on the latest trends in AI

[0588] Key Challenges

[0589] Task 1

[0590] Task 2

[0591] 5. View the generated Markdown:

[0592] The generated Markdown content is displayed on the smartphone, where users can view it and make edits or corrections as needed.

[0593] Specific examples

[0594] If a user inputs a prompt such as "I want you to write an article about the latest developments in AI," and the emotion engine recognizes "joy," the generative AI will generate more creative and interesting articles. For example, the following prompt sentences may be used:

[0595] Please write articles about the latest trends in AI. Please make the content more creative and engaging.

[0596] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[0597] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0598] Step 1:

[0599] The user inputs a prompt using a smartphone. The input prompt is an instruction to the generative AI and serves as a basis for determining the content and format of the generated content. For example, the user might input, "I want you to write an article about the latest trends in AI." This prompt is then sent to the server.

[0600] Step 2:

[0601] The server uses an emotion recognition API to recognize the user's emotional state. It receives and analyzes the user's emotional data, such as voice, text, and facial expressions, as input. The analysis results in the user's emotional state (e.g., "joy") being output.

[0602] Step 3:

[0603] The server adjusts the prompt based on the recognized emotion. It receives as input the original prompt and the emotion recognition result. For example, if the user indicates the emotion "joy," it adds "Please make the content more creative and engaging." to the prompt. The adjusted prompt is output.

[0604] Step 4:

[0605] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. It receives the tailored prompts as input and sends them to a generative AI model. The generative AI model generates Markdown content based on the prompts and outputs it. For example, the following Markdown is generated:

[0606] Major research on the latest trends in AI

[0607] Key Challenges

[0608] Task 1

[0609] Task 2

[0610] Step 5:

[0611] The generated Markdown content is displayed on the smartphone. The generated Markdown content is received as input and output to the smartphone's display screen. The user can view it and edit or modify it as needed.

[0612] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[0613] Example 3

[0614] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0615] Conventional slide creation systems require users to manually write the content of the slides, which is inefficient and makes it difficult to create appropriate slides that reflect the user's emotional state. Even when generative AI is used, the system does not adjust the slides to take the user's emotional state into account, which can make the user feel anxious or tense.

[0616] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0617] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and describing the content using presentation software, and means for detecting the user's emotional state and adjusting the slide content using the generative artificial intelligence, thereby making it possible to efficiently create appropriate slides according to the user's emotional state.

[0618] "Generative AI" is an AI technology that generates optimal text and data based on user input.

[0619] An "input sentence" is text data that is created by a generative artificial intelligence based on a user's request.

[0620] A "text editor" is software that allows users to create and edit text data.

[0621] A "markup language" is a description language for adding structure and meaning to text data.

[0622] A "slide outline" is an outline that shows the basic components of each slide in a presentation.

[0623] "Presentation software" is software for visually displaying information in the form of slides.

[0624] "Emotional state" indicates the psychological state of the user, and includes emotions such as anxiety and tension.

[0625] "Adjustment" is the process by which the generative AI changes the slide content depending on the user's emotional state.

[0626] The present invention relates to a system for efficiently creating slides using generative artificial intelligence. A specific embodiment of this system will be described below.

[0627] First, the user writes the content of the slides in Markdown format. Markdown is a markup language for adding structure and meaning to text data, and is a concise and easy-to-read format. For example, create a Markdown file like this:

[0628] markdown

[0629] Title slide

[0630] This is the title slide.

[0631] Slide 1

[0632] This is the content of slide 1.

[0633] Slide 2

[0634] This is slide 2.

[0635] Next, the user copies this Markdown file and pastes it into a new file in a text editor on the terminal, using any common software.

[0636] The device's text editor parses the Markdown file pasted by the user and uses the "Create Slides" function to generate a slide outline, which is an outline showing the basic components of each slide in a presentation. Specifically, the Markdown heading is treated as the slide title, and the text below it is treated as the slide content.

[0637] The generated slide outline is imported into presentation software. The user starts the presentation software and selects an option to import the slide outline. Any general software can be used as the presentation software.

[0638] The user writes necessary content for each slide using the presentation software, for example, adjusting the design of the slide and adding images and graphs.

[0639] Furthermore, the emotion engine detects the user's emotional state. The emotional state indicates the user's psychological state and includes feelings such as anxiety and tension. The emotion engine detects the user's emotional state in real time from the user's facial expressions and voice. If the user is feeling anxious or nervous, the generative AI adjusts the content of the slides to make them simpler and easier to understand. For example, it may replace complex graphs with simpler diagrams.

[0640] For example, the following prompts can be input to a generative artificial intelligence:

[0641] Please explain the process of creating a slide outline in a text editor based on the Markdown file provided by the user, and then outputting it to presentation software to complete the final slides. If the user feels anxious or nervous, the generative AI will adjust to generate simpler and easier-to-understand slide outlines and content for the presentation software.

[0642] In this way, it becomes possible to efficiently create appropriate slides according to the emotional state of the user. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0643] Step 1:

[0644] A user creates a Markdown file.

[0645] The user writes the content of the slides in Markdown format. For example, create a Markdown file like this:

[0646] markdown

[0647] Title slide

[0648] This is the title slide.

[0649] Slide 1

[0650] This is the content of slide 1.

[0651] Slide 2

[0652] This is slide 2.

[0653] Input: Markdown file containing the slide content

[0654] Output: Markdown formatted text data

[0655] Step 2:

[0656] The user pastes the Markdown file into a text editor.

[0657] The user copies the Markdown file they created, launches a text editor on their device, and pastes it into a new file.

[0658] Input: Markdown format text data

[0659] Output: Markdown data pasted into a text editor

[0660] Step 3:

[0661] The device uses the "Create Slides" function of the text editor to generate the outline of the slides.

[0662] The device's text editor parses the Markdown file pasted by the user and generates the outline of the slides using the "Create Slides" function, which treats the Markdown heading as the slide title and the text below it as the slide content.

[0663] Input: Markdown data pasted into a text editor

[0664] Output: Generated slide skeleton

[0665] Step 4:

[0666] The user imports the generated slide outline into presentation software.

[0667] The user saves the created slide outline and starts the presentation software, then imports the slide outline using the "import" function of the presentation software.

[0668] Input: Generated slide skeleton

[0669] Output: Slide outline imported into presentation software

[0670] Step 5:

[0671] The user writes the content of the slide in the presentation software.

[0672] The user writes necessary content for each slide using the presentation software, for example, adjusting the design of the slide and adding images and graphs.

[0673] Input: Slide outline imported into presentation software

[0674] Output: Finished slides

[0675] Step 6:

[0676] An emotion engine detects the user's emotional state, and a generative AI model adjusts the slide content.

[0677] The emotion engine detects the user's emotional state in real time from their facial expressions and voice. If the user is feeling anxious or nervous, the generative AI model will adjust the content of the slides to make them simpler and easier to understand, for example by replacing complex graphs with simpler diagrams.

[0678] Input: User's emotional state, completed slides

[0679] Output: Slides adjusted according to the user's emotional state

[0680] (Application example 3)

[0681] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0682] In conventional document creation systems, users had to manually create the outline of slides and output them to presentation software, which was a cumbersome process, making it difficult to create documents efficiently. Furthermore, it was not possible to adjust the slide content appropriately based on the user's emotional state, which could lead to a decline in the quality of the documents if the user felt anxious or nervous. This created a need for a system that could quickly create high-quality documents for content distribution services such as online lectures and webinars.

[0683] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0684] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for a text editor using the generative AI, means for creating a slide outline using the text editor, means for outputting and describing the content using presentation software, and means for adjusting the slide content according to the user's emotional state using an emotion engine. This enables users to efficiently create high-quality materials, and makes it possible to create appropriate materials according to the user's emotional state in content distribution services such as online lectures and webinars.

[0685] "Generative AI" is an artificial intelligence technology that generates optimal prompts and code based on user input.

[0686] A "text editor" is software for editing text data.

[0687] A "markup language" is a language used to add structure and meaning to text, and includes HTML and Markdown.

[0688] A "slide outline" is a component that concisely summarizes the title and content of each slide in a presentation.

[0689] "Presentation software" refers to software for visually displaying information in slide format, and generally includes PowerPoint and similar software.

[0690] An "emotion engine" is a technology that analyzes a user's emotional state and responds appropriately based on the results.

[0691] "User's emotional state" refers to the psychological state such as anxiety or tension felt by the user.

[0692] A "content distribution service" is a service that distributes information such as lectures and webinars online.

[0693] A system for implementing this invention includes a generative AI, a text editor, presentation software, and an emotion engine. Specific embodiments are described below.

[0694] The server uses a generative AI to create the optimal prompt. The generative AI generates an appropriate prompt sentence based on the information entered by the user and the content they want to search. This prompt sentence is output as a markup language for a text editor (e.g., Markdown).

[0695] The server then pastes the generated markup into a text editor, which parses the Markdown-formatted text and creates slide outlines, which briefly summarize the title and content of each slide.

[0696] The server then outputs the slide outline to presentation software (e.g., PowerPoint), which creates each slide based on the slide outline and allows the user to fill in the necessary content.

[0697] Furthermore, the emotion engine analyzes the user's emotional state. If the user is feeling anxious or nervous, the emotion engine simplifies the slide content and adjusts it to output in a more understandable format. This makes it possible to create appropriate materials according to the user's emotional state.

[0698] As a concrete example, consider a scenario in which a user is creating materials for an online lecture. The user enters the following Markdown text:

[0699] markdown

[0700] Online lecture title

[0701] Slide 1

[0702] This is the content of slide 1.

[0703] Slide 2

[0704] This is slide 2.

[0705] Entering this text into the application will generate the following slide outline:

[0706] Slide 1: Title: "Slide 1", Content: "This is the content of Slide 1."

[0707] Slide 2: Title: "Slide 2", Content: "This is the content of Slide 2."

[0708] If the emotion engine detects the user's emotional state as "anxious," the slide content is simplified and output in a more understandable format.

[0709] Example prompts to input to a generative AI model:

[0710] A user has entered the following Markdown text to create materials for an online lecture. If the emotion engine detects the user's emotional state as "anxious," simplify the slide content and output it.

[0711] Online lecture title

[0712] Slide 1

[0713] This is the content of slide 1.

[0714] Slide 2

[0715] This is slide 2.

[0716] In this way, users can efficiently create high-quality materials, and content distribution services such as online lectures and webinars can create appropriate materials according to the user's emotional state.

[0717] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0718] Step 1:

[0719] A user inputs text in Markdown format to create materials for an online lecture. The user uses a text editor to input the following Markdown text:

[0720] Input: Markdown-formatted text

[0721] Output: Markdown text entered by the user

[0722] Step 2:

[0723] The server creates the optimal prompt using a generative AI, which analyzes the Markdown text entered by the user and generates an appropriate prompt.

[0724] Input: User-entered Markdown text

[0725] Output: Generated prompt statement

[0726] Step 3:

[0727] The server creates a markup language (Markdown) for the text editor based on the generated prompt. The generative AI analyzes the prompt and generates text in Markdown format.

[0728] Input: Generated prompt text

[0729] Output: Markdown formatted text

[0730] Step 4:

[0731] The server pastes the generated Markdown text into a text editor, which parses it and creates a slide outline.

[0732] Input: Markdown-formatted text

[0733] Output: Slide outline

[0734] Step 5:

[0735] The server outputs the slide outline to presentation software (e.g., PowerPoint), which creates slides based on the slide outline and allows the user to write the necessary content.

[0736] Input: Slide outline

[0737] Output: Slides for presentation software

[0738] Step 6:

[0739] The server analyzes the user's emotional state using an emotion engine, which analyzes data such as the user's facial expressions and voice to determine whether the user is feeling anxious or nervous.

[0740] Input: User's facial expressions and voice data

[0741] Output: User's emotional state

[0742] Step 7:

[0743] The server adjusts the slide content based on the user's emotional state detected by the emotion engine. For example, if the user is feeling anxious or nervous, the server simplifies the slide content and outputs it in a more understandable format.

[0744] Input: user's emotional state, slides for presentation software

[0745] Output: Adjusted slide content

[0746] In this way, users can efficiently create high-quality materials, and content distribution services such as online lectures and webinars can create appropriate materials according to the user's emotional state.

[0747] 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.

[0748] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0749] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0750] 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.

[0751] [Second embodiment]

[0752] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0753] 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.

[0754] 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).

[0755] 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.

[0756] 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.

[0757] 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).

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] In the smart glasses 214, 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.

[0763] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0764] "Example 1"

[0765] This embodiment of the present invention has a means for generating optimal prompts using generative AI. Specifically, when a user inputs the information they need or the content they want to research, the generative AI automatically generates optimal prompts based on that information. For example, if a user inputs that they want to create a document about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[0766] "Example 2"

[0767] Furthermore, this embodiment of the present invention includes a means for generating markdown for VSCord using a generative AI. Specifically, the generative AI automatically generates markdown for VSCord based on a prompt. For example, based on the above prompt, the generative AI generates markdown including headings such as "Major Research on the Latest Trends in AI" and "Major Challenges."

[0768] "Example 3"

[0769] Furthermore, this embodiment of the present invention provides a means for creating a slide outline using VSCord. Specifically, the above markdown is pasted into VSCord, and a slide outline is created using VSCord's functions. For example, by using VSCord's "Create Slide" function, a slide outline is created in which the markdown heading is used as the slide title and the text below it is used as the slide content.

[0770] "Example 4"

[0771] Finally, this embodiment of the present invention includes a means for outputting the slides in PowerPoint and writing the necessary content. Specifically, the slide outline is output to PowerPoint and the necessary content is written therein. For example, PowerPoint slides corresponding to each slide in the slide outline are created and the content is written therein. This allows for efficient creation of materials.

[0772] The processing flow of each embodiment will be described below.

[0773] "Example 1"

[0774] Step 1: The user enters the information they need or the question they want to find into the system.

[0775] Step 2: Generative AI automatically generates optimal prompts based on this information.

[0776] Step 3: The generated prompt is presented to the user.

[0777] "Example 2"

[0778] Step 1: Generative AI automatically generates markdown for VSCOrd based on prompts.

[0779] Step 2: The generated markdown is presented to the user.

[0780] "Example 3"

[0781] Step 1: User pastes the generated markdown into VSCOrd.

[0782] Step 2: Create the outline of the slides using VSCOrd's functions.

[0783] Step 3: The created slide outline is presented to the user.

[0784] "Example 4"

[0785] Step 1: The user exports the slide outline to PowerPoint.

[0786] Step 2: Write down what users need on a PowerPoint slide.

[0787] Step 3: The completed document is presented to the user.

[0788] Example 1

[0789] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0790] Conventional information search systems have made it difficult for users to efficiently obtain the specific information they need. Furthermore, creating appropriate prompts for the content users want to search for requires a high level of specialized knowledge, making it difficult for average users to do so. This reduces the efficiency of information gathering and increases the time and effort required.

[0791] 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.

[0792] In this invention, the server includes a means for a user to use a terminal to input the content they want to search or the information they need, a means for the server to receive the user's input and analyze it using natural language processing technology, a means for the server to call a generative AI model based on the analysis results and pass the user's input as a prompt, a means for the generative AI model to generate an optimal prompt based on the user's input, and a means for the server to return the generated prompt to the user's terminal. This enables users to efficiently obtain the information they need even without specialized knowledge.

[0793] "User" means an individual or organization that uses the system to input information and obtain required information.

[0794] A "terminal" is an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter information.

[0795] A "server" is a computer system whose role is to receive input from a user, analyze it, invoke a generative AI model to generate prompts, and return the results.

