System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting usage information of a generated AI tool; means for transmitting the collected usage information to a server; means for storing the transmitted usage information in a storage; means for analyzing and categorizing the stored usage information; means for visualizing the categorized usage information on a web platform; means for evaluating a user's usage of the generated AI tool based on the usage information; means for determining a reward for the user based on the evaluation; and means for holding a contest for promoting the usage.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] This invention relates to a system for promoting the business use of generative AI tools across an entire company. Conventionally, the use of generative AI tools has been left up to individual users, making it difficult to evaluate the company's overall efficiency and contribution to business performance. Furthermore, usage data was not shared sufficiently, making it difficult to reuse other users' knowledge and experience. Furthermore, there was no system for properly evaluating business performance using generative AI tools, making it difficult to improve user motivation. [Means for solving the problem]

[0005] In order to solve such problems, the present invention provides the following means.

[0006] A means of collecting usage data for the generative AI tool; and

[0007] means for transmitting the collected usage data to a server;

[0008] a means for storing the transmitted usage data in storage;

[0009] means for analyzing and categorizing the stored usage data;

[0010] a means for visualizing the classified usage data on a web platform;

[0011] A means for evaluating a user's performance in using the generated AI tool based on usage data; and

[0012] means for determining a reward for the user based on the rating;

[0013] By establishing a means to hold contests to promote usage and making effective use of these, we will promote the business use of generative AI tools throughout the company and provide a system that allows each user's knowledge and experience to be shared and reused.

[0014] Furthermore, the present invention has a means for recording metadata including prompts and generated content as usage data of the AI ​​tool, which enables more specific understanding and evaluation of usage. Furthermore, in analyzing usage data, the present invention has a means for automatically categorizing prompts using natural language processing technology, which enables efficient data organization and classification.

[0015] A "generative AI tool" is an artificial intelligence technology that generates content such as text, images, or code based on natural language prompts.

[0016] "Usage Data" means information generated through the use of a Generative AI Tool, including prompts, output results, usage time, user ID, and other metadata.

[0017] "Means for collection" refers to a function or device for regularly recording and collecting usage data of the generative AI tool.

[0018] The "transmitting means" is a function or device for transmitting collected data to a server at a predetermined timing.

[0019] "Server" means a computer system that receives, stores, analyzes, and categorizes Usage Data.

[0020] "Storage" means a device for safely and efficiently storing collected and transmitted usage data.

[0021] "Analyzing means" are algorithms and processing programs that facilitate interpreting and categorizing stored usage data.

[0022] A "means for classifying" is a function or device for automatically assigning analyzed usage data to a particular category.

[0023] The "web platform" is an online system that visualizes classified usage data and allows users to access, view, and search it.

[0024] "Means for evaluation" refers to a function or device for scoring and evaluating a user's usage record of the generated AI tool based on usage data.

[0025] The "means for determining a reward" is a function or device for determining a reward or bonus for a user based on the evaluation score.

[0026] "Means for holding a contest" refers to a function or device for holding a contest in which users compete against each other on their achievements in using the AI ​​generation tool, and for encouraging participation.

[0027] A "prompt" is a natural language query that requests the generation AI tool to give instructions for operation or generate information. [Brief explanation of the drawings]

[0028] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0029] 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.

[0030] First, the terms used in the following description will be explained.

[0031] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] [First embodiment]

[0037] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0038] 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.

[0039] 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).

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0049] This invention relates to a system for promoting the use of generative AI tools throughout a company. This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on the results. It also holds contests to promote usage.

[0050] System Overview

[0051] The system consists of the following main components:

[0052] Generative AI tools used by users

[0053] User terminal

[0054] Central Server

[0055] Web Platform

[0056] Secure Storage

[0057] Program processing

[0058] 1. Collecting usage data of generative AI tools

[0059] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[0060] A generative AI tool processes the input prompts and returns generated content to the user.

[0061] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[0062] 2. Transmission and storage of log data

[0063] The terminal periodically sends the collected log data to the server.

[0064] The server stores the received log data in secure storage, where the data is encrypted using a secure communication protocol (e.g., HTTPS).

[0065] 3. Data Analysis and Classification

[0066] The server analyzes the stored log data and automatically categorizes the prompt content using natural language processing technology.

[0067] Duplicate prompts are detected and removed as needed, ensuring only the necessary data is ultimately saved to the database.

[0068] 4. Data Visualization

[0069] The server visualizes the organized data on a web platform, making it accessible and viewable by users.

[0070] Users can log in to the platform and view and search other users' prompts and generated results.