[0796] "Natural language processing technology" is a technology for analyzing text data entered by users and understanding its meaning, and specifically includes tokenization, keyword extraction, grammar analysis, etc.

[0797] A "generative AI model" is an artificial intelligence model that generates optimal prompts based on user input, and refers to advanced language models such as GPT-4.

[0798] "Prompts" are questions or instructions that a generative AI model generates based on user input, helping users efficiently obtain the information they need.

[0799] "Analysis results" are the data obtained after the server analyzes the user's input using natural language processing technology, and are an intermediate product before being passed to the generative AI model.

[0800] "Return" is the process by which the server sends the prompt generated by the generative AI model back to the user's device.

[0801] This invention is a system for efficiently obtaining information required by a user, and generates optimal prompts using a generative AI model. Specific embodiments of this system are described below.

[0802] First, the user uses a device (such as a PC or smartphone) to input the content they want to research or the information they need. For example, the user might type, "I want to create a document about the latest trends in AI." This input is entered as text into the device's input field and sent to the server by clicking the send button.

[0803] Next, the server receives the user's input. It analyzes the user's input text using natural language processing techniques such as Python's NLTK library or spaCy. Specifically, it tokenizes the input text and extracts important keywords. For example, keywords such as "AI," "latest trends," and "document creation" are extracted.

[0804] The server then calls a generative AI model (for example, GPT-4) based on the analysis results. The server passes the user's input as a prompt to the generative AI model. The generative AI model generates the optimal prompt based on the user's input. For example, it generates prompts such as "What are the major research topics regarding the latest trends in AI?" or "What are the major challenges in the latest trends in AI?"

[0805] Finally, the server returns the generated prompt to the user's device. The user can check the returned prompt on the device screen and make corrections or additions as necessary. This allows users to efficiently obtain the information they need, even if they do not have specialized knowledge.

[0806] As a concrete example, if a user inputs, "I want to create a document about the latest trends in AI," the generative AI model will generate the following prompt:

[0807] "What are the major research findings on the latest trends in AI?"

[0808] "What are the major challenges in the latest trends in AI?"

[0809] This system allows users to efficiently collect information and create the necessary materials.

[0810] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0811] Step 1:

[0812] The user uses the device to enter the information they want to find out and the information they need.

[0813] Input: The user enters "I would like to create a document about the latest trends in AI" into the input field on their device and clicks the send button.

[0814] Output: User input is sent to the server.

[0815] Specific behavior: The user enters text using the device keyboard and clicks the send button, which sends the input to the server.

[0816] Step 2:

[0817] The server receives the user's input and analyzes it using natural language processing techniques.

[0818] Input: User input (e.g., "I want to create a document about the latest developments in AI").

[0819] Output: Analyzed keywords (e.g., "AI", "latest trends", "document creation").

[0820] How it works: The server uses Python's NLTK library and spaCy to tokenize the input text and extract important keywords.

[0821] Step 3:

[0822] The server calls the generative AI model based on the analysis results and passes the user's input as a prompt.

[0823] Input: Analyzed keywords (e.g., "AI," "latest trends," "document creation").

[0824] Output: The prompt passed to the generative AI model (e.g., "I would like to create a paper about the latest developments in AI").

[0825] Specific operation: Based on the analysis results, the server calls a generative AI model (e.g., GPT-4) and passes the user's input as a prompt.

[0826] Step 4:

[0827] A generative AI model generates optimal prompts based on user input.

[0828] Input: The prompt passed to the generative AI model (e.g., "I want to create a paper about the latest developments in AI").

[0829] Output: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[0830] What it does: A generative AI model analyzes user input and generates the most appropriate prompt.

[0831] Step 5:

[0832] The server generates a prompt and returns it to the user's terminal.

[0833] Input: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[0834] Output: The prompt returned to the user's terminal.

[0835] What happens: The server sends the generated prompt to the user's device, allowing the user to view the prompt on their device's screen.

[0836] (Application example 1)

[0837] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0838] Conventional prompt creation systems using generative AI can generate optimal prompts based on the information a user needs or the content they want to research, but they lack the ability to automatically generate and provide relevant content to users based on the generated prompts. This means that users must manually create content based on the generated prompts, which is inefficient.

[0839] 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.

[0840] In this invention, the server includes means for creating an optimal prompt using generative AI, means for creating Markdown using generative AI, means for creating a slide outline, means for outputting and writing content using presentation software, means for generating an optimal prompt based on a topic entered by a user, means for automatically generating related content based on the generated prompt, and means for displaying the generated content to the user. This makes it possible to generate an optimal prompt based on a topic entered by a user, and automatically generate related content based on the prompt and provide it to the user.

[0841] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on information entered by the user.

[0842] A "prompt" is a question or instruction generated by generative AI in response to a user's request, and is the input data used to generate related information and content.

[0843] Markdown is a lightweight markup language for easily formatting text, and is one of the formats for content generated by generative AI.

[0844] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is automatically created by generative AI.

[0845] "Presentation software" is software for visually displaying information in slide format, and is used to output the outline of slides created by generative AI.

[0846] A "topic" is a subject or theme that a user is interested in and requests generative AI to generate information about.

[0847] "Content" refers to information and materials that generative AI automatically generates based on prompts, including in the form of articles, blog posts, reports, presentations, etc.

[0848] A "user" is an individual or organization that requests the generation of information or content using a generative AI system.

[0849] The system for implementing this invention uses generative AI to create optimal prompts, automatically generates related content based on those prompts, and provides it to users. Specific embodiments of this system are described below.

[0850] Hardware and software used

[0851] Hardware: Smartphone (iOS or Android)

[0852] Software: Python, OpenAI API, presentation software (e.g., Microsoft PowerPoint)

[0853] System configuration

[0854] 1. How to use generative AI to create optimal prompts:

[0855] The server generates the most appropriate prompts based on the topic entered by the user. For example, if a user wants to know about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[0856] 2. How to create Markdown using generative AI:

[0857] The server automatically generates relevant content in Markdown format based on the generated prompt, allowing users to easily get formatted text.

[0858] 3. How to create a slide outline:

[0859] The server automatically creates a slide outline that shows the basic structure and content of the presentation materials based on the generated content.

[0860] 4. How to output and write content using presentation software:

[0861] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the contents.

[0862] 5. How to generate the best prompt based on the topic entered by the user:

[0863] The server generates the most appropriate prompt based on the topic entered by the user. For example, for the topic "Latest trends in AI," the generative AI generates a prompt such as "What are the major research topics related to the latest trends in AI?"

[0864] 6. A way to auto-generate relevant content based on generated prompts:

[0865] The server automatically generates relevant content based on the generated prompts, for example, articles and reports on the latest trends in AI.

[0866] 7. How to display generated content to users:

[0867] The server displays the generated content to the user, who can view the generated content through his / her smartphone.

[0868] Specific examples

[0869] If a user wants to know about "The Latest in AI," the following prompt will be generated:

[0870] "What are the major research findings on the latest trends in AI?"

[0871] "What are the major challenges in the latest trends in AI?"

[0872] Based on these prompts, the generative AI generates relevant articles and reports and provides them to users, who can then view the content on their smartphones and use it as presentation materials if needed.

[0873] In this way, it is possible to generate optimal prompts based on the topic entered by the user, and automatically generate related content based on those prompts to provide to the user.

[0874] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0875] Step 1:

[0876] A user uses a smartphone to input topics of interest. The input topics are sent to the server. The input data is text data containing the information the user wants to know or research.

[0877] Step 2:

[0878] The server uses a generative AI to generate optimal prompts based on the received topic. Specifically, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate questions and instructions related to the topic. The input data is the topic entered by the user, and the output data is the generated prompt.

[0879] Step 3:

[0880] The server automatically generates relevant content based on the generated prompt. It uses a generative AI model again to generate content that includes answers to the prompt and related information. The input data is the generated prompt, and the output data is the generated content (e.g., article, report).

[0881] Step 4:

[0882] The server formats the generated content in Markdown, which makes the content easy to read and organized. The input data is the generated content and the output data is the Markdown formatted content.

[0883] Step 5:

[0884] The server automatically creates slide outlines for presentation materials based on the generated content. Specifically, it extracts key points from the generated content and places them on each page of the slides. The input data is content in Markdown format, and the output data is the slide outlines.

[0885] Step 6:

[0886] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the content. The input data is the slide outline, and the output data is the completed presentation material.

[0887] Step 7:

[0888] The server displays the generated content and presentation materials to the user. The user can view the content through their smartphone and download or edit it as needed. The input data is the generated content and presentation materials, and the output data is the information displayed to the user.

[0889] Example 2

[0890] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0891] In conventional document creation systems, users manually input prompts and create documents based on them, which required a lot of time and effort. Furthermore, the quality of the generated documents was often inconsistent, and they sometimes failed to meet user expectations. Furthermore, transferring the generated documents to other software was also a problem.

[0892] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for creating a markup language file for a text editor using the generative AI, means for creating a document outline using the text editor, means for outputting and describing the content using presentation software, means for receiving a prompt sentence entered by a user and passing it to the generative AI model, and means for receiving a markup language file generated from the generative AI model and displaying it to the user. This enables users to efficiently automatically generate high-quality documents and easily transfer them to other software.

[0893] "Generative AI" is an artificial intelligence technology that automatically generates documents and code based on prompts entered by the user.

[0894] A "prompt" is an instruction that a user inputs to a generative AI, and is used to determine the content of the document or code that is generated.

[0895] A "text editor" is software that allows users to create and edit text documents.

[0896] A "markup language file" is a text file used to define the structure and format of a document, including, for example, Markdown and HTML.

[0897] A "document outline" is an outline that shows the basic structure and main points of a document.

[0898] "Presentation software" means software for creating, editing, and displaying slide presentations.

[0899] A "server" is a computer system that receives and processes requests from clients over a network.

[0900] A "user" is someone who uses the system to enter prompts and receive generated documents and code.

[0901] This invention relates to a system for automatically generating markup language files for text editors using a generative AI model. Specific embodiments of this system are described below.

[0902] Hardware and software used

[0903] Subject: Server

[0904] The server is a computer system for running a generative AI model. Specifically, OpenAI's GPT-3 is used as the generative AI model. The server receives prompts sent by the user and passes them to the generative AI model. It also receives markup language files generated by the generative AI model and returns them to the user.

[0905] Subject: Terminal

[0906] The terminal is a device that allows a user to input a prompt text and send it to a server. Terminals include computer devices such as PCs, tablets, and smartphones. The terminal sends the prompt text input by the user to the server, receives the markup language file returned from the server, and displays it.

[0907] Subject: User

[0908] A user is a person who uses a terminal to enter a prompt and receive the generated markup language file. The user enters a prompt based on a specific theme or content and consumes a document automatically generated by a generative AI model.

[0909] Data processing and calculation

[0910] Subject: Server

[0911] The server passes the prompt received from the user to the generative AI model, which generates a markup language file based on the prompt, then sends the file back to the server, which then sends it to the user.

[0912] Specific examples

[0913] Prompt Sentence Examples

[0914] The user enters the following prompt text:

[0915] Major research on the latest trends in AI

[0916] Example of a generated markup language file

[0917] The generative AI model generates a Markdown file that looks like this:

[0918] markdown

[0919] Major research on the latest trends in AI

[0920] Key Challenges

[0921] 1. Data quality and quantity

[0922] 2. Model Interpretability

[0923] 3. Efficient use of computing resources

[0924] 4. Ethical Issues

[0925] In this way, based on the prompts entered by the user, the server automatically generates markup language files using a generative AI model and provides them to the user via their terminal. This system allows users to efficiently generate high-quality documents that can be easily transferred to other software.

[0926] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0927] Step 1:

[0928] The user enters a prompt into an input field on the device, for example, "Major research on the latest trends in AI." The entered prompt is temporarily stored in the device's memory.

[0929] Step 2:

[0930] The user presses the send button to send the entered prompt text to the server. The terminal sends the prompt text to the server using an HTTP POST request. The input is the prompt text, and the output is an HTTP request to the server.

[0931] Step 3:

[0932] The server receives the prompt sent from the device. The server extracts the prompt from the body of the HTTP request and prepares to pass it to the generative AI model. The input is the HTTP request, and the output is the prompt.

[0933] Step 4:

[0934] The server passes the received prompt sentence to the generative AI model. Specifically, it calls the API of the generative AI model and passes the prompt sentence as a parameter. The input is the prompt sentence, and the output is an API request to the generative AI model.

[0935] Step 5:

[0936] The generative AI model generates a markup language file based on the prompt. The generative AI model uses an internal database and algorithms to generate the optimal document for the prompt. The input is the prompt, and the output is a markup language file.

[0937] Step 6:

[0938] The server receives the markup language file generated from the generative AI model. The server parses the data returned as an API response and extracts the markup language file. The input is the API response, and the output is the markup language file.

[0939] Step 7:

[0940] The server sends the generated markup language file to the terminal. The server returns the markup language file as an HTTP response. The input is the markup language file, and the output is the HTTP response to the terminal.

[0941] Step 8:

[0942] The terminal receives the markup language file sent from the server. The terminal extracts the markup language file from the body of the HTTP response and prepares it to be displayed to the user. The input is the HTTP response and the output is the markup language file.

[0943] Step 9:

[0944] The terminal displays the received markup language file to the user. Specifically, the markup language file is displayed in a text area or a dedicated viewer. The input is the markup language file, and the output is the document displayed to the user.

[0945] (Application example 2)

[0946] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0947] Conventional content generation systems require users to manually create prompts and edit the generated content, resulting in inefficiencies. Furthermore, the generated content lacked preview and saving / sharing functionality, resulting in poor user convenience. This made it difficult to quickly and efficiently generate content, especially technical documentation and blog posts.

[0948] 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.

[0949] In this invention, the server includes means for generating optimal prompts using generative AI, means for generating documents in markup language format using the generative AI, means for previewing the documents in markup language format in real time, means for editing the generated documents, and means for saving and sharing the generated documents, thereby enabling users to efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[0950] "Generative AI" is artificial intelligence that automatically generates content based on prompts entered by the user.

[0951] A "prompt" is input information that instructs generative AI on the content and direction of the content to be generated.

[0952] A "document in a markup language" is a language for writing documents with a specific structure and style, including Markdown and HTML.

[0953] The "means for displaying a preview in real time" is a function for displaying a generated document in a markup language format so that the document can be immediately visually confirmed.

[0954] "Means for editing" refers to the functionality that allows users to manually correct or modify the generated document.

[0955] "Means for saving and sharing" refers to the functionality for saving generated documents to local storage or cloud services and sharing them with other users.

[0956] An embodiment of this invention is a system that uses generative AI to create optimal prompts, creates documents in markup language format using generative AI, displays previews in real time, and allows editing, saving, and sharing.

[0957] System Program

[0958] This system is realized using the following hardware and software.

[0959] Hardware: Smartphones, head-mounted displays, servers

[0960] Software: Flask (a Python web framework), OpenAI API, markdown2 (a library that converts Markdown to HTML)

[0961] Processing flow

[0962] 1. Prompt input: The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt.

[0963] 2. Content generation using generative AI: The server generates a document in markup language format using the OpenAI API based on the input prompt.

[0964] 3. Real-time preview: The generated document is converted to HTML using the markdown2 library and previewed in real time on the user's device.

[0965] 4. Editing function: Users can manually edit the generated documents.

[0966] 5. Save and share function: Once edited, the document can be saved to local storage or cloud services and shared with other users.

[0967] Specific examples

[0968] For example, if a user types, "I want to generate a blog post about the latest developments in AI," the following prompt sentence might be used:

[0969] Prompt Sentence Examples

[0970] Produce blog posts on the latest developments in AI, including key research and challenges.

[0971] Based on this prompt, the generative AI generates a document in the following markup language format:

[0972] markdown

[0973] Major research on the latest trends in AI

[0974] Key Challenges

[0975] 1. Data bias

[0976] 2. Model Interpretability

[0977] 3. Privacy and Security

[0978] Latest research findings

[0979] New Models in Natural Language Processing

[0980] Advances in image recognition technology

[0981] Applications of reinforcement learning

[0982] In this way, users can efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[0983] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0984] Step 1:

[0985] The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt. The input prompt is sent to the server, where it is converted into a format that can be understood by the generative AI.

[0986] Step 2:

[0987] The server calls the OpenAI API based on the received prompt. The OpenAI API generates a document in markup language format based on the prompt. The generated document is returned to the server. Data processing involves parsing the prompt text and converting it into appropriate tokens.

[0988] Step 3:

[0989] The server converts the generated markup language document into HTML using the Markdown2 library. The converted HTML is sent to the user's device and displayed as a real-time preview. The markup language to HTML conversion process is performed as a data calculation.

[0990] Step 4:

[0991] The user can manually edit the previewed document. The edited content is sent back to the server. The input data is the user's edited content, and the output data is the updated document in markup language format.

[0992] Step 5:

[0993] The server saves the edited document to a local storage or a cloud service. The saved document can be shared with other users. Specific operations include saving the file and generating a shared link.

[0994] Example 3

[0995] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0996] The traditional process of creating presentation materials required a lot of manual work, which made it inefficient. Furthermore, transferring data between a text editor and presentation software was cumbersome, placing a heavy burden on users. Furthermore, maintaining consistency when editing slide content was difficult.

[0997] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0998] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and writing content using presentation software, means for importing the created slide outline into the presentation software, and means for editing the content of the slides using the presentation software, thereby enabling the creation of efficient and consistent presentation materials.

[0999] "Generative AI" is an AI technology that automatically generates optimal input sentences and code based on user input.

[1000] An "input sentence" is a text-format instruction sentence that the generative artificial intelligence creates in response to a user request.

[1001] A "text editor" is software for creating and editing text files.

[1002] A "markup language" is a language for adding structure and meaning to text, and is used to describe the outline of presentation materials.

[1003] A "slide outline" is an early stage slide that shows the basic structure and content of a presentation material.

[1004] "Presentation software" means software for creating, editing, and displaying slide-format materials.

[1005] "Import" is the operation of taking in data from other software or files.

[1006] "Editing" is the operation of changing or modifying existing data or content.

[1007] The present invention is a system for efficiently creating presentation materials using generative artificial intelligence. Specific embodiments of this system will be described below.

[1008] First, the user writes the content of the slides in Markdown format. Markdown is a markup language that can be easily edited with a text editor. For example, create a Markdown file like the one below.

[1009] markdown

[1010] Title slide

[1011] This slide is the title slide.

[1012] Slide 1

[1013] This slide is the first slide.

[1014] Slide 2

[1015] This is the second slide.

[1016] Next, the user pastes this Markdown file into a text editor. Any common text editing software can be used as the text editor. Here, we will use VSCode as a specific example.

[1017] Users generate slide outlines using the VSCode "Markdown Slide Generator" extension, which parses Markdown files, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[1018] The generated slide outline is imported into presentation software. Any general presentation creation software can be used as the presentation software. Here, we will use "PowerPoint" as a specific example.

[1019] Users can load slide outlines generated in VSCode using PowerPoint's "import" feature, which converts Markdown files into PowerPoint slides.

[1020] Finally, the user edits the slides in PowerPoint to create the final presentation, reviewing each slide and adding text and images as needed.

[1021] As a concrete example, the following prompt sentence can be input to the generative artificial intelligence:

[1022] Paste the Markdown file into a text editor to create the outline of your slides, then import it into your presentation software and edit each slide to create your final presentation.

[1023] By using this prompt sentence, the user can create slide materials efficiently. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[1024] Step 1:

[1025] A user creates a Markdown file.

[1026] Input: The user writes the content of the slide in Markdown format.

[1027] Specific behavior: A user uses a text editor to create a Markdown file like the one below.

[1028] markdown

[1029] Title slide

[1030] This slide is the title slide.

[1031] Slide 1

[1032] This slide is the first slide.

[1033] Slide 2

[1034] This is the second slide.

[1035] Output: A Markdown file is generated.

[1036] Step 2:

[1037] The user pastes the Markdown file into a text editor.

[1038] Input: A user-created Markdown file.

[1039] Specific behavior: The user opens a text editor (e.g., VSCode) and pastes a Markdown file.

[1040] Output: A Markdown file displayed in a text editor.

[1041] Step 3:

[1042] A user generates a slide outline using the "Markdown Slide Generator" extension in a text editor.

[1043] Input: Markdown file pasted into a text editor.

[1044] What it does: A user opens the VSCode command palette and selects "Markdown Slide Generator," which parses a Markdown file, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[1045] Output: A slide skeleton is generated.

[1046] Step 4:

[1047] The user imports the generated slide outline into presentation software.

[1048] Input: The generated slide skeleton.

[1049] What happens: A user opens presentation software (e.g., PowerPoint) and uses the "Import" function to load a slide outline file.

[1050] Output: The slide outline will be displayed in your presentation software.

[1051] Step 5:

[1052] The user edits the slide content in the presentation software to complete the final presentation material.

[1053] Input: Slide outline imported into presentation software.

[1054] What it does: The user selects each slide, adds and edits text boxes and images, and adjusts the slide layout and design as needed.

[1055] Output: The final presentation material is completed.

[1056] (Application example 3)

[1057] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1058] There is a need to efficiently display work procedures and safety instructions in factories and help workers understand them. However, conventional methods require a lot of time and effort to create slides manually, making it difficult to communicate information efficiently.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1060] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for a text editor using generative AI, means for creating a slide outline using a text editor, means for outputting and describing the content using presentation software, and means for displaying work procedures and safety instructions in slide format as an application installed on a factory robot. This makes it possible to efficiently display work procedures and safety instructions in a factory and help workers understand them.

[1061] "Generative AI" is a system that uses artificial intelligence technology to generate text and data for specific purposes.

[1062] A "prompt" is an instruction or question entered into a generative AI to obtain a specific output.

[1063] A "text editor" is software for creating and editing text data.

[1064] A "markup language" is a language for adding structure and meaning to text, and includes HTML and Markdown.

[1065] A "slide outline" is an outline that shows the basic components of a presentation.

[1066] "Presentation software" refers to software for visually displaying information in slide format, including PowerPoint.

[1067] A "factory robot" is a mechanical device used to automate work in a factory.

[1068] A "task procedure" is an instruction that shows the steps or method for performing a particular task.

[1069] "Safety instructions" are precautions and instructions for workers to carry out their work safely.

[1070] The system for implementing this invention includes a series of processes that use generative AI to create optimal prompts, generate markup language for a text editor, create slide outlines, and output them using presentation software.Furthermore, as an application installed on a factory robot, it has the function of displaying work procedures and safety instructions in slide format.

[1071] System program generation

[1072] The server uses generative AI to create optimal prompts based on the information the user enters. The generative AI then uses the prompts to generate markup language (Markdown format) for a text editor, which contains work procedures and safety instructions for the factory.

[1073] The generated Markdown text is pasted into a text editor (e.g., VSCode) to create a slide outline, where the heading is the slide title and the text below it is the slide content.

[1074] Next, presentation software (e.g., PowerPoint) is used to convert the outline into the final slide format and write the content, allowing for efficient creation of materials.

[1075] Hardware and software used

[1076] Hardware: Factory robot display

[1077] Software: VSCode, Python, markdown library, pptx library

[1078] Data processing and calculation

[1079] The server uses generative AI to create prompts, then generates Markdown text based on the prompts, which is then converted into slide outlines in a text editor and then into the final slide format in presentation software.

[1080] Specific examples

[1081] For example, you can write down work procedures in a factory in Markdown format, create a slide outline using VSCode, and output it to PowerPoint using the following prompt text, which can be input to a generative AI model.

[1082] Prompt Sentence Examples

[1083] "Please tell me how to write down the work procedures in the factory in Markdown format, create the outline of the slides using VSCode, and output them to PowerPoint."

[1084] This system makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[1085] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1086] Step 1:

[1087] The server receives information input by the user and creates an optimal prompt for the generative AI. This prompt is an instruction sentence for generating content including work procedures and safety instructions within the factory. The input is an outline of the work procedures and safety instructions provided by the user, and the output is a prompt sentence passed to the generative AI.

[1088] Step 2:

[1089] The server uses a generative AI to generate markup language (Markdown format) for a text editor based on the prompt created in step 1. The input is the prompt text, and the output is text in Markdown format. The generative AI analyzes the prompt text and outputs work procedures and safety instructions in Markdown format with appropriate headings and lists.

[1090] Step 3:

[1091] The server pastes the generated Markdown text into a text editor (e.g., VSCode) to create a slide outline. The input is Markdown text, and the output is a slide outline. The text editor automatically places the Markdown heading as the slide title and the text below it as the slide content.

[1092] Step 4:

[1093] The server outputs the slide outline to presentation software (e.g., PowerPoint) and converts it into the final slide format. The input is the slide outline, and the output is the completed slide presentation. The presentation software creates and fills in each slide based on the slide outline.

[1094] Step 5:

[1095] The factory robot receives the completed slide presentation sent from the server and displays it on its display. The input is the completed slide presentation, and the output is the slides displayed on the factory robot's display. The factory robot displays work procedures and safety instructions in slide format to help workers understand them.

[1096] This series of processes makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[1097] 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.

[1098] "Example 1"

[1099] In one embodiment of the present invention, the system incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and provides feedback to the generative AI. For example, if the user senses stress, the generative AI is adjusted to generate more concise and clear prompts. This allows for more appropriate support tailored to the user's emotional state.

[1100] "Example 2"

[1101] The emotion engine is also used by the generative AI when generating markdown for VSCOrd. For example, if the user senses joy or excitement, the generative AI will be adjusted to generate more creative code. This allows for more appropriate code generation according to the user's emotional state.

[1102] "Example 3"

[1103] Furthermore, the emotion engine is also used when creating slide outlines in VSCord and when outputting and writing content in PowerPoint. For example, if the user senses anxiety or tension, the generative AI will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content. This makes it possible to create more appropriate materials based on the user's emotional state.

[1104] The processing flow of each embodiment will be described below.

[1105] "Example 1"

[1106] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1107] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1108] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1109] Step 4: The generative AI adjusts the prompt generation based on the feedback. For example, if it senses that the user is stressed, it will adjust to generate more concise and clear prompts.

[1110] "Example 2"

[1111] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1112] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1113] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1114] Step 4: The generative AI adjusts the markdown generated for VSCOrd based on the feedback. For example, if it senses that the user is happy or excited, it will adjust to generate more creative code.

[1115] "Example 3"

[1116] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1117] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1118] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1119] Step 4: Based on the feedback, the generative AI makes adjustments when creating the slide outline in VSCord and when outputting and writing content in PowerPoint. For example, if it senses that the user is feeling anxious or nervous, it will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content.

[1120] Example 1

[1121] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1122] Conventional prompt generation systems using generative AI generate prompts without considering the user's emotional state, which means that they do not provide appropriate support according to the user's stress or emotional state. Furthermore, if the generated prompts do not match the user's emotional state, the user's work efficiency may decrease.

[1123] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for analyzing the user's emotional state using an emotion analysis engine, means for feeding back the emotion analysis result to the generative AI and adjusting the prompt generation, and means for providing the generated prompt to the user's terminal. This makes it possible to generate an appropriate prompt according to the user's emotional state and improve the user's work efficiency.

[1124] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts based on user input.

[1125] An "emotion analysis engine" is a system that analyzes emotions from a user's tone of voice, facial expressions, choice of words, etc.

[1126] A "prompt" is a question or instruction that specifically indicates the information the user needs or the content they want to find out.

[1127] "Feedback" is the process of returning the results of emotion analysis to the generative AI and adjusting the prompt generation.

[1128] A "terminal" is a device such as a computer or smartphone that a user uses to input and output data.

[1129] This invention is a system that combines generative AI and an emotion analysis engine to generate optimal prompts according to the user's emotional state. Specific embodiments of this system are described below.

[1130] Hardware and software used

[1131] Hardware: Servers, devices (PCs, smartphones, etc.)

[1132] Software: Generative AI (e.g., GPT-4), sentiment analysis engine

[1133] System configuration

[1134] 1. User Input

[1135] The user uses the device to input the content they want to research or the information they need. For example, the user might type "I want to create a document about the latest trends in AI" into the input field on their PC or smartphone.

[1136] 2. Emotion analysis using an emotion analysis engine

[1137] The server uses an emotion analysis engine to analyze the user's input, tone of voice, facial expressions, and choice of words. For example, the server calls the emotion analysis engine's API and analyzes the user's input data and voice data. The analysis result is returned as "Stress level: High."

[1138] 3. Prompt generation using generative AI

[1139] The server instructs the generative AI to generate the optimal prompt based on the analysis results of the emotion analysis engine. For example, the server calls the generative AI's API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: High." The generative AI automatically generates an appropriate prompt, taking into account the user's input and emotional state.

[1140] 4. Providing prompts

[1141] The server sends the generated prompt to the user's device, where the user can check the generated prompt and use it to create documents or gather information. For example, the user can search for related information on the Internet based on the prompt they received.

[1142] Specific examples

[1143] Example user input: "I want to create a document about the latest trends in AI."

[1144] Example of a generative AI prompt:

[1145] "What are the major research findings on the latest trends in AI?"

[1146] "What are the major challenges in the latest trends in AI?"

[1147] "What are the latest statistics on the latest trends in AI?"

[1148] This system allows users to efficiently gather the necessary information and create materials, and provides more appropriate support by generating prompts according to the user's emotional state.

[1149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1150] Step 1:

[1151] The user uses the terminal to input the information they want to find out and the information they need.

[1152] Specifically, the user enters "I would like to create a document about the latest trends in AI" into the input field on their PC or smartphone and clicks the send button.

[1153] The input data is the text "I would like to create a document about the latest trends in AI."

[1154] The terminal transmits this input data to the server.

[1155] Step 2:

[1156] The server receives the user's input data and passes it to the sentiment analysis engine.

[1157] Specifically, the server calls the API of the emotion analysis engine and analyzes the user's input data and voice data.

[1158] The input data is the user's text input and voice data.

[1159] The sentiment analysis engine analyzes this data to determine the user's emotional state (e.g., stress level).

[1160] The output data is the analysis result "Stress level: High".

[1161] Step 3:

[1162] Based on the analysis results of the emotion analysis engine, the server instructs the generative AI to generate the optimal prompt.

[1163] Specifically, the server calls the generative AI API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: high."

[1164] The input data is the user's text input and the emotion analysis results.

[1165] Based on this data, generative AI automatically generates appropriate prompts.

[1166] The output data is a prompt such as "What are the major research findings on the latest trends in AI?"

[1167] Step 4:

[1168] The server sends the generated prompt to the user's terminal.

[1169] As a specific operation, the server returns the generated prompt to the user's terminal as an HTTP response.

[1170] The input data is a prompt sentence from the generative AI.

[1171] The output data is a prompt that is displayed on the user's terminal.

[1172] The user checks the prompts generated on the terminal and uses them to create documents and gather information.

[1173] (Application example 1)

[1174] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1175] Conventional prompt creation systems using generative AI generate prompts without considering the user's emotional state, which means they are unable to provide optimal support according to the user's situation. Furthermore, it is difficult to recommend appropriate content when the user is feeling stressed or in a specific emotional state.