[0071] 5. Evaluation of usage record

[0072] The server evaluates each user's performance in using the generated AI tool based on usage data, converting the evaluation into a score and measuring the efficiency and contribution to business performance.

[0073] Based on this score, the server determines the user's rewards and bonuses.

[0074] 6. Hosting a Contest

[0075] The server announces the practical application example contest on the web platform and provides an environment in which users can apply.

[0076] Users can submit their own efforts and compete against other users, with evaluation criteria including practicality, creativity, and contribution to business performance.

[0077] Specific examples

[0078] Specific examples are shown below.

[0079] 1. Use of generative AI tools

[0080] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[0081] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[0082] The device will log this operation.

[0083] 2. Transmission and storage of log data

[0084] The terminal periodically sends log data to the server.

[0085] The server receives the data and stores it in storage.

[0086] 3. Data Analysis and Classification

[0087] The server categorizes the prompt into the "Marketing" category and reflects it in the database.

[0088] 4. Visualization and Evaluation

[0089] The user may access a web platform to view other marketing-related prompts and their generated results.

[0090] The server also evaluates the user's activity and determines the reward for the next year.

[0091] As described above, the system of the present invention provides a concrete means for effectively utilizing generative AI tools throughout the company to achieve efficiency and improved performance.

[0092] The processing flow will be explained below.

[0093] Step 1: Use generative AI tools

[0094] A user logs in to the generative AI tool.

[0095] The user enters a prompt into the generative AI tool (e.g., "Please create a tagline for our new product").

[0096] A generative AI tool processes the input prompts and returns generated content (e.g., innovative products that open up the future) to the user.

[0097] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[0098] Step 2: Sending log data

[0099] The terminal sends the collected log data to the server at regular intervals (e.g., every hour).

[0100] The transmission is done in encrypted form using a secure communication protocol (e.g. HTTPS).

[0101] Step 3: Receiving and storing log data

[0102] The server receives the log data sent from the terminal.

[0103] The server decompresses the received log data and stores it in secure storage.

[0104] The server creates indexes to eliminate data redundancy and enable efficient searching.

[0105] Step 4: Analyze and classify the data

[0106] The server analyzes the stored log data.

[0107] The server uses natural language processing technology to automatically categorize the prompt content into categories (e.g., "Marketing," "Technical Documentation," etc.).

[0108] The server identifies and removes duplicate prompts, creating an optimized database.

[0109] Step 5: Visualize the data

[0110] The server classifies and organizes the log data, which is then visualized on a web platform.

[0111] Allows users to log in to a web platform to browse and search categorized prompts and generated results.

[0112] Step 6: Evaluate usage

[0113] The server evaluates the user's usage performance of the generated AI tool based on the usage data.

[0114] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, etc.).

[0115] Step 7: Determine the reward

[0116] The server determines the user's reward or bonus based on the evaluation score calculated.

[0117] The server notifies the evaluation score and reward determination on the web platform.

[0118] Step 8: Host a Contest

[0119] The server announces the use case contest on the web platform.

[0120] Users submit their work to the contest.

[0121] The server will evaluate the submitted practical applications and determine the winners.

[0122] This is the specific process flow of the invention. This system promotes the use of generative AI tools throughout the company, allowing for efficient data management and improved user motivation.

[0123] Example 1

[0124] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0125] With conventional generative AI models, it has been difficult to effectively evaluate each user's usage and the quality of the generated content, leading to improvements in company-wide operational efficiency. Fair and transparent standards are also needed for evaluating usage performance and determining compensation. Furthermore, there has been a lack of mechanisms for users to share their generated results with each other and a system for promoting performance.

[0126] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0127] In this invention, the server includes means for collecting usage data of the generative AI model, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for analyzing and categorizing the stored usage data, means for visualizing the categorized usage data on a web platform, means for evaluating users' usage performance of the generative AI model based on the usage data, means for determining user rewards based on the evaluation, means for holding contests to promote usage performance, means for encrypting the collected usage data using a secure communication protocol, means for recording generated content and its prompts as metadata, means for automatically detecting and deleting duplicate prompts, and means for searching and viewing prompts and results generated by users. This enables effective and fair evaluation of business use of the generative AI model, improving company-wide business efficiency, and enabling users to share results.

[0128] A "generative AI model" is a type of computer program that uses artificial intelligence to generate new data or content based on input data.

[0129] A "prompt" refers to textual instructions or requests that a user enters into a generative AI model.

[0130] "Usage Data" means data including log information, prompts, generated content, and associated metadata related to the use of a Generative AI Model.

[0131] A "server" is a computer system that processes, stores, and manages data on a network.

[0132] "Storage" is a data storage device or system for persistently storing data.

[0133] "Web Platform" means a web-based software application for providing data visualization, sharing, and access over the Internet.

[0134] "Analysis" is the process of taking log data and generated content and evaluating and categorizing the data based on specific rules and algorithms.

[0135] "Metadata" is data that includes attribute and descriptive information associated with prompts and generated content.

[0136] A "secure communication protocol" is a communication protocol for encrypting and safely transmitting and receiving data, and examples include HTTPS.

[0137] "Duplicate prompts" refer to identical or very similar instruction or request text.

[0138] "Evaluation" is the process of quantitatively or qualitatively assessing the performance of generative AI models and the quality of the content they generate.

[0139] A "contest" is an event in which user-generated content or prompts are compared based on specific criteria, and the best submissions are selected and rewarded or awarded.

[0140] "Rewards" are incentives such as money or goods given to users based on the evaluation results.

[0141] This invention relates to a system for promoting the business use of generative AI models across the entire company. This system collects, analyzes, and classifies usage data of generative AI models, evaluates user usage performance, and determines rewards based on the results. It also includes a function to hold contests to promote usage.

[0142] System configuration

[0143] The system consists of the following main components:

[0144] Generative AI models used by users

[0145] User terminal

[0146] Central Server

[0147] Web Platform

[0148] Secure Storage

[0149] Collecting usage data for generative AI models

[0150] The user logs in to the generative AI model and inputs a prompt. For example, the user might input a prompt such as, "Please create a catchphrase for a new product." This prompt is processed by the generative AI model, which generates an "innovative product that will open up the future" and returns it to the user. The device records this series of operations as a log. The log includes the prompt, the generation result, the usage time, the user ID, etc.

[0151] Sending and storing log data

[0152] The terminal periodically sends the collected log data to the server. The data is sent in encrypted form using a secure communication protocol such as HTTPS. The server then stores the received log data in secure storage.

[0153] Data analysis and classification

[0154] The server analyzes the stored log data. This analysis uses natural language processing technology to extract keywords for each prompt. It then automatically classifies prompts into categories such as "Marketing" or "Finance" based on the extracted keywords. Duplicate prompts are detected and deleted as necessary.

[0155] Data Visualization

[0156] The server visualizes the organized data on a web platform. Users can view and search other users' prompts and generated results by logging in to the web platform. A visually easy-to-understand dashboard is provided, displaying data by category.

[0157] Evaluation of usage history

[0158] The server evaluates the user's performance in using the generated AI model based on usage data. This evaluation is scored using indicators such as frequency of use, quality of generated results, and usage time. Rewards and bonuses for users are determined based on this score.

[0159] Hosting a contest

[0160] The server will announce the contest on the web platform and provide an environment where users can submit their own work. Users will compete against each other based on evaluation criteria, which may include practicality, creativity, and contribution to business performance, and the best work will be selected.

[0161] Specific examples

[0162] For example, if a marketing department user uses a generative AI model to create a catchphrase for a new product, they would enter the prompt "Please create a catchphrase for our new product." The generated result for this prompt would be "An innovative product that opens up the future." This series of operations is logged by the device and periodically sent to the server. The server then analyzes and classifies the data and visualizes it on a web platform. Finally, the server evaluates the results and determines compensation and bonuses.

[0163] As a result, this system provides a concrete means for effectively utilizing generative AI models across the entire company to improve operational efficiency and performance.

[0164] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0165] Step 1: Getting started with generative AI models

[0166] The user logs into the generative AI model's web interface using their own device. The input requires the user's employee ID and password. The output is an authenticated user session.

[0167] The user enters a prompt such as "Please create a catchphrase for our new product." The prompt becomes input data and is sent to the generative AI model.

[0168] Step 2: Handling prompts and retrieving generated content

[0169] The generative AI model analyzes the received prompt and generates the generated content using the appropriate algorithm. The input is the user's prompt, and the output is the generated content (e.g., "Innovative products that open up the future").

[0170] The device records this generated content along with a log containing prompts, usage time, and user ID, thereby accumulating usage data.

[0171] Step 3: Sending log data

[0172] The terminal sends log data to the server at regular intervals (for example, every 24 hours). The data sent is all collected log information. HTTPS is used as the appropriate communication protocol, and the data is encrypted.

[0173] The server receives this log data and stores it in storage. The input is the log data sent from the terminal, and the output is the data stored in secure storage.

[0174] Step 4: Analyze and categorize the data

[0175] The server analyzes the stored log data and classifies the prompt content into categories using natural language processing technology. The input is the log data, specifically the prompt text. The output is the data classified by category.