[1176] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing content using presentation software, and an emotion engine for analyzing the user's emotional state. This makes it possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1177] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on user input.

[1178] A "prompt" is an instruction or question that a generative AI creates based on user input.

[1179] A "markup language" is a language used in document creation tools to describe the structure and format of a document.

[1180] A "document creation tool" is software for creating the outline of slides or documents.

[1181] "Presentation software" is software for displaying and editing created slides and documents.

[1182] The "emotion engine" is a system that analyzes emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1183] A system for implementing this invention includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing the content using presentation software, and an emotion engine for analyzing the user's emotional state.

[1184] System configuration

[1185] 1. Generative AI:

[1186] Software: Generative AI models (e.g., GPT-4)

[1187] What it does: Auto-generates optimal prompts based on user input.

[1188] 2. Emotion Engine:

[1189] Hardware: Smartphone camera, microphone

[1190] Software: Sentiment analysis software

[1191] Function: Analyzes emotions from the user's tone of voice, facial expressions, and choice of words.

[1192] 3. Document creation tools:

[1193] Software: Word processing tools

[1194] Function: Creates a slide skeleton.

[1195] 4. Presentation software:

[1196] Software: Presentation software (e.g., Microsoft PowerPoint)

[1197] Functions: View and edit created slides and documents.

[1198] Program processing

[1199] The server uses the smartphone's camera and microphone to collect the user's facial expressions and tone of voice in real time to analyze the user's emotional state. The emotion analysis software analyzes this data to identify the user's emotional state. For example, if the user is feeling stressed, the emotion engine feeds that information back to the generative AI.

[1200] The generative AI uses emotional data obtained from the emotion engine to generate prompts that best fit the user's emotional state. For example, if a user is feeling stressed, it will generate a prompt such as "Tell me some relaxing movies."

[1201] The generated prompts are output as markup language that can be pasted into a word processing tool, which then creates slide outlines that can be viewed and edited in presentation software.

[1202] Specific examples

[1203] While a user is using their smartphone, an emotion engine detects stress from their facial expressions. A generative AI model generates prompts such as "Tell me some relaxing movies" and outputs code that can be pasted into a word processor. The word processor then uses this code to create a slide deck that can be viewed and edited in presentation software.

[1204] Example prompt sentence:

[1205] Generate prompts to recommend movies that will help users relax when they're feeling stressed.

[1206] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1208] Step 1:

[1209] When a user uses a smartphone, the device uses a camera and microphone to collect the user's facial expressions and tone of voice in real time, and this data is fed into the emotion engine.

[1210] Step 2:

[1211] The device's emotion engine analyzes the collected facial expression and tone of voice data to identify the user's emotional state. For example, if the user is feeling stressed, that information will be output as the analysis result.

[1212] Step 3:

[1213] The server receives the user's emotional state data obtained from the emotion engine and inputs it into the generative AI. Based on this emotional state data, the generative AI generates a prompt that is optimal for the user's emotional state. For example, a prompt such as "Tell me about a relaxing movie" may be generated.

[1214] Step 4:

[1215] The prompts generated by the generative AI are output by the server as markup language to be pasted into a document creation tool. This markup language is then input into the document creation tool.

[1216] Step 5:

[1217] The document creation tool creates a slide outline based on the input markup language, and the created slide outline is output to the presentation software.

[1218] Step 6:

[1219] The presentation software provides the user with a viewable and editable version of the slide outlines output from the word processing tool, allowing the user to create a presentation based on the slides.

[1220] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1221] Example 2

[1222] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1223] Conventional document generation systems using generative AI generate uniform content without considering the user's emotional state, making it difficult to fully meet the user's needs. Furthermore, if the generated document does not meet the user's expectations, the user must re-enter the prompt text, which is inefficient.

[1224] 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.

[1225] In this invention, the server includes means for creating an optimal input sentence using a generative artificial intelligence, means for creating a markup language for a text editor using the generative artificial intelligence, means for analyzing the emotional state of a user and providing feedback to the generative artificial intelligence, and means for the generative artificial intelligence to adjust the markup language by reflecting the feedback from the emotion analysis, thereby enabling more appropriate and creative document generation according to the emotional state of the user.

[1226] "Generative AI" is an AI technology that automatically generates text and code based on user input.

[1227] An "input sentence" is a text that a user inputs to give instructions to a generative artificial intelligence.

[1228] A "text editor" is software that allows a user to edit text or code.

[1229] A "markup language" is a language for adding structure and style to text, and includes, for example, Markdown.

[1230] "Presentation software" is software for visually displaying information in the form of slides.

[1231] An "emotional state" refers to the emotions a user is feeling, such as happiness, excitement, sadness, etc.

[1232] "Feedback" refers to information the system provides to the generative artificial intelligence based on the user's emotional state and other information.

[1233] A "document outline" is an outline that shows the basic structure and main points of a document.

[1234] The present invention is a system for generating a markup language for a text editor according to the emotional state of a user using generative artificial intelligence. Specific embodiments of this system will be described below.

[1235] Hardware and software used

[1236] server

[1237] The server hosts a generative AI model and an emotion engine. The generative AI model receives prompts from the user and generates markup language based on them. The emotion engine analyzes the user's emotional state and feeds that information back to the generative AI model.

[1238] Terminal

[1239] The terminal provides an interface for the user to input a prompt sentence, sends the input prompt sentence to the server, and displays the generated result returned from the server to the user.

[1240] Data processing and calculation

[1241] Entering a prompt statement

[1242] The user enters a prompt in the device's input field specifying the content and structure of the markup language they want to generate, for example, "Generate Markdown for key research and challenges related to the latest developments in AI."

[1243] Sending a prompt

[1244] The terminal sends the prompt text entered by the user to the server. Specifically, the terminal sends the prompt text to the server using an HTTP request.

[1245] Parsing and generating prompts

[1246] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The generative AI model automatically generates markup language for the text editor based on the prompt. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[1247] markdown

[1248] Major research on the latest trends in AI

[1249] Key Challenges

[1250] Emotional state analysis and feedback

[1251] The emotion engine monitors the user's input and actions to analyze their emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[1252] Adjusting the generated results

[1253] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[1254] Returning and displaying generated results

[1255] The server receives the markup language generated by the generative AI model and returns it to the terminal. The terminal displays the markup language received from the server to the user. The user can check the generated markup language and edit or save it as necessary.

[1256] Specific examples

[1257] Prompt Sentence Examples

[1258] The user enters the following prompt text:

[1259] Generate Markdown for key research and challenges related to the latest trends in AI.

[1260] Example of generated Markdown

[1261] The generative AI model generates the following Markdown:

[1262] markdown

[1263] Major research on the latest trends in AI

[1264] Key Challenges

[1265] In this way, the system generates markup language based on prompt statements in cooperation with the server, terminal, and user.

[1266] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1267] Step 1:

[1268] The user enters a prompt statement.

[1269] The user enters a prompt in the device's input field, specifying the content and structure of the markup language they want to generate. For example, they might enter, "Please generate Markdown for major research and issues related to the latest trends in AI." The entered prompt is then sent to the server in the next step.

[1270] Step 2:

[1271] The terminal sends the prompt to the server.

[1272] The terminal sends the prompt text entered by the user to the server using an HTTP request. The input data is the prompt text, and the output is a request sent to the server.

[1273] Step 3:

[1274] The server receives the prompt sentence and passes it to the generative artificial intelligence model.

[1275] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The input data is the prompt, and the output is the input data for the generative AI model. Specifically, the server converts the prompt into an appropriate format and inputs it into the generative AI model.

[1276] Step 4:

[1277] A generative artificial intelligence model generates markup language based on the prompt sentence.

[1278] The generative artificial intelligence model automatically generates markup language for a text editor based on a prompt received from the server. The input data is the prompt, and the output is the generated markup language. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[1279] markdown

[1280] Major research on the latest trends in AI

[1281] Key Challenges

[1282] Step 5:

[1283] The emotion engine analyzes the user's emotional state and provides feedback to the generative artificial intelligence model.

[1284] The emotion engine monitors the user's input and behavior to analyze the user's emotional state. The input data is the user's behavioral data, and the output is the analysis result of the user's emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[1285] Step 6:

[1286] A generative artificial intelligence model adjusts the markup language based on feedback from the emotion engine.

[1287] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. The input data is the analysis result of the emotional state, and the output is the adjusted markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[1288] Step 7:

[1289] The server returns the generated markup language to the terminal.

[1290] The server receives the markup language generated by the generative AI model and sends it back to the terminal using an HTTP response. The input data is the generated markup language, and the output is the response sent to the terminal.

[1291] Step 8:

[1292] The terminal displays the generated markup language to the user.

[1293] The terminal displays the markup language received from the server to the user. The input data is the generated markup language, and the output is the display to the user. The user checks the generated markup language and edits or saves it as necessary.

[1294] (Application example 2)

[1295] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1296] Conventional content generation systems using generative AI have the problem of being unable to fully meet user needs because they generate content in a uniform tone and style without considering the user's emotional state. Furthermore, there was a lack of means to properly display the generated content on devices such as smartphones, which led to issues with reduced usability.

[1297] 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.

[1298] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markdown for VSCode using generative AI, means for creating slide outlines in VSCode, means for outputting and describing content in PowerPoint, means for recognizing the user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated markdown content on a smartphone. This makes it possible to generate content in an appropriate tone and style according to the user's emotional state and display it appropriately on devices such as smartphones.

[1299] "Generative AI" is an artificial intelligence technology that automatically generates content such as text and code based on user input.

[1300] A "prompt" is input data or instructions given to generative AI, and serves as the basis for determining the content and format of the content to be generated.

[1301] "VSCode" is a source code editor provided by Microsoft and is a tool used for programming and editing Markdown.

[1302] "Markdown" is a lightweight markup language for easily formatting text, and is widely used, especially for creating technical documentation and blog posts.

[1303] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is used to efficiently organize the content of the slides.

[1304] "PowerPoint" is presentation software provided by Microsoft, and is a tool for visually presenting information in slide format.

[1305] An "emotion engine" is a technology that recognizes a user's emotional state and adjusts the tone and style of the generated content accordingly.

[1306] A "smartphone" is a multi-functional mobile device that can access the Internet and run applications in addition to the functions of a mobile phone.

[1307] "Tone" refers to the overall atmosphere or mood of a piece of text or content, and is adjusted according to the user's emotions and intentions.

[1308] "Style" refers to the way in which text or content is expressed or formatted, and is adjusted according to the user's feelings and intentions.

[1309] A system for implementing this invention includes means for generating optimal prompts using generative AI, creating Markdown for VSCode using the generative AI, creating slide outlines in VSCode, and outputting and writing the content in PowerPoint. It also includes means for recognizing a user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated Markdown content on a smartphone.

[1310] System Program

[1311] The program of this system operates as follows.

[1312] Hardware and Software

[1313] Hardware: Smartphones, servers

[1314] Software: Python, OpenAI API, Emotion Recognition API, VSCode, PowerPoint

[1315] Data processing and calculation

[1316] 1. User prompt input:

[1317] The user uses a smartphone to input a prompt, for example, "I want you to write an article about the latest developments in AI."

[1318] 2. Emotion Recognition with Emotion Engine:

[1319] The server uses an emotion recognition API to recognize the user's emotional state, for example, recognizing that the user is expressing the emotion "joy."

[1320] 3. Adjust the prompt:

[1321] The server will tailor the prompt based on the perceived emotion, for example, "Please write an article about the latest developments in AI. Please make the content more creative and engaging."

[1322] 4. Generative AI Markdown Generation:

[1323] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. For example, the following Markdown is generated:

[1324] Major research on the latest trends in AI

[1325] Key Challenges

[1326] Task 1

[1327] Task 2

[1328] 5. View the generated Markdown:

[1329] The generated Markdown content is displayed on the smartphone, where users can view it and make edits or corrections as needed.

[1330] Specific examples

[1331] If a user inputs a prompt such as "I want you to write an article about the latest developments in AI," and the emotion engine recognizes "joy," the generative AI will generate more creative and interesting articles. For example, the following prompt sentences may be used:

[1332] Please write articles about the latest trends in AI. Please make the content more creative and engaging.

[1333] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[1334] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1335] Step 1:

[1336] The user inputs a prompt using a smartphone. The input prompt is an instruction to the generative AI and serves as a basis for determining the content and format of the generated content. For example, the user might input, "I want you to write an article about the latest trends in AI." This prompt is then sent to the server.

[1337] Step 2:

[1338] The server uses an emotion recognition API to recognize the user's emotional state. It receives and analyzes the user's emotional data, such as voice, text, and facial expressions, as input. The analysis results in the user's emotional state (e.g., "joy") being output.

[1339] Step 3:

[1340] The server adjusts the prompt based on the recognized emotion. It receives as input the original prompt and the emotion recognition result. For example, if the user indicates the emotion "joy," it adds "Please make the content more creative and engaging." to the prompt. The adjusted prompt is output.

[1341] Step 4:

[1342] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. It receives the tailored prompts as input and sends them to a generative AI model. The generative AI model generates Markdown content based on the prompts and outputs it. For example, the following Markdown is generated:

[1343] Major research on the latest trends in AI

[1344] Key Challenges

[1345] Task 1

[1346] Task 2

[1347] Step 5:

[1348] The generated Markdown content is displayed on the smartphone. The generated Markdown content is received as input and output to the smartphone's display screen. The user can view it and edit or modify it as needed.

[1349] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[1350] Example 3

[1351] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1352] Conventional slide creation systems require users to manually write the content of the slides, which is inefficient and makes it difficult to create appropriate slides that reflect the user's emotional state. Even when generative AI is used, the system does not adjust the slides to take the user's emotional state into account, which can make the user feel anxious or tense.

[1353] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1354] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and describing the content using presentation software, and means for detecting the user's emotional state and adjusting the slide content using the generative artificial intelligence, thereby making it possible to efficiently create appropriate slides according to the user's emotional state.

[1355] "Generative AI" is an AI technology that generates optimal text and data based on user input.

[1356] An "input sentence" is text data that is created by a generative artificial intelligence based on a user's request.

[1357] A "text editor" is software that allows users to create and edit text data.

[1358] A "markup language" is a description language for adding structure and meaning to text data.

[1359] A "slide outline" is an outline that shows the basic components of each slide in a presentation.

[1360] "Presentation software" is software for visually displaying information in the form of slides.

[1361] "Emotional state" indicates the psychological state of the user, and includes emotions such as anxiety and tension.

[1362] "Adjustment" is the process by which the generative AI changes the slide content depending on the user's emotional state.

[1363] The present invention relates to a system for efficiently creating slides using generative artificial intelligence. A specific embodiment of this system will be described below.

[1364] First, the user writes the content of the slides in Markdown format. Markdown is a markup language for adding structure and meaning to text data, and is a concise and easy-to-read format. For example, create a Markdown file like this:

[1365] markdown

[1366] Title slide

[1367] This is the title slide.

[1368] Slide 1

[1369] This is the content of slide 1.

[1370] Slide 2

[1371] This is slide 2.

[1372] Next, the user copies this Markdown file and pastes it into a new file in a text editor on the terminal, using any common software.

[1373] The device's text editor parses the Markdown file pasted by the user and uses the "Create Slides" function to generate a slide outline, which is an outline showing the basic components of each slide in a presentation. Specifically, the Markdown heading is treated as the slide title, and the text below it is treated as the slide content.

[1374] The generated slide outline is imported into presentation software. The user starts the presentation software and selects an option to import the slide outline. Any general software can be used as the presentation software.