[0176] The server detects and, if necessary, removes duplicate prompts using a duplicate detection algorithm.

[0177] Step 5: Visualize the data

[0178] The server converts the organized data into graphs and charts and visualizes them on a web platform. The input is organized log data and the output is a visually easy-to-understand dashboard or report.

[0179] Users log in to the web platform and view other users' prompts and generated results, making it easy to search and view data.

[0180] Step 6: Evaluate usage

[0181] The server scores the user's performance in using the generated AI model based on usage data. The input is various usage data indicators (frequency of use, quality of generated content, usage time, etc.). The output is an evaluation score for each user.

[0182] Based on this evaluation score, the server calculates and determines the user's rewards and bonuses.

[0183] Step 7: Host a Contest

[0184] The server announces the contest on a web platform and provides an environment in which users can enter. The input is the contest information and entry conditions, and the output is an entry form that users can use to enter.

[0185] Users enter the contest by submitting their own generated content or prompts, and the output is that the submitted content is judged and ranked based on a set of evaluation criteria.

[0186] (Application example 1)

[0187] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0188] The present invention relates to a system that effectively utilizes generative AI tools across an entire company to improve business efficiency. Its purpose, in particular, is to efficiently control and support maintenance of automated machinery in factories. Conventional systems have difficulty not only collecting usage data of generative AI tools but also classifying and visualizing the data into appropriate categories. Furthermore, evaluating users' usage records and determining rewards are complex. Furthermore, conventional technologies have not been able to adequately address the need for actual business support using generative AI tools, particularly for improving the efficiency of the operation and maintenance of automated machinery in factories.

[0189] 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.

[0190] In this invention, the server includes: means for collecting usage data of the generating AI tool; means for transmitting the collected usage data to the server; means for storing the transmitted usage data in storage; means for analyzing and categorizing the stored usage data; means for visualizing the categorized usage data on a web platform; means for evaluating a user's usage history of the generating AI tool based on the usage data; means for determining a reward for the user based on the evaluation; means for holding a contest to promote usage history; means for efficiently supporting the control and maintenance procedures of automated machines in a factory using the generating AI tool; means for collecting log data including operation and maintenance records of the automated machines in the factory; and means for analyzing the operation logs of the automated machines in the factory and presenting optimal maintenance procedures. This makes it possible to appropriately collect, classify, and visualize the usage data of the generating AI tool, evaluate the user's usage history, and determine rewards. Furthermore, the generating AI tool can be used to efficiently support the control and maintenance procedures of automated machines in a factory.

[0191] A "generative AI tool" is an artificial intelligence technology that generates content or information based on a user-supplied natural language prompt.

[0192] “Usage Data” means information about the use of a generative AI tool, including prompts, generated content, duration of use, and user interactions.

[0193] A "server" is a computer system that provides the computational resources to receive, store, analyze, categorize, and visualize usage data.

[0194] "Storage" refers to a storage device for safely storing collected usage data and analysis results.

[0195] "Web Platform" means an internet-accessible web application that enables users to view and search the usage and results of the Generative AI Tools.

[0196] "Natural language processing technology" is a technology that aims to enable computers to understand and process human language, and is used for prompt analysis and categorization.

[0197] "Evaluation" refers to the activity of quantifying and measuring the performance of users of generative AI tools based on collected and analyzed usage data.

[0198] A "reward" is a monetary or non-monetary consideration given to a user depending on the evaluation result.

[0199] A "contest" is an event in which users compete with each other to generate content in response to a specific task, with the aim of promoting the use of generative AI tools.

[0200] "Automated machinery in factories" refers to robots and devices installed in factories that perform production tasks automatically.

[0201] "Control and maintenance procedures" are written procedures for safely and efficiently operating automated machinery and for regularly maintaining and inspecting it.

[0202] This invention is a system for effectively utilizing generative AI tools across an entire company, particularly for efficiently controlling and supporting the maintenance of automated machinery in factories. This system is composed of the following main components:

[0203] 1. Generative AI tools used by users

[0204] Users access generative AI tools and generate the necessary information and procedures by entering prompts in natural language.

[0205] For example, if a user inputs the prompt "Please tell me the routine maintenance procedures for a robot," the generative AI tool will generate the procedures and provide them to the user.

[0206] 2. User Device

[0207] This includes devices used by users such as smartphones, smart glasses, and head-mounted displays.

[0208] These devices provide an interface with generative AI tools and record user operation history and log data.

[0209] 3. Central Server

[0210] The central server is responsible for receiving, storing, analyzing, and classifying usage data sent from user terminals.

[0211] The server uses a programming language such as Python to interact with AI generation tools (e.g., OpenAI's GPT-3).

[0212] 4. Secure Storage

[0213] Secure storage (e.g., AWS S3) is used to safely store collected usage data and analysis results.

[0214] Data is encrypted using secure communication protocols (e.g. HTTPS).

[0215] 5. Web Platform

[0216] It is a web application accessible via the internet that allows users to view and search the usage and results of generated AI tools.

[0217] The platform also provides the ability to view other users' prompts and generated results.

[0218] 6. Categorizing and visualizing prompts

[0219] The server analyzes the collected usage data using natural language processing techniques and categorizes prompts.

[0220] The classified data is visualized on a web platform, allowing users to understand it intuitively.

[0221] 7. User evaluation and reward determination

[0222] The server evaluates the user's performance in using the generated AI tool based on the usage data and determines the user's reward based on the evaluation results.

[0223] For example, users who provide efficient maintenance procedures may be given high marks.

[0224] 8. Hosting a Contest

[0225] The server will host a contest on its web platform to recognize creative efforts using generative AI tools.

[0226] Users compete with other users with their proposals and solutions and are evaluated based on their results.

[0227] As a concrete example, if a user wants to learn the maintenance procedures for a robot in a factory, they input the prompt, "Please tell me the routine maintenance procedures for the robot." The generative AI tool generates procedures such as "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation," and returns them to the user. The operation logs are recorded on the device and sent to a central server for analysis and evaluation.

[0228] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0229] Step 1:

[0230] A user logs in to the generative AI tool and enters a prompt to obtain information and procedures. The input is the user's prompt (e.g., "Please tell me the routine maintenance procedures for the robot"), and the generative AI tool generates the necessary information based on this. The output is the generated content (e.g., "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation.").

[0231] Step 2:

[0232] The device records a log of user operations. The input includes the prompt text entered by the user and the content generated by the generative AI tool. The device records this information as a log and saves it along with metadata. The output is the recorded operation log.

[0233] Step 3:

[0234] The terminal periodically sends the collected log data to the server. The input is the operation log recorded on the terminal, which is sent to the server using an encrypted communication protocol (e.g., HTTPS). The output is the log data sent to the server.

[0235] Step 4:

[0236] The server stores the received log data in secure storage. The input is encrypted log data, which is decrypted and stored in secure storage. The output is the data stored in secure storage.

[0237] Step 5:

[0238] The server analyzes the stored log data and classifies the prompt content by category. The input is the log data stored in secure storage, and natural language processing technology is used to analyze and classify the prompts by category. The output is the data classified by category.

[0239] Step 6:

[0240] The server visualizes the organized data on a web platform. The input is data classified by category, which is converted into a format that can be displayed on the web platform. The output is data visualized on the web platform in a format that can be viewed by users.

[0241] Step 7:

[0242] The server evaluates the user's usage performance of the generated AI tool based on usage data. The input is data visualized on the web platform, and the evaluation algorithm quantifies the user's usage performance. The output is an evaluation score for each user.

[0243] Step 8:

[0244] The server determines the reward based on the user's rating score. The input is the rating score, and the reward amount and content are determined using a reward determination algorithm. The output is the user's reward information.

[0245] Step 9:

[0246] The server hosts a contest on a web platform to promote the use of generative AI tools. The input is user submission data, and the server evaluates the user's submission based on the contest's evaluation criteria. The output is the contest results and the user's evaluation.

[0247] Step 10:

[0248] The server publishes users' contest results on a web platform and provides prizes or additional rewards as needed. The input is the evaluated contest results, which are published appropriately and notified to users. The output is the published contest results and a notification to users.

[0249] 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.

[0250] This invention is a system for promoting the use of generative AI tools in business processes across the entire company, and also combines it with an emotion engine that recognizes user emotions. This allows for the collection of user emotion data, improving work efficiency and user motivation. The system of this invention consists of the following main components:

[0251] Generative AI Tools

[0252] User terminal

[0253] Central Server

[0254] Web Platform

[0255] Secure Storage

[0256] Emotion Engine

[0257] System Overview

[0258] This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on that. It also collects users' emotional data and reflects it in the evaluation to provide a comprehensive evaluation. The system aims to promote the use of generative AI tools and improve user motivation.

[0259] Program processing

[0260] 1. Collecting usage data of generative AI tools

[0261] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[0262] A generative AI tool processes the input prompts and returns generated content to the user.

[0263] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[0264] 2. Collecting Emotional Data

[0265] When a user uses the generative AI tool, emotional data is collected in real time using the built-in camera and microphone.