[1375] The user writes necessary content for each slide using the presentation software, for example, adjusting the design of the slide and adding images and graphs.

[1376] Furthermore, the emotion engine detects the user's emotional state. The emotional state indicates the user's psychological state and includes feelings such as anxiety and tension. The emotion engine detects the user's emotional state in real time from the user's facial expressions and voice. If the user is feeling anxious or nervous, the generative AI adjusts the content of the slides to make them simpler and easier to understand. For example, it may replace complex graphs with simpler diagrams.

[1377] For example, the following prompts can be input to a generative artificial intelligence:

[1378] Please explain the process of creating a slide outline in a text editor based on the Markdown file provided by the user, and then outputting it to presentation software to complete the final slides. If the user feels anxious or nervous, the generative AI will adjust to generate simpler and easier-to-understand slide outlines and content for the presentation software.

[1379] In this way, it becomes possible to efficiently create appropriate slides according to the emotional state of the user. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1380] Step 1:

[1381] A user creates a Markdown file.

[1382] The user writes the content of the slides in Markdown format. For example, create a Markdown file like this:

[1383] markdown

[1384] Title slide

[1385] This is the title slide.

[1386] Slide 1

[1387] This is the content of slide 1.

[1388] Slide 2

[1389] This is slide 2.

[1390] Input: Markdown file containing the slide content

[1391] Output: Markdown formatted text data

[1392] Step 2:

[1393] The user pastes the Markdown file into a text editor.

[1394] The user copies the Markdown file they created, launches a text editor on their device, and pastes it into a new file.

[1395] Input: Markdown format text data

[1396] Output: Markdown data pasted into a text editor

[1397] Step 3:

[1398] The device uses the "Create Slides" function of the text editor to generate the outline of the slides.

[1399] The device's text editor parses the Markdown file pasted by the user and generates the outline of the slides using the "Create Slides" function, which treats the Markdown heading as the slide title and the text below it as the slide content.

[1400] Input: Markdown data pasted into a text editor

[1401] Output: Generated slide skeleton

[1402] Step 4:

[1403] The user imports the generated slide outline into presentation software.

[1404] The user saves the created slide outline and starts the presentation software, then imports the slide outline using the "import" function of the presentation software.

[1405] Input: Generated slide skeleton

[1406] Output: Slide outline imported into presentation software

[1407] Step 5:

[1408] The user writes the content of the slide in the presentation software.

[1409] The user writes necessary content for each slide using the presentation software, for example, adjusting the design of the slide and adding images and graphs.

[1410] Input: Slide outline imported into presentation software

[1411] Output: Finished slides

[1412] Step 6:

[1413] An emotion engine detects the user's emotional state, and a generative AI model adjusts the slide content.

[1414] The emotion engine detects the user's emotional state in real time from their facial expressions and voice. If the user is feeling anxious or nervous, the generative AI model will adjust the content of the slides to make them simpler and easier to understand, for example by replacing complex graphs with simpler diagrams.

[1415] Input: User's emotional state, completed slides

[1416] Output: Slides adjusted according to the user's emotional state

[1417] (Application example 3)

[1418] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1419] In conventional document creation systems, users had to manually create the outline of slides and output them to presentation software, which was a cumbersome process, making it difficult to create documents efficiently. Furthermore, it was not possible to adjust the slide content appropriately based on the user's emotional state, which could lead to a decline in the quality of the documents if the user felt anxious or nervous. This created a need for a system that could quickly create high-quality documents for content distribution services such as online lectures and webinars.

[1420] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1421] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for a text editor using the generative AI, means for creating a slide outline using the text editor, means for outputting and describing the content using presentation software, and means for adjusting the slide content according to the user's emotional state using an emotion engine. This enables users to efficiently create high-quality materials, and makes it possible to create appropriate materials according to the user's emotional state in content distribution services such as online lectures and webinars.

[1422] "Generative AI" is an artificial intelligence technology that generates optimal prompts and code based on user input.

[1423] A "text editor" is software for editing text data.

[1424] A "markup language" is a language used to add structure and meaning to text, and includes HTML and Markdown.

[1425] A "slide outline" is a component that concisely summarizes the title and content of each slide in a presentation.

[1426] "Presentation software" refers to software for visually displaying information in slide format, and generally includes PowerPoint and similar software.

[1427] An "emotion engine" is a technology that analyzes a user's emotional state and responds appropriately based on the results.

[1428] "User's emotional state" refers to the psychological state such as anxiety or tension felt by the user.

[1429] A "content distribution service" is a service that distributes information such as lectures and webinars online.

[1430] A system for implementing this invention includes a generative AI, a text editor, presentation software, and an emotion engine. Specific embodiments are described below.

[1431] The server uses a generative AI to create the optimal prompt. The generative AI generates an appropriate prompt sentence based on the information entered by the user and the content they want to search. This prompt sentence is output as a markup language for a text editor (e.g., Markdown).

[1432] The server then pastes the generated markup into a text editor, which parses the Markdown-formatted text and creates slide outlines, which briefly summarize the title and content of each slide.

[1433] The server then outputs the slide outline to presentation software (e.g., PowerPoint), which creates each slide based on the slide outline and allows the user to fill in the necessary content.

[1434] Furthermore, the emotion engine analyzes the user's emotional state. If the user is feeling anxious or nervous, the emotion engine simplifies the slide content and adjusts it to output in a more understandable format. This makes it possible to create appropriate materials according to the user's emotional state.

[1435] As a concrete example, consider a scenario in which a user is creating materials for an online lecture. The user enters the following Markdown text:

[1436] markdown

[1437] Online lecture title

[1438] Slide 1

[1439] This is the content of slide 1.

[1440] Slide 2

[1441] This is slide 2.

[1442] Entering this text into the application will generate the following slide outline:

[1443] Slide 1: Title: "Slide 1", Content: "This is the content of Slide 1."

[1444] Slide 2: Title: "Slide 2", Content: "This is the content of Slide 2."

[1445] If the emotion engine detects the user's emotional state as "anxious," the slide content is simplified and output in a more understandable format.

[1446] Example prompts to input to a generative AI model:

[1447] A user has entered the following Markdown text to create materials for an online lecture. If the emotion engine detects the user's emotional state as "anxious," simplify the slide content and output it.

[1448] Online lecture title

[1449] Slide 1

[1450] This is the content of slide 1.

[1451] Slide 2

[1452] This is slide 2.

[1453] In this way, users can efficiently create high-quality materials, and content distribution services such as online lectures and webinars can create appropriate materials according to the user's emotional state.

[1454] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1455] Step 1:

[1456] A user inputs text in Markdown format to create materials for an online lecture. The user uses a text editor to input the following Markdown text:

[1457] Input: Markdown-formatted text

[1458] Output: Markdown text entered by the user

[1459] Step 2:

[1460] The server creates the optimal prompt using a generative AI, which analyzes the Markdown text entered by the user and generates an appropriate prompt.

[1461] Input: User-entered Markdown text

[1462] Output: Generated prompt statement

[1463] Step 3:

[1464] The server creates a markup language (Markdown) for the text editor based on the generated prompt. The generative AI analyzes the prompt and generates text in Markdown format.

[1465] Input: Generated prompt text

[1466] Output: Markdown formatted text

[1467] Step 4:

[1468] The server pastes the generated Markdown text into a text editor, which parses it and creates a slide outline.

[1469] Input: Markdown-formatted text

[1470] Output: Slide outline

[1471] Step 5:

[1472] The server outputs the slide outline to presentation software (e.g., PowerPoint), which creates slides based on the slide outline and allows the user to write the necessary content.

[1473] Input: Slide outline

[1474] Output: Slides for presentation software

[1475] Step 6:

[1476] The server analyzes the user's emotional state using an emotion engine, which analyzes data such as the user's facial expressions and voice to determine whether the user is feeling anxious or nervous.

[1477] Input: User's facial expressions and voice data

[1478] Output: User's emotional state

[1479] Step 7:

[1480] The server adjusts the slide content based on the user's emotional state detected by the emotion engine. For example, if the user is feeling anxious or nervous, the server simplifies the slide content and outputs it in a more understandable format.

[1481] Input: user's emotional state, slides for presentation software

[1482] Output: Adjusted slide content

[1483] In this way, users can efficiently create high-quality materials, and content distribution services such as online lectures and webinars can create appropriate materials according to the user's emotional state.

[1484] 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.

[1485] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1486] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1487] 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.

[1488] [Third embodiment]

[1489] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1490] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1491] 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).

[1492] 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.

[1493] 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.

[1494] 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).

[1495] 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.

[1496] 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.

[1497] 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.

[1498] 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.

[1499] 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.

[1500] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1501] "Example 1"

[1502] This embodiment of the present invention has a means for generating optimal prompts using generative AI. Specifically, when a user inputs the information they need or the content they want to research, the generative AI automatically generates optimal prompts based on that information. For example, if a user inputs that they want to create a document about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[1503] "Example 2"

[1504] Furthermore, this embodiment of the present invention includes a means for generating markdown for VSCord using a generative AI. Specifically, the generative AI automatically generates markdown for VSCord based on a prompt. For example, based on the above prompt, the generative AI generates markdown including headings such as "Major Research on the Latest Trends in AI" and "Major Challenges."

[1505] "Example 3"

[1506] Furthermore, this embodiment of the present invention provides a means for creating a slide outline using VSCord. Specifically, the above markdown is pasted into VSCord, and a slide outline is created using VSCord's functions. For example, by using VSCord's "Create Slide" function, a slide outline is created in which the markdown heading is used as the slide title and the text below it is used as the slide content.

[1507] "Example 4"

[1508] Finally, this embodiment of the present invention includes a means for outputting the slides in PowerPoint and writing the necessary content. Specifically, the slide outline is output to PowerPoint and the necessary content is written therein. For example, PowerPoint slides corresponding to each slide in the slide outline are created and the content is written therein. This allows for efficient creation of materials.

[1509] The processing flow of each embodiment will be described below.

[1510] "Example 1"

[1511] Step 1: The user enters the information they need or the question they want to find into the system.

[1512] Step 2: Generative AI automatically generates optimal prompts based on this information.

[1513] Step 3: The generated prompt is presented to the user.

[1514] "Example 2"

[1515] Step 1: Generative AI automatically generates markdown for VSCOrd based on prompts.

[1516] Step 2: The generated markdown is presented to the user.

[1517] "Example 3"

[1518] Step 1: User pastes the generated markdown into VSCOrd.

[1519] Step 2: Create the outline of the slides using VSCOrd's functions.

[1520] Step 3: The created slide outline is presented to the user.

[1521] "Example 4"

[1522] Step 1: The user exports the slide outline to PowerPoint.

[1523] Step 2: Write down what users need on a PowerPoint slide.

[1524] Step 3: The completed document is presented to the user.

[1525] Example 1

[1526] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1527] Conventional information search systems have made it difficult for users to efficiently obtain the specific information they need. Furthermore, creating appropriate prompts for the content users want to search for requires a high level of specialized knowledge, making it difficult for average users to do so. This reduces the efficiency of information gathering and increases the time and effort required.

[1528] 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.

[1529] In this invention, the server includes a means for a user to use a terminal to input the content they want to search or the information they need, a means for the server to receive the user's input and analyze it using natural language processing technology, a means for the server to call a generative AI model based on the analysis results and pass the user's input as a prompt, a means for the generative AI model to generate an optimal prompt based on the user's input, and a means for the server to return the generated prompt to the user's terminal. This enables users to efficiently obtain the information they need even without specialized knowledge.

[1530] "User" means an individual or organization that uses the system to input information and obtain required information.

[1531] A "terminal" is an electronic device, such as a computer, smartphone, or tablet, that a user uses to enter information.

[1532] A "server" is a computer system whose role is to receive input from a user, analyze it, invoke a generative AI model to generate prompts, and return the results.

[1533] "Natural language processing technology" is a technology for analyzing text data entered by users and understanding its meaning, and specifically includes tokenization, keyword extraction, grammar analysis, etc.

[1534] A "generative AI model" is an artificial intelligence model that generates optimal prompts based on user input, and refers to advanced language models such as GPT-4.

[1535] "Prompts" are questions or instructions that a generative AI model generates based on user input, helping users efficiently obtain the information they need.

[1536] "Analysis results" are the data obtained after the server analyzes the user's input using natural language processing technology, and are an intermediate product before being passed to the generative AI model.

[1537] "Return" is the process by which the server sends the prompt generated by the generative AI model back to the user's device.

[1538] This invention is a system for efficiently obtaining information required by a user, and generates optimal prompts using a generative AI model. Specific embodiments of this system are described below.

[1539] First, the user uses a device (such as a PC or smartphone) to input the content they want to research or the information they need. For example, the user might type, "I want to create a document about the latest trends in AI." This input is entered as text into the device's input field and sent to the server by clicking the send button.

[1540] Next, the server receives the user's input. It analyzes the user's input text using natural language processing techniques such as Python's NLTK library or spaCy. Specifically, it tokenizes the input text and extracts important keywords. For example, keywords such as "AI," "latest trends," and "document creation" are extracted.

[1541] The server then calls a generative AI model (for example, GPT-4) based on the analysis results. The server passes the user's input as a prompt to the generative AI model. The generative AI model generates the optimal prompt based on the user's input. For example, it generates prompts such as "What are the major research topics regarding the latest trends in AI?" or "What are the major challenges in the latest trends in AI?"

[1542] Finally, the server returns the generated prompt to the user's device. The user can check the returned prompt on the device screen and make corrections or additions as necessary. This allows users to efficiently obtain the information they need, even if they do not have specialized knowledge.

[1543] As a concrete example, if a user inputs, "I want to create a document about the latest trends in AI," the generative AI model will generate the following prompt:

[1544] "What are the major research findings on the latest trends in AI?"

[1545] "What are the major challenges in the latest trends in AI?"

[1546] This system allows users to efficiently collect information and create the necessary materials.

[1547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1548] Step 1:

[1549] The user uses the device to enter the information they want to find out and the information they need.

[1550] Input: The user enters "I would like to create a document about the latest trends in AI" into the input field on their device and clicks the send button.

[1551] Output: User input is sent to the server.

[1552] Specific behavior: The user enters text using the device keyboard and clicks the send button, which sends the input to the server.

[1553] Step 2:

[1554] The server receives the user's input and analyzes it using natural language processing techniques.

[1555] Input: User input (e.g., "I want to create a document about the latest developments in AI").

[1556] Output: Analyzed keywords (e.g., "AI", "latest trends", "document creation").

[1557] How it works: The server uses Python's NLTK library and spaCy to tokenize the input text and extract important keywords.

[1558] Step 3:

[1559] The server calls the generative AI model based on the analysis results and passes the user's input as a prompt.

[1560] Input: Analyzed keywords (e.g., "AI," "latest trends," "document creation").

[1561] Output: The prompt passed to the generative AI model (e.g., "I would like to create a paper about the latest developments in AI").

[1562] Specific operation: Based on the analysis results, the server calls a generative AI model (e.g., GPT-4) and passes the user's input as a prompt.

[1563] Step 4:

[1564] A generative AI model generates optimal prompts based on user input.

[1565] Input: The prompt passed to the generative AI model (e.g., "I want to create a paper about the latest developments in AI").

[1566] Output: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[1567] What it does: A generative AI model analyzes user input and generates the most appropriate prompt.

[1568] Step 5:

[1569] The server generates a prompt and returns it to the user's terminal.

[1570] Input: Generated prompts (e.g., "What are the key research findings in the latest trends in AI?", "What are the key challenges in the latest trends in AI?").

[1571] Output: The prompt returned to the user's terminal.