[0266] The emotion engine analyzes the user's facial expressions and tone of voice to detect their emotional state (e.g., stress, joy, excitement, etc.).

[0267] The device records the emotional data along with usage data of the generated AI tool.

[0268] 3. Transmission and storage of log data and emotional data

[0269] The terminal periodically transmits the collected log data and emotion data to the server.

[0270] The server stores the received data in secure storage.

[0271] 4. Data Analysis and Classification

[0272] The server analyzes the stored log data and emotion data.

[0273] The server uses natural language processing technology to automatically categorize the prompt content and associate it with emotional data.

[0274] It also simultaneously removes duplicate data and optimizes data.

[0275] 5. Data Visualization

[0276] The server then visualizes the organized data on a web platform.

[0277] It allows users to log in to a web platform and view and search other users' prompts, generation results, and sentiment data.

[0278] 6. Evaluation of usage history and emotional data

[0279] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[0280] The server calculates a score for each user based on the evaluation criteria, and also reflects emotional data in the overall evaluation.

[0281] 7. Determination of Remuneration

[0282] The server determines the user's reward or bonus based on the evaluation score calculated.

[0283] The server notifies the evaluation score and reward determination on the web platform.

[0284] 8. Hosting a Contest

[0285] The server announces the use case contest on the web platform.

[0286] Users submit their work to the contest.

[0287] The server evaluates the submitted practical applications and also refers to emotional data to determine the winners.

[0288] Specific examples

[0289] Specific examples are shown below.

[0290] 1. Use of generative AI tools

[0291] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[0292] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[0293] The device will log this operation.

[0294] 2. Collecting Emotional Data

[0295] While the user is using the generative AI tool, the emotion engine collects the user's facial expression data and detects the emotion of joy.

[0296] The device records this emotion data together with the log data.

[0297] 3. Transmission and storage of log data and emotional data

[0298] The device periodically sends log data and emotion data to the server.

[0299] The server receives the data and stores it in storage.

[0300] 4. Data Analysis and Classification

[0301] The server categorizes the prompt into a "marketing" category, associates sentiment data with it, and reflects it in a database.

[0302] 5. Visualization and Evaluation

[0303] Users can access the web platform to view other marketing-related prompts, their generated results, and sentiment data.

[0304] The server evaluates the user's activity and determines the reward for the next year, taking into account their emotional data.

[0305] As described above, the system of the present invention promotes the use of generative AI tools throughout the company, and by taking emotional data into account, it performs more comprehensive evaluations, thereby improving motivation and work efficiency.

[0306] The processing flow will be explained below.

[0307] Step 1: Use generative AI tools

[0308] A user logs in to the generative AI tool.

[0309] A user enters a prompt into a generative AI tool (e.g., "Please create a tagline for our new product").

[0310] A generative AI tool processes the input prompt and returns generated content (e.g., "Innovative products that open up the future") to the user.

[0311] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[0312] Step 2: Collecting emotion data

[0313] While you are using the generative AI tool, it uses your camera and microphone to analyze your facial expressions and tone of voice.

[0314] The emotion engine recognizes the user's facial expressions and voice to detect their emotional state (e.g., joy, excitement, stress).

[0315] The device records the detected emotion data as a log.

[0316] Step 3: Sending log data and emotion data

[0317] The device periodically sends the collected log data and emotion data to a server. The data is sent in encrypted form using a secure communication protocol (e.g., HTTPS).

[0318] Step 4: Receiving and storing data

[0319] The server receives the log data and emotion data sent from the terminal.

[0320] The server decompresses the received log data and emotion data and stores them in secure storage.

[0321] The server creates indexes to eliminate data redundancy and enable efficient searching.

[0322] Step 5: Analyze and classify the data

[0323] The server analyzes the stored log data and emotion data.

[0324] The server uses natural language processing technology to automatically categorize the prompt content (e.g., "Marketing," "Technical Documentation," etc.).

[0325] The server associates the emotional data with the prompt and generated content.

[0326] Duplicate data is also detected and removed at the same time.

[0327] Step 6: Visualize the data

[0328] The server organizes and classifies the log data and emotion data, which are then visualized on a web platform.

[0329] Users can log in to the platform and view and search other users' prompts, generated results, and sentiment data.

[0330] Step 7: Evaluate usage and sentiment data

[0331] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[0332] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, emotional control, etc.).

[0333] Step 8: Determine the reward

[0334] The server determines the user's rewards and bonuses based on the evaluation score.

[0335] The server notifies the user of the evaluation results and reward details through the web platform.

[0336] Step 9: Host a Contest

[0337] The server announces the use case contest on the web platform.

[0338] Users submit their efforts to the contest, which includes performance and emotion data generated by the generative AI tool.

[0339] The server evaluates the submitted practical applications and also refers to the emotional data to determine the winners.

[0340] As described above, the system of the present invention promotes the use of generative AI tools in business operations throughout the company, performs comprehensive evaluations by taking into account user emotional data, and aims to improve business efficiency and user motivation.

[0341] Example 2

[0342] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0343] Conventional systems for collecting usage data on generative AI tools evaluate users based on their frequency of use and the results of their generation, but do not take into account the user's emotional state. This has resulted in problems such as insufficient reflection of the user's actual satisfaction and motivation. Furthermore, it is difficult to determine rewards based on the evaluation results or provide appropriate feedback to promote usage, resulting in limitations on improving work efficiency and user motivation.

[0344] 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.

[0345] In this invention, the server includes means for collecting usage data of the generation AI tool, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for collecting user emotional data, means for analyzing the collected emotional data to detect the emotional state, means for analyzing the stored usage data and emotional data and classifying them by category, means for visualizing the classified usage data and emotional data on a web platform, means for evaluating the user's usage performance of the generation AI tool based on the usage data and emotional data, means for determining the user's reward based on the evaluation, and means for holding contests to promote usage performance. This enables comprehensive evaluation that takes the user's emotional state into consideration, thereby improving work efficiency and user motivation.

[0346] A "generative AI tool" is an artificial intelligence system that analyzes prompts entered by users and generates specific content.

[0347] "Usage data" refers to information about the use of the generative AI tool, specifically metadata including prompt text, generated results, usage time, usage date and time, user ID, etc.

[0348] "Emotion data" is data that represents the user's emotional state, and is analyzed from the user's facial expressions and tone of voice collected using a camera or microphone.

[0349] A "server" is a central computer system that receives, stores, and analyzes data sent from the terminals.

[0350] "Storage" refers to a data storage device for safely storing usage data and emotion data collected by the server.

[0351] A "web platform" is an online system that users can access via the Internet and that provides data visualization and search functions.

[0352] An "emotion engine" is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state.

[0353] The "evaluation score" is the user's overall evaluation value calculated based on the usage data and emotional data of the generation AI tool.

[0354] "Rewards" are monetary or other incentives awarded to users based on their rating scores.

[0355] A "contest" is a competition or awards event held based on users' performance in using the AI ​​generation tool.

[0356] This invention is a system that promotes the use of generative AI tools in business processes across the entire company. By combining it with an emotion engine that recognizes users' emotions, it collects user emotion data and improves work efficiency and user motivation. The system of this invention consists of the following main components:

[0357] Generative AI Tools

[0358] User terminal

[0359] Central Server

[0360] Web Platform

[0361] Secure Storage

[0362] Emotion Engine

[0363] This system collects, analyzes, and classifies usage data and emotional data from the generative AI tool to comprehensively evaluate users' usage performance and determine rewards and bonuses based on that data. Contests will also be held to promote usage performance. Specific implementation methods are described in detail below.

[0364] Hardware and Software Configuration

[0365] User terminal

[0366] This is a device that allows users to access and use generative AI tools. The device has a built-in camera and microphone, and is equipped with hardware for collecting emotional data.

[0367] Generative AI Tools

[0368] A generative AI tool is an artificial intelligence system that analyzes prompts entered by users and generates specific content. As a specific example of its use, if the prompt is "Please create a catchphrase for a new product," the generated result will be "An innovative product that opens up the future."

[0369] Central Server

[0370] The server is a computer system that receives, analyzes, and stores usage data and emotion data sent from the devices. The server is equipped with an analysis system that uses natural language processing technology to classify and evaluate the data.

[0371] Secure Storage

[0372] The storage is a data storage device for safely storing the usage data and emotion data received by the server, and is equipped with security measures such as access control and encryption.

[0373] Web Platform

[0374] The web platform is an online system that users can access via the Internet and use data visualization and search functions. On this platform, users can view other users' prompts, generated results, and emotion data.

[0375] Emotion Engine

[0376] An emotion engine is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state. It detects emotional states such as stress, joy, and excitement in real time and collects them as data on the device.

[0377] Specific examples

[0378] Use of generative AI tools

[0379] A user uses a generative AI tool to create a catchphrase for a new product in the marketing department. The user enters "Please create a catchphrase for our new product" as the prompt, and the generated result is "An innovative product that will open up the future." The device records a log of this operation and saves details such as the user ID, prompt, generated result, usage time, and usage date and time.

[0380] Collecting Emotional Data

[0381] While the user is using the generative AI tool, the built-in camera captures the user's facial expressions and the microphone records the tone of voice. The emotion engine analyzes this data in real time to detect emotions such as joy. The device records this emotion data along with the log data.

[0382] Data transmission and storage

[0383] The device periodically collects log data and emotional data and sends it to a server, which then stores the received data in secure storage and applies access control and encryption.

[0384] Data analysis and classification

[0385] The server analyzes the stored log data and sentiment data, and uses natural language processing technology to categorize prompts and associate sentiment data with them, such as marketing, technical support, and product development.

[0386] Data Visualization

[0387] The server displays the organized data on a web platform dashboard, where users can log in and view prompts, results, and sentiment data in the "Marketing" category, filtering for the information they need.

[0388] Evaluation of usage history and emotional data

[0389] The server analyzes the data of all users and calculates an evaluation score based on the frequency of use, the quality of the generated results, the positivity of the emotional data, etc. Based on this score, the server notifies each user of the evaluation result.

[0390] Determining compensation

[0391] The server determines the amount of rewards and bonuses for each user based on the evaluation score, and notifies the user of the details of the determined rewards and bonuses on the web platform dashboard.

[0392] Hosting a contest

[0393] The server announces the "Practical Case Contest" on the web platform. Users enter the necessary information into the application form and submit it with their own efforts attached. The server evaluates all applications, incorporating emotional data into the evaluation criteria, and determines the winners. The results are announced on the web platform, and the winners are notified.

[0394] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0395] Step 1:

[0396] The user logs into the generative AI tool and enters a prompt.

[0397] Input: User ID, prompt

[0398] Specific operation: The user enters their ID and password to log in to the generation AI tool. The prompt text is "Please create a catchphrase for our new product."

[0399] Output: Logged in to the generation AI tool, and the prompt entered

[0400] Step 2:

[0401] The generative AI tool processes the input prompt sentence and produces a generated result.

[0402] Input: prompt statement

[0403] Specific operation: The generative AI tool analyzes the prompt sentence and generates the generated result, "An innovative product that opens up the future."

[0404] Output: Generated result

[0405] Step 3:

[0406] The device records usage data of the generated AI tool.

[0407] Input: User ID, prompt, generated result, usage time, usage date and time

[0408] Specific operation: The terminal records detailed logs such as the user ID, prompt text, generated results, usage time, and usage date and time.

[0409] Output: Recorded usage data

[0410] Step 4:

[0411] While the user is using the generative AI tool, the device's camera and microphone collect emotional data.

[0412] Input: User's facial expression, tone of voice

[0413] Specific operations: The camera captures the user's facial expressions and the microphone records the tone of voice.

[0414] Output: Collected emotion data

[0415] Step 5:

[0416] The emotion engine analyzes the collected emotion data to detect the emotional state.

[0417] Input: Emotion data

[0418] Specific operation: The emotion engine analyzes collected facial expression data and tone of voice to detect emotional states such as joy, stress, and excitement.

[0419] Output: Detected emotional state

[0420] Step 6:

[0421] The terminal transmits the log data and the emotion data to the server.

[0422] Input: Log data, emotion data

[0423] Specific operation: The terminal periodically sends the collected log data and emotion data to the server.

[0424] Output: Data sent to the server

[0425] Step 7:

[0426] The server stores the received data in secure storage.

[0427] Input: Log data, emotion data

[0428] Specific operation: The server stores the received log data and emotion data in storage. Access control and encryption are applied.

[0429] Output: Saved data

[0430] Step 8:

[0431] The server analyzes the stored data, categorizes the prompts, and associates them with emotion data.

[0432] Input: Saved log data, emotion data

[0433] How it works: The server uses natural language processing technology to analyze the prompt and classify it into categories such as marketing, technical support, product development, etc. It also associates sentiment data.

[0434] Output: Categorized and linked data

[0435] Step 9:

[0436] The server then visualizes the organized data on a web platform.

[0437] Input: Categorized and linked data

[0438] What it does: The server displays the data in a dashboard, allowing users to log in and search / view it.

[0439] Output: visualized data

[0440] Step 10:

[0441] The server analyzes the usage data and emotion data of all users and calculates an evaluation score.

[0442] Input: Categorized and linked data

[0443] Specific operation: Based on the data, the server evaluates the frequency of use, the quality of the generated results, the positivity of the emotional data, etc., and calculates a score.

[0444] Output: Evaluation score

[0445] Step 11:

[0446] The server determines and notifies the user of rewards and bonuses