[1572] What happens: The server sends the generated prompt to the user's device, allowing the user to view the prompt on their device's screen.

[1573] (Application example 1)

[1574] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1575] Conventional prompt creation systems using generative AI can generate optimal prompts based on the information a user needs or the content they want to research, but they lack the ability to automatically generate and provide relevant content to users based on the generated prompts. This means that users must manually create content based on the generated prompts, which is inefficient.

[1576] 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.

[1577] In this invention, the server includes means for creating an optimal prompt using generative AI, means for creating Markdown using generative AI, means for creating a slide outline, means for outputting and writing content using presentation software, means for generating an optimal prompt based on a topic entered by a user, means for automatically generating related content based on the generated prompt, and means for displaying the generated content to the user. This makes it possible to generate an optimal prompt based on a topic entered by a user, and automatically generate related content based on the prompt and provide it to the user.

[1578] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on information entered by the user.

[1579] A "prompt" is a question or instruction generated by generative AI in response to a user's request, and is the input data used to generate related information and content.

[1580] Markdown is a lightweight markup language for easily formatting text, and is one of the formats for content generated by generative AI.

[1581] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is automatically created by generative AI.

[1582] "Presentation software" is software for visually displaying information in slide format, and is used to output the outline of slides created by generative AI.

[1583] A "topic" is a subject or theme that a user is interested in and requests generative AI to generate information about.

[1584] "Content" refers to information and materials that generative AI automatically generates based on prompts, including in the form of articles, blog posts, reports, presentations, etc.

[1585] A "user" is an individual or organization that requests the generation of information or content using a generative AI system.

[1586] The system for implementing this invention uses generative AI to create optimal prompts, automatically generates related content based on those prompts, and provides it to users. Specific embodiments of this system are described below.

[1587] Hardware and software used

[1588] Hardware: Smartphone (iOS or Android)

[1589] Software: Python, OpenAI API, presentation software (e.g., Microsoft PowerPoint)

[1590] System configuration

[1591] 1. How to use generative AI to create optimal prompts:

[1592] The server generates the most appropriate prompts based on the topic entered by the user. For example, if a user wants to know about the latest trends in AI, the generative AI will generate prompts such as "What are the major research topics related to the latest trends in AI?" and "What are the major challenges in the latest trends in AI?"

[1593] 2. How to create Markdown using generative AI:

[1594] The server automatically generates relevant content in Markdown format based on the generated prompt, allowing users to easily get formatted text.

[1595] 3. How to create a slide outline:

[1596] The server automatically creates a slide outline that shows the basic structure and content of the presentation materials based on the generated content.

[1597] 4. How to output and write content using presentation software:

[1598] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the contents.

[1599] 5. How to generate the best prompt based on the topic entered by the user:

[1600] The server generates the most appropriate prompt based on the topic entered by the user. For example, for the topic "Latest trends in AI," the generative AI generates a prompt such as "What are the major research topics related to the latest trends in AI?"

[1601] 6. A way to auto-generate relevant content based on generated prompts:

[1602] The server automatically generates relevant content based on the generated prompts, for example, articles and reports on the latest trends in AI.

[1603] 7. How to display generated content to users:

[1604] The server displays the generated content to the user, who can view the generated content through his / her smartphone.

[1605] Specific examples

[1606] If a user wants to know about "The Latest in AI," the following prompt will be generated:

[1607] "What are the major research findings on the latest trends in AI?"

[1608] "What are the major challenges in the latest trends in AI?"

[1609] Based on these prompts, the generative AI generates relevant articles and reports and provides them to users, who can then view the content on their smartphones and use it as presentation materials if needed.

[1610] In this way, it is possible to generate optimal prompts based on the topic entered by the user, and automatically generate related content based on those prompts to provide to the user.

[1611] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1612] Step 1:

[1613] A user uses a smartphone to input topics of interest. The input topics are sent to the server. The input data is text data containing the information the user wants to know or research.

[1614] Step 2:

[1615] The server uses a generative AI to generate optimal prompts based on the received topic. Specifically, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate questions and instructions related to the topic. The input data is the topic entered by the user, and the output data is the generated prompt.

[1616] Step 3:

[1617] The server automatically generates relevant content based on the generated prompt. It uses a generative AI model again to generate content that includes answers to the prompt and related information. The input data is the generated prompt, and the output data is the generated content (e.g., article, report).

[1618] Step 4:

[1619] The server formats the generated content in Markdown, which makes the content easy to read and organized. The input data is the generated content and the output data is the Markdown formatted content.

[1620] Step 5:

[1621] The server automatically creates slide outlines for presentation materials based on the generated content. Specifically, it extracts key points from the generated content and places them on each page of the slides. The input data is content in Markdown format, and the output data is the slide outlines.

[1622] Step 6:

[1623] The server outputs the generated slide outline using presentation software (e.g., Microsoft PowerPoint) and writes the content. The input data is the slide outline, and the output data is the completed presentation material.

[1624] Step 7:

[1625] The server displays the generated content and presentation materials to the user. The user can view the content through their smartphone and download or edit it as needed. The input data is the generated content and presentation materials, and the output data is the information displayed to the user.

[1626] Example 2

[1627] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1628] In conventional document creation systems, users manually input prompts and create documents based on them, which required a lot of time and effort. Furthermore, the quality of the generated documents was often inconsistent, and they sometimes failed to meet user expectations. Furthermore, transferring the generated documents to other software was also a problem.

[1629] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for creating a markup language file for a text editor using the generative AI, means for creating a document outline using the text editor, means for outputting and describing the content using presentation software, means for receiving a prompt sentence entered by a user and passing it to the generative AI model, and means for receiving a markup language file generated from the generative AI model and displaying it to the user. This enables users to efficiently automatically generate high-quality documents and easily transfer them to other software.

[1630] "Generative AI" is an artificial intelligence technology that automatically generates documents and code based on prompts entered by the user.

[1631] A "prompt" is an instruction that a user inputs to a generative AI, and is used to determine the content of the document or code that is generated.

[1632] A "text editor" is software that allows users to create and edit text documents.

[1633] A "markup language file" is a text file used to define the structure and format of a document, including, for example, Markdown and HTML.

[1634] A "document outline" is an outline that shows the basic structure and main points of a document.

[1635] "Presentation software" means software for creating, editing, and displaying slide presentations.

[1636] A "server" is a computer system that receives and processes requests from clients over a network.

[1637] A "user" is someone who uses the system to enter prompts and receive generated documents and code.

[1638] This invention relates to a system for automatically generating markup language files for text editors using a generative AI model. Specific embodiments of this system are described below.

[1639] Hardware and software used

[1640] Subject: Server

[1641] The server is a computer system for running a generative AI model. Specifically, OpenAI's GPT-3 is used as the generative AI model. The server receives prompts sent by the user and passes them to the generative AI model. It also receives markup language files generated by the generative AI model and returns them to the user.

[1642] Subject: Terminal

[1643] The terminal is a device that allows a user to input a prompt text and send it to a server. Terminals include computer devices such as PCs, tablets, and smartphones. The terminal sends the prompt text input by the user to the server, receives the markup language file returned from the server, and displays it.

[1644] Subject: User

[1645] A user is a person who uses a terminal to enter a prompt and receive the generated markup language file. The user enters a prompt based on a specific theme or content and consumes a document automatically generated by a generative AI model.

[1646] Data processing and calculation

[1647] Subject: Server

[1648] The server passes the prompt received from the user to the generative AI model, which generates a markup language file based on the prompt, then sends the file back to the server, which then sends it to the user.

[1649] Specific examples

[1650] Prompt Sentence Examples

[1651] The user enters the following prompt text:

[1652] Major research on the latest trends in AI

[1653] Example of a generated markup language file

[1654] The generative AI model generates a Markdown file that looks like this:

[1655] markdown

[1656] Major research on the latest trends in AI

[1657] Key Challenges

[1658] 1. Data quality and quantity

[1659] 2. Model Interpretability

[1660] 3. Efficient use of computing resources

[1661] 4. Ethical Issues

[1662] In this way, based on the prompts entered by the user, the server automatically generates markup language files using a generative AI model and provides them to the user via their terminal. This system allows users to efficiently generate high-quality documents that can be easily transferred to other software.

[1663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1664] Step 1:

[1665] The user enters a prompt into an input field on the device, for example, "Major research on the latest trends in AI." The entered prompt is temporarily stored in the device's memory.

[1666] Step 2:

[1667] The user presses the send button to send the entered prompt text to the server. The terminal sends the prompt text to the server using an HTTP POST request. The input is the prompt text, and the output is an HTTP request to the server.

[1668] Step 3:

[1669] The server receives the prompt sent from the device. The server extracts the prompt from the body of the HTTP request and prepares to pass it to the generative AI model. The input is the HTTP request, and the output is the prompt.

[1670] Step 4:

[1671] The server passes the received prompt sentence to the generative AI model. Specifically, it calls the API of the generative AI model and passes the prompt sentence as a parameter. The input is the prompt sentence, and the output is an API request to the generative AI model.

[1672] Step 5:

[1673] The generative AI model generates a markup language file based on the prompt. The generative AI model uses an internal database and algorithms to generate the optimal document for the prompt. The input is the prompt, and the output is a markup language file.

[1674] Step 6:

[1675] The server receives the markup language file generated from the generative AI model. The server parses the data returned as an API response and extracts the markup language file. The input is the API response, and the output is the markup language file.

[1676] Step 7:

[1677] The server sends the generated markup language file to the terminal. The server returns the markup language file as an HTTP response. The input is the markup language file, and the output is the HTTP response to the terminal.

[1678] Step 8:

[1679] The terminal receives the markup language file sent from the server. The terminal extracts the markup language file from the body of the HTTP response and prepares it to be displayed to the user. The input is the HTTP response and the output is the markup language file.

[1680] Step 9:

[1681] The terminal displays the received markup language file to the user. Specifically, the markup language file is displayed in a text area or a dedicated viewer. The input is the markup language file, and the output is the document displayed to the user.

[1682] (Application example 2)

[1683] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1684] Conventional content generation systems require users to manually create prompts and edit the generated content, resulting in inefficiencies. Furthermore, the generated content lacked preview and saving / sharing functionality, resulting in poor user convenience. This made it difficult to quickly and efficiently generate content, especially technical documentation and blog posts.

[1685] 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.

[1686] In this invention, the server includes means for generating optimal prompts using generative AI, means for generating documents in markup language format using the generative AI, means for previewing the documents in markup language format in real time, means for editing the generated documents, and means for saving and sharing the generated documents, thereby enabling users to efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[1687] "Generative AI" is artificial intelligence that automatically generates content based on prompts entered by the user.

[1688] A "prompt" is input information that instructs generative AI on the content and direction of the content to be generated.

[1689] A "document in a markup language" is a language for writing documents with a specific structure and style, including Markdown and HTML.

[1690] The "means for displaying a preview in real time" is a function for displaying a generated document in a markup language format so that the document can be immediately visually confirmed.

[1691] "Means for editing" refers to the functionality that allows users to manually correct or modify the generated document.

[1692] "Means for saving and sharing" refers to the functionality for saving generated documents to local storage or cloud services and sharing them with other users.

[1693] An embodiment of this invention is a system that uses generative AI to create optimal prompts, creates documents in markup language format using generative AI, displays previews in real time, and allows editing, saving, and sharing.

[1694] System Program

[1695] This system is realized using the following hardware and software.

[1696] Hardware: Smartphones, head-mounted displays, servers

[1697] Software: Flask (a Python web framework), OpenAI API, markdown2 (a library that converts Markdown to HTML)

[1698] Processing flow

[1699] 1. Prompt input: The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt.

[1700] 2. Content generation using generative AI: The server generates a document in markup language format using the OpenAI API based on the input prompt.

[1701] 3. Real-time preview: The generated document is converted to HTML using the markdown2 library and previewed in real time on the user's device.

[1702] 4. Editing function: Users can manually edit the generated documents.

[1703] 5. Save and share function: Once edited, the document can be saved to local storage or cloud services and shared with other users.

[1704] Specific examples

[1705] For example, if a user types, "I want to generate a blog post about the latest developments in AI," the following prompt sentence might be used:

[1706] Prompt Sentence Examples

[1707] Produce blog posts on the latest developments in AI, including key research and challenges.

[1708] Based on this prompt, the generative AI generates a document in the following markup language format:

[1709] markdown

[1710] Major research on the latest trends in AI

[1711] Key Challenges

[1712] 1. Data bias

[1713] 2. Model Interpretability

[1714] 3. Privacy and Security

[1715] Latest research findings

[1716] New Models in Natural Language Processing

[1717] Advances in image recognition technology

[1718] Applications of reinforcement learning

[1719] In this way, users can efficiently generate high-quality content, preview it in real time, edit it as needed, and easily save and share it.

[1720] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1721] Step 1:

[1722] The user uses a smartphone or head-mounted display to input a summary of the content they want to generate and keywords as a prompt. The input prompt is sent to the server, where it is converted into a format that can be understood by the generative AI.

[1723] Step 2:

[1724] The server calls the OpenAI API based on the received prompt. The OpenAI API generates a document in markup language format based on the prompt. The generated document is returned to the server. Data processing involves parsing the prompt text and converting it into appropriate tokens.

[1725] Step 3:

[1726] The server converts the generated markup language document into HTML using the Markdown2 library. The converted HTML is sent to the user's device and displayed as a real-time preview. The markup language to HTML conversion process is performed as a data calculation.

[1727] Step 4:

[1728] The user can manually edit the previewed document. The edited content is sent back to the server. The input data is the user's edited content, and the output data is the updated document in markup language format.

[1729] Step 5:

[1730] The server saves the edited document to a local storage or a cloud service. The saved document can be shared with other users. Specific operations include saving the file and generating a shared link.

[1731] Example 3

[1732] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1733] The traditional process of creating presentation materials required a lot of manual work, which made it inefficient. Furthermore, transferring data between a text editor and presentation software was cumbersome, placing a heavy burden on users. Furthermore, maintaining consistency when editing slide content was difficult.

[1734] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1735] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and writing content using presentation software, means for importing the created slide outline into the presentation software, and means for editing the content of the slides using the presentation software, thereby enabling the creation of efficient and consistent presentation materials.

[1736] "Generative AI" is an AI technology that automatically generates optimal input sentences and code based on user input.

[1737] An "input sentence" is a text-format instruction sentence that the generative artificial intelligence creates in response to a user request.

[1738] A "text editor" is software for creating and editing text files.

[1739] A "markup language" is a language for adding structure and meaning to text, and is used to describe the outline of presentation materials.

[1740] A "slide outline" is an early stage slide that shows the basic structure and content of a presentation material.

[1741] "Presentation software" means software for creating, editing, and displaying slide-format materials.

[1742] "Import" is the operation of taking in data from other software or files.

[1743] "Editing" is the operation of changing or modifying existing data or content.

[1744] The present invention is a system for efficiently creating presentation materials using generative artificial intelligence. Specific embodiments of this system will be described below.

[1745] First, the user writes the content of the slides in Markdown format. Markdown is a markup language that can be easily edited with a text editor. For example, create a Markdown file like the one below.

[1746] markdown

[1747] Title slide

[1748] This slide is the title slide.

[1749] Slide 1

[1750] This slide is the first slide.

[1751] Slide 2

[1752] This is the second slide.

[1753] Next, the user pastes this Markdown file into a text editor. Any common text editing software can be used as the text editor. Here, we will use VSCode as a specific example.

[1754] Users generate slide outlines using the VSCode "Markdown Slide Generator" extension, which parses Markdown files, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[1755] The generated slide outline is imported into presentation software. Any general presentation creation software can be used as the presentation software. Here, we will use "PowerPoint" as a specific example.

[1756] Users can load slide outlines generated in VSCode using PowerPoint's "import" feature, which converts Markdown files into PowerPoint slides.

[1757] Finally, the user edits the slides in PowerPoint to create the final presentation, reviewing each slide and adding text and images as needed.

[1758] As a concrete example, the following prompt sentence can be input to the generative artificial intelligence:

[1759] Paste the Markdown file into a text editor to create the outline of your slides, then import it into your presentation software and edit each slide to create your final presentation.

[1760] By using this prompt sentence, the user can create slide materials efficiently. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[1761] Step 1:

[1762] A user creates a Markdown file.

[1763] Input: The user writes the content of the slide in Markdown format.

[1764] Specific behavior: A user uses a text editor to create a Markdown file like the one below.

[1765] markdown

[1766] Title slide

[1767] This slide is the title slide.

[1768] Slide 1

[1769] This slide is the first slide.

[1770] Slide 2

[1771] This is the second slide.

[1772] Output: A Markdown file is generated.

[1773] Step 2:

[1774] The user pastes the Markdown file into a text editor.

[1775] Input: A user-created Markdown file.

[1776] Specific behavior: The user opens a text editor (e.g., VSCode) and pastes a Markdown file.

[1777] Output: A Markdown file displayed in a text editor.

[1778] Step 3:

[1779] A user generates a slide outline using the "Markdown Slide Generator" extension in a text editor.

[1780] Input: Markdown file pasted into a text editor.

[1781] What it does: A user opens the VSCode command palette and selects "Markdown Slide Generator," which parses a Markdown file, recognizes each heading as a slide title, and automatically places the text below it as the slide content.

[1782] Output: A slide skeleton is generated.

[1783] Step 4:

[1784] The user imports the generated slide outline into presentation software.

[1785] Input: The generated slide skeleton.

[1786] What happens: A user opens presentation software (e.g., PowerPoint) and uses the "Import" function to load a slide outline file.

[1787] Output: The slide outline will be displayed in your presentation software.

[1788] Step 5:

[1789] The user edits the slide content in the presentation software to complete the final presentation material.

[1790] Input: Slide outline imported into presentation software.

[1791] What it does: The user selects each slide, adds and edits text boxes and images, and adjusts the slide layout and design as needed.

[1792] Output: The final presentation material is completed.

[1793] (Application example 3)

[1794] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1795] There is a need to efficiently display work procedures and safety instructions in factories and help workers understand them. However, conventional methods require a lot of time and effort to create slides manually, making it difficult to communicate information efficiently.

[1796] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1797] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for a text editor using generative AI, means for creating a slide outline using a text editor, means for outputting and describing the content using presentation software, and means for displaying work procedures and safety instructions in slide format as an application installed on a factory robot. This makes it possible to efficiently display work procedures and safety instructions in a factory and help workers understand them.

[1798] "Generative AI" is a system that uses artificial intelligence technology to generate text and data for specific purposes.

[1799] A "prompt" is an instruction or question entered into a generative AI to obtain a specific output.

[1800] A "text editor" is software for creating and editing text data.

[1801] A "markup language" is a language for adding structure and meaning to text, and includes HTML and Markdown.

[1802] A "slide outline" is an outline that shows the basic components of a presentation.

[1803] "Presentation software" refers to software for visually displaying information in slide format, including PowerPoint.

[1804] A "factory robot" is a mechanical device used to automate work in a factory.

[1805] A "task procedure" is an instruction that shows the steps or method for performing a particular task.

[1806] "Safety instructions" are precautions and instructions for workers to carry out their work safely.

[1807] The system for implementing this invention includes a series of processes that use generative AI to create optimal prompts, generate markup language for a text editor, create slide outlines, and output them using presentation software.Furthermore, as an application installed on a factory robot, it has the function of displaying work procedures and safety instructions in slide format.

[1808] System program generation

[1809] The server uses generative AI to create optimal prompts based on the information the user enters. The generative AI then uses the prompts to generate markup language (Markdown format) for a text editor, which contains work procedures and safety instructions for the factory.

[1810] The generated Markdown text is pasted into a text editor (e.g., VSCode) to create a slide outline, where the heading is the slide title and the text below it is the slide content.

[1811] Next, presentation software (e.g., PowerPoint) is used to convert the outline into the final slide format and write the content, allowing for efficient creation of materials.

[1812] Hardware and software used

[1813] Hardware: Factory robot display

[1814] Software: VSCode, Python, markdown library, pptx library

[1815] Data processing and calculation

[1816] The server uses generative AI to create prompts, then generates Markdown text based on the prompts, which is then converted into slide outlines in a text editor and then into the final slide format in presentation software.

[1817] Specific examples

[1818] For example, you can write down work procedures in a factory in Markdown format, create a slide outline using VSCode, and output it to PowerPoint using the following prompt text, which can be input to a generative AI model.

[1819] Prompt Sentence Examples

[1820] "Please tell me how to write down the work procedures in the factory in Markdown format, create the outline of the slides using VSCode, and output them to PowerPoint."

[1821] This system makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[1822] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1823] Step 1:

[1824] The server receives information input by the user and creates an optimal prompt for the generative AI. This prompt is an instruction sentence for generating content including work procedures and safety instructions within the factory. The input is an outline of the work procedures and safety instructions provided by the user, and the output is a prompt sentence passed to the generative AI.

[1825] Step 2:

[1826] The server uses a generative AI to generate markup language (Markdown format) for a text editor based on the prompt created in step 1. The input is the prompt text, and the output is text in Markdown format. The generative AI analyzes the prompt text and outputs work procedures and safety instructions in Markdown format with appropriate headings and lists.

[1827] Step 3:

[1828] The server pastes the generated Markdown text into a text editor (e.g., VSCode) to create a slide outline. The input is Markdown text, and the output is a slide outline. The text editor automatically places the Markdown heading as the slide title and the text below it as the slide content.

[1829] Step 4:

[1830] The server outputs the slide outline to presentation software (e.g., PowerPoint) and converts it into the final slide format. The input is the slide outline, and the output is the completed slide presentation. The presentation software creates and fills in each slide based on the slide outline.

[1831] Step 5:

[1832] The factory robot receives the completed slide presentation sent from the server and displays it on its display. The input is the completed slide presentation, and the output is the slides displayed on the factory robot's display. The factory robot displays work procedures and safety instructions in slide format to help workers understand them.

[1833] This series of processes makes it possible to efficiently display work procedures and safety instructions within the factory, helping workers to understand them.

[1834] 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.

[1835] "Example 1"

[1836] In one embodiment of the present invention, the system incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and provides feedback to the generative AI. For example, if the user senses stress, the generative AI is adjusted to generate more concise and clear prompts. This allows for more appropriate support tailored to the user's emotional state.

[1837] "Example 2"

[1838] The emotion engine is also used by the generative AI when generating markdown for VSCOrd. For example, if the user senses joy or excitement, the generative AI will be adjusted to generate more creative code. This allows for more appropriate code generation according to the user's emotional state.

[1839] "Example 3"

[1840] Furthermore, the emotion engine is also used when creating slide outlines in VSCord and when outputting and writing content in PowerPoint. For example, if the user senses anxiety or tension, the generative AI will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content. This makes it possible to create more appropriate materials based on the user's emotional state.

[1841] The processing flow of each embodiment will be described below.

[1842] "Example 1"

[1843] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1844] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1845] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1846] Step 4: The generative AI adjusts the prompt generation based on the feedback. For example, if it senses that the user is stressed, it will adjust to generate more concise and clear prompts.

[1847] "Example 2"

[1848] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1849] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1850] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1851] Step 4: The generative AI adjusts the markdown generated for VSCOrd based on the feedback. For example, if it senses that the user is happy or excited, it will adjust to generate more creative code.

[1852] "Example 3"

[1853] Step 1: The emotion engine receives input from the user (voice, facial expressions, words, etc.).

[1854] Step 2: The emotion engine analyzes the user's emotions based on tone of voice, facial expressions, and word choice.

[1855] Step 3: The emotion engine feeds the analysis results back to the generative AI.

[1856] Step 4: Based on the feedback, the generative AI makes adjustments when creating the slide outline in VSCord and when outputting and writing content in PowerPoint. For example, if it senses that the user is feeling anxious or nervous, it will adjust to generate simpler, easier-to-understand slide outlines and PowerPoint content.

[1857] Example 1

[1858] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1859] Conventional prompt generation systems using generative AI generate prompts without considering the user's emotional state, which means that they do not provide appropriate support according to the user's stress or emotional state. Furthermore, if the generated prompts do not match the user's emotional state, the user's work efficiency may decrease.

[1860] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for creating an optimal prompt using a generative AI, means for analyzing the user's emotional state using an emotion analysis engine, means for feeding back the emotion analysis result to the generative AI and adjusting the prompt generation, and means for providing the generated prompt to the user's terminal. This makes it possible to generate an appropriate prompt according to the user's emotional state and improve the user's work efficiency.

[1861] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts based on user input.

[1862] An "emotion analysis engine" is a system that analyzes emotions from a user's tone of voice, facial expressions, choice of words, etc.

[1863] A "prompt" is a question or instruction that specifically indicates the information the user needs or the content they want to find out.

[1864] "Feedback" is the process of returning the results of emotion analysis to the generative AI and adjusting the prompt generation.

[1865] A "terminal" is a device such as a computer or smartphone that a user uses to input and output data.

[1866] This invention is a system that combines generative AI and an emotion analysis engine to generate optimal prompts according to the user's emotional state. Specific embodiments of this system are described below.

[1867] Hardware and software used

[1868] Hardware: Servers, devices (PCs, smartphones, etc.)

[1869] Software: Generative AI (e.g., GPT-4), sentiment analysis engine

[1870] System configuration

[1871] 1. User Input

[1872] The user uses the device to input the content they want to research or the information they need. For example, the user might type "I want to create a document about the latest trends in AI" into the input field on their PC or smartphone.

[1873] 2. Emotion analysis using an emotion analysis engine

[1874] The server uses an emotion analysis engine to analyze the user's input, tone of voice, facial expressions, and choice of words. For example, the server calls the emotion analysis engine's API and analyzes the user's input data and voice data. The analysis result is returned as "Stress level: High."

[1875] 3. Prompt generation using generative AI

[1876] The server instructs the generative AI to generate the optimal prompt based on the analysis results of the emotion analysis engine. For example, the server calls the generative AI's API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: High." The generative AI automatically generates an appropriate prompt, taking into account the user's input and emotional state.

[1877] 4. Providing prompts

[1878] The server sends the generated prompt to the user's device, where the user can check the generated prompt and use it to create documents or gather information. For example, the user can search for related information on the Internet based on the prompt they received.

[1879] Specific examples

[1880] Example user input: "I want to create a document about the latest trends in AI."

[1881] Example of a generative AI prompt:

[1882] "What are the major research findings on the latest trends in AI?"

[1883] "What are the major challenges in the latest trends in AI?"

[1884] "What are the latest statistics on the latest trends in AI?"

[1885] This system allows users to efficiently gather the necessary information and create materials, and provides more appropriate support by generating prompts according to the user's emotional state.

[1886] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1887] Step 1:

[1888] The user uses the terminal to input the information they want to find out and the information they need.

[1889] Specifically, the user enters "I would like to create a document about the latest trends in AI" into the input field on their PC or smartphone and clicks the send button.

[1890] The input data is the text "I would like to create a document about the latest trends in AI."

[1891] The terminal transmits this input data to the server.

[1892] Step 2:

[1893] The server receives the user's input data and passes it to the sentiment analysis engine.

[1894] Specifically, the server calls the API of the emotion analysis engine and analyzes the user's input data and voice data.

[1895] The input data is the user's text input and voice data.

[1896] The sentiment analysis engine analyzes this data to determine the user's emotional state (e.g., stress level).

[1897] The output data is the analysis result "Stress level: High".

[1898] Step 3:

[1899] Based on the analysis results of the emotion analysis engine, the server instructs the generative AI to generate the optimal prompt.

[1900] Specifically, the server calls the generative AI API and passes the input "I would like to create a document about the latest trends in AI" and the emotion analysis result "Stress level: high."

[1901] The input data is the user's text input and the emotion analysis results.

[1902] Based on this data, generative AI automatically generates appropriate prompts.

[1903] The output data is a prompt such as "What are the major research findings on the latest trends in AI?"

[1904] Step 4:

[1905] The server sends the generated prompt to the user's terminal.

[1906] As a specific operation, the server returns the generated prompt to the user's terminal as an HTTP response.

[1907] The input data is a prompt sentence from the generative AI.

[1908] The output data is a prompt that is displayed on the user's terminal.

[1909] The user checks the prompts generated on the terminal and uses them to create documents and gather information.

[1910] (Application example 1)

[1911] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1912] Conventional prompt creation systems using generative AI generate prompts without considering the user's emotional state, which means they are unable to provide optimal support according to the user's situation. Furthermore, it is difficult to recommend appropriate content when the user is feeling stressed or in a specific emotional state.

[1913] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing content using presentation software, and an emotion engine for analyzing the user's emotional state. This makes it possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1914] "Generative AI" is an artificial intelligence system that automatically generates optimal prompts and content based on user input.

[1915] A "prompt" is an instruction or question that a generative AI creates based on user input.

[1916] A "markup language" is a language used in document creation tools to describe the structure and format of a document.

[1917] A "document creation tool" is software for creating the outline of slides or documents.

[1918] "Presentation software" is software for displaying and editing created slides and documents.

[1919] The "emotion engine" is a system that analyzes emotions from the user's tone of voice, facial expressions, choice of words, etc.

[1920] A system for implementing this invention includes means for creating optimal prompts using generative AI, means for creating markup language for documents using generative AI, means for creating slide outlines using a document creation tool, means for outputting and describing the content using presentation software, and an emotion engine for analyzing the user's emotional state.

[1921] System configuration

[1922] 1. Generative AI:

[1923] Software: Generative AI models (e.g., GPT-4)

[1924] What it does: Auto-generates optimal prompts based on user input.

[1925] 2. Emotion Engine:

[1926] Hardware: Smartphone camera, microphone

[1927] Software: Sentiment analysis software

[1928] Function: Analyzes emotions from the user's tone of voice, facial expressions, and choice of words.

[1929] 3. Document creation tools:

[1930] Software: Word processing tools

[1931] Function: Creates a slide skeleton.

[1932] 4. Presentation software:

[1933] Software: Presentation software (e.g., Microsoft PowerPoint)

[1934] Functions: View and edit created slides and documents.

[1935] Program processing

[1936] The server uses the smartphone's camera and microphone to collect the user's facial expressions and tone of voice in real time to analyze the user's emotional state. The emotion analysis software analyzes this data to identify the user's emotional state. For example, if the user is feeling stressed, the emotion engine feeds that information back to the generative AI.

[1937] The generative AI uses emotional data obtained from the emotion engine to generate prompts that best fit the user's emotional state. For example, if a user is feeling stressed, it will generate a prompt such as "Tell me some relaxing movies."

[1938] The generated prompts are output as markup language that can be pasted into a word processing tool, which then creates slide outlines that can be viewed and edited in presentation software.

[1939] Specific examples

[1940] While a user is using their smartphone, an emotion engine detects stress from their facial expressions. A generative AI model generates prompts such as "Tell me some relaxing movies" and outputs code that can be pasted into a word processor. The word processor then uses this code to create a slide deck that can be viewed and edited in presentation software.

[1941] Example prompt sentence:

[1942] Generate prompts to recommend movies that will help users relax when they're feeling stressed.

[1943] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1944] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1945] Step 1:

[1946] When a user uses a smartphone, the device uses a camera and microphone to collect the user's facial expressions and tone of voice in real time, and this data is fed into the emotion engine.

[1947] Step 2:

[1948] The device's emotion engine analyzes the collected facial expression and tone of voice data to identify the user's emotional state. For example, if the user is feeling stressed, that information will be output as the analysis result.

[1949] Step 3:

[1950] The server receives the user's emotional state data obtained from the emotion engine and inputs it into the generative AI. Based on this emotional state data, the generative AI generates a prompt that is optimal for the user's emotional state. For example, a prompt such as "Tell me about a relaxing movie" may be generated.

[1951] Step 4:

[1952] The prompts generated by the generative AI are output by the server as markup language to be pasted into a document creation tool. This markup language is then input into the document creation tool.

[1953] Step 5:

[1954] The document creation tool creates a slide outline based on the input markup language, and the created slide outline is output to the presentation software.

[1955] Step 6:

[1956] The presentation software provides the user with a viewable and editable version of the slide outlines output from the word processing tool, allowing the user to create a presentation based on the slides.

[1957] In this way, it is possible to generate optimal prompts according to the user's emotional state and provide more appropriate support to the user.

[1958] Example 2

[1959] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1960] Conventional document generation systems using generative AI generate uniform content without considering the user's emotional state, making it difficult to fully meet the user's needs. Furthermore, if the generated document does not meet the user's expectations, the user must re-enter the prompt text, which is inefficient.

[1961] 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.

[1962] In this invention, the server includes means for creating an optimal input sentence using a generative artificial intelligence, means for creating a markup language for a text editor using the generative artificial intelligence, means for analyzing the emotional state of a user and providing feedback to the generative artificial intelligence, and means for the generative artificial intelligence to adjust the markup language by reflecting the feedback from the emotion analysis, thereby enabling more appropriate and creative document generation according to the emotional state of the user.

[1963] "Generative AI" is an AI technology that automatically generates text and code based on user input.

[1964] An "input sentence" is a text that a user inputs to give instructions to a generative artificial intelligence.

[1965] A "text editor" is software that allows a user to edit text or code.

[1966] A "markup language" is a language for adding structure and style to text, and includes, for example, Markdown.

[1967] "Presentation software" is software for visually displaying information in the form of slides.

[1968] An "emotional state" refers to the emotions a user is feeling, such as happiness, excitement, sadness, etc.

[1969] "Feedback" refers to information the system provides to the generative artificial intelligence based on the user's emotional state and other information.

[1970] A "document outline" is an outline that shows the basic structure and main points of a document.

[1971] The present invention is a system for generating a markup language for a text editor according to the emotional state of a user using generative artificial intelligence. Specific embodiments of this system will be described below.

[1972] Hardware and software used

[1973] server

[1974] The server hosts a generative AI model and an emotion engine. The generative AI model receives prompts from the user and generates markup language based on them. The emotion engine analyzes the user's emotional state and feeds that information back to the generative AI model.

[1975] Terminal

[1976] The terminal provides an interface for the user to input a prompt sentence, sends the input prompt sentence to the server, and displays the generated result returned from the server to the user.

[1977] Data processing and calculation

[1978] Entering a prompt statement

[1979] The user enters a prompt in the device's input field specifying the content and structure of the markup language they want to generate, for example, "Generate Markdown for key research and challenges related to the latest developments in AI."

[1980] Sending a prompt

[1981] The terminal sends the prompt text entered by the user to the server. Specifically, the terminal sends the prompt text to the server using an HTTP request.

[1982] Parsing and generating prompts

[1983] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The generative AI model automatically generates markup language for the text editor based on the prompt. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[1984] markdown

[1985] Major research on the latest trends in AI

[1986] Key Challenges

[1987] Emotional state analysis and feedback

[1988] The emotion engine monitors the user's input and actions to analyze their emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[1989] Adjusting the generated results

[1990] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[1991] Returning and displaying generated results

[1992] The server receives the markup language generated by the generative AI model and returns it to the terminal. The terminal displays the markup language received from the server to the user. The user can check the generated markup language and edit or save it as necessary.

[1993] Specific examples

[1994] Prompt Sentence Examples

[1995] The user enters the following prompt text:

[1996] Generate Markdown for key research and challenges related to the latest trends in AI.

[1997] Example of generated Markdown

[1998] The generative AI model generates the following Markdown:

[1999] markdown

[2000] Major research on the latest trends in AI

[2001] Key Challenges

[2002] In this way, the system generates markup language based on prompt statements in cooperation with the server, terminal, and user.

[2003] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2004] Step 1:

[2005] The user enters a prompt statement.

[2006] The user enters a prompt in the device's input field, specifying the content and structure of the markup language they want to generate. For example, they might enter, "Please generate Markdown for major research and issues related to the latest trends in AI." The entered prompt is then sent to the server in the next step.

[2007] Step 2:

[2008] The terminal sends the prompt to the server.

[2009] The terminal sends the prompt text entered by the user to the server using an HTTP request. The input data is the prompt text, and the output is a request sent to the server.

[2010] Step 3:

[2011] The server receives the prompt sentence and passes it to the generative artificial intelligence model.

[2012] The server analyzes the prompt received from the terminal and passes it to the generative AI model. The input data is the prompt, and the output is the input data for the generative AI model. Specifically, the server converts the prompt into an appropriate format and inputs it into the generative AI model.

[2013] Step 4:

[2014] A generative artificial intelligence model generates markup language based on the prompt sentence.

[2015] The generative artificial intelligence model automatically generates markup language for a text editor based on a prompt received from the server. The input data is the prompt, and the output is the generated markup language. For example, if the prompt is "Please generate Markdown about major research on the latest trends in AI and its challenges," it will generate Markdown like the following:

[2016] markdown

[2017] Major research on the latest trends in AI

[2018] Key Challenges

[2019] Step 5:

[2020] The emotion engine analyzes the user's emotional state and provides feedback to the generative artificial intelligence model.

[2021] The emotion engine monitors the user's input and behavior to analyze the user's emotional state. The input data is the user's behavioral data, and the output is the analysis result of the user's emotional state. For example, if it determines that the user is feeling joy or excitement, it feeds that information back to the generative AI model.

[2022] Step 6:

[2023] A generative artificial intelligence model adjusts the markup language based on feedback from the emotion engine.

[2024] The generative AI model receives feedback from the emotion engine and adjusts the content and style of the generated markup. The input data is the analysis result of the emotional state, and the output is the adjusted markup. For example, if the user is feeling happy or excited, it generates markup with more creative headlines and content.

[2025] Step 7:

[2026] The server returns the generated markup language to the terminal.

[2027] The server receives the markup language generated by the generative AI model and sends it back to the terminal using an HTTP response. The input data is the generated markup language, and the output is the response sent to the terminal.

[2028] Step 8:

[2029] The terminal displays the generated markup language to the user.

[2030] The terminal displays the markup language received from the server to the user. The input data is the generated markup language, and the output is the display to the user. The user checks the generated markup language and edits or saves it as necessary.

[2031] (Application example 2)

[2032] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2033] Conventional content generation systems using generative AI have the problem of being unable to fully meet user needs because they generate content in a uniform tone and style without considering the user's emotional state. Furthermore, there was a lack of means to properly display the generated content on devices such as smartphones, which led to issues with reduced usability.

[2034] 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.

[2035] In this invention, the server includes means for creating optimal prompts using generative AI, means for creating markdown for VSCode using generative AI, means for creating slide outlines in VSCode, means for outputting and describing content in PowerPoint, means for recognizing the user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated markdown content on a smartphone. This makes it possible to generate content in an appropriate tone and style according to the user's emotional state and display it appropriately on devices such as smartphones.

[2036] "Generative AI" is an artificial intelligence technology that automatically generates content such as text and code based on user input.

[2037] A "prompt" is input data or instructions given to generative AI, and serves as the basis for determining the content and format of the content to be generated.

[2038] "VSCode" is a source code editor provided by Microsoft and is a tool used for programming and editing Markdown.

[2039] "Markdown" is a lightweight markup language for easily formatting text, and is widely used, especially for creating technical documentation and blog posts.

[2040] A "slide outline" is an outline that shows the basic structure and content of a presentation document, and is used to efficiently organize the content of the slides.

[2041] "PowerPoint" is presentation software provided by Microsoft, and is a tool for visually presenting information in slide format.

[2042] An "emotion engine" is a technology that recognizes a user's emotional state and adjusts the tone and style of the generated content accordingly.

[2043] A "smartphone" is a multi-functional mobile device that can access the Internet and run applications in addition to the functions of a mobile phone.

[2044] "Tone" refers to the overall atmosphere or mood of a piece of text or content, and is adjusted according to the user's emotions and intentions.

[2045] "Style" refers to the way in which text or content is expressed or formatted, and is adjusted according to the user's feelings and intentions.

[2046] A system for implementing this invention includes means for generating optimal prompts using generative AI, creating Markdown for VSCode using the generative AI, creating slide outlines in VSCode, and outputting and writing the content in PowerPoint. It also includes means for recognizing a user's emotional state using an emotion engine and adjusting the tone and style of the generated content, and means for displaying the generated Markdown content on a smartphone.

[2047] System Program

[2048] The program of this system operates as follows.

[2049] Hardware and Software

[2050] Hardware: Smartphones, servers

[2051] Software: Python, OpenAI API, Emotion Recognition API, VSCode, PowerPoint

[2052] Data processing and calculation

[2053] 1. User prompt input:

[2054] The user uses a smartphone to input a prompt, for example, "I want you to write an article about the latest developments in AI."

[2055] 2. Emotion Recognition with Emotion Engine:

[2056] The server uses an emotion recognition API to recognize the user's emotional state, for example, recognizing that the user is expressing the emotion "joy."

[2057] 3. Adjust the prompt:

[2058] The server will tailor the prompt based on the perceived emotion, for example, "Please write an article about the latest developments in AI. Please make the content more creative and engaging."

[2059] 4. Generative AI Markdown Generation:

[2060] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. For example, the following Markdown is generated:

[2061] Major research on the latest trends in AI

[2062] Key Challenges

[2063] Task 1

[2064] Task 2

[2065] 5. View the generated Markdown:

[2066] The generated Markdown content is displayed on the smartphone, where users can view it and make edits or corrections as needed.

[2067] Specific examples

[2068] If a user inputs a prompt such as "I want you to write an article about the latest developments in AI," and the emotion engine recognizes "joy," the generative AI will generate more creative and interesting articles. For example, the following prompt sentences may be used:

[2069] Please write articles about the latest trends in AI. Please make the content more creative and engaging.

[2070] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[2071] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2072] Step 1:

[2073] The user inputs a prompt using a smartphone. The input prompt is an instruction to the generative AI and serves as a basis for determining the content and format of the generated content. For example, the user might input, "I want you to write an article about the latest trends in AI." This prompt is then sent to the server.

[2074] Step 2:

[2075] The server uses an emotion recognition API to recognize the user's emotional state. It receives and analyzes the user's emotional data, such as voice, text, and facial expressions, as input. The analysis results in the user's emotional state (e.g., "joy") being output.

[2076] Step 3:

[2077] The server adjusts the prompt based on the recognized emotion. It receives as input the original prompt and the emotion recognition result. For example, if the user indicates the emotion "joy," it adds "Please make the content more creative and engaging." to the prompt. The adjusted prompt is output.

[2078] Step 4:

[2079] The server uses the OpenAI API to generate Markdown content based on the tailored prompts. It receives the tailored prompts as input and sends them to a generative AI model. The generative AI model generates Markdown content based on the prompts and outputs it. For example, the following Markdown is generated:

[2080] Major research on the latest trends in AI

[2081] Key Challenges

[2082] Task 1

[2083] Task 2

[2084] Step 5:

[2085] The generated Markdown content is displayed on the smartphone. The generated Markdown content is received as input and output to the smartphone's display screen. The user can view it and edit or modify it as needed.

[2086] In this way, content can be generated in an appropriate tone and style according to the user's emotional state and displayed appropriately on devices such as smartphones.

[2087] Example 3

[2088] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2089] Conventional slide creation systems require users to manually write the content of the slides, which is inefficient and makes it difficult to create appropriate slides that reflect the user's emotional state. Even when generative AI is used, the system does not adjust the slides to take the user's emotional state into account, which can make the user feel anxious or tense.

[2090] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[2091] In this invention, the server includes means for creating optimal input sentences using generative artificial intelligence, means for creating markup language for a text editor using the generative artificial intelligence, means for creating a slide outline using the text editor, means for outputting and describing the content using presentation software, and means for detecting the user's emotional state and adjusting the slide content using the generative artificial intelligence, thereby making it possible to efficiently create appropriate slides according to the user's emotional state.

[2092] "Generative AI" is an AI technology that generates optimal text and data based on user input.

[2093] An "input sentence" is text data that is created by a generative artificial intelligence based on a user's request.

[2094] A "text editor" is software that allows users to create and edit text data.

[2095] A "markup language" is a description language for adding structure and meaning to text data.

[2096] A "slide outline" is an outline that shows the basic components of each slide in a presentation.

[2097] "Presentation software" is software for visually displaying information in the form of slides.

[2098] "Emotional state" indicates the psychological state of the user, and includes emotions such as anxiety and tension.

[2099] "Adjustment" is the process by which the generative AI changes the slide content depending on the user's emotional state.

[2100] The present invention relates to a system for efficiently creating slides using generative artificial intelligence. A specific embodiment of this system will be described below.

[2101] First, the user writes the content of the slides in Markdown format. Markdown is a markup language for adding structure and meaning to text data, and is a concise and easy-to-read format. For example, create a Markdown file like this:

[2102] markdown

[2103] Title slide

[2104] This is the title slide.

[2105] Slide 1

[2106] This is the content of slide 1.

[2107] Slide 2

[2108] This is slide 2.

[2109] Next, the user copies this Markdown file and pastes it into a new file in a text editor on the terminal, using any common software.

[2110] The device's text editor parses the Markdown file pasted by the user and uses the "Create Slides" function to generate a slide outline, which is an outline showing the basic components of each slide in a presentation. Specifically, the Markdown heading is treated as the slide title, and the text below it is treated as the slide content.

[2111] The generated slide outline is imported into presentation software. The user starts the presentation software and selects an option to import the slide outline. Any general software can be used as the presentation software.

[2112] The user writes necessary content for each slide using the presentation software, for example, adjusting the design of the slide and adding images and graphs.

[2113] Furthermore, the emotion engine detects the user's emotional state. The emotional state indicates the user's psychological state and includes feelings such as anxiety and tension. The emotion engine detects the user's emotional state in real time from the user's facial expressions and voice. If the user is feeling anxious or nervous, the generative AI adjusts the content of the slides to make them simpler and easier to understand. For example, it may replace complex graphs with simpler diagrams.

[2114] For example, the following prompts can be input to a generative artificial intelligence:

[2115] Please explain the process of creating a slide outline in a text editor based on the Markdown file provided by the user, and then outputting it to presentation software to complete the final slides. If the user feels anxious or nervous, the generative AI will adjust to generate simpler and easier-to-understand slide outlines and content for the presentation software.

[2116] ...

Claims

1. A means for accepting input information from a user; means for recognizing an emotional state of the user using an emotion engine; means for generating prompts responsive to the user's input information and the user's emotional state using generative AI; means for generating a markup language outline based on the generated prompts using the generative AI; means for outputting the outline to presentation software; A system including:

2. The means for creating the prompt adjusts the prompt so that the gist is in a tone and style responsive to the emotional state of the user. The system of claim 1 .

3. The input information is information the user needs or wants to know. The system of claim 1 .

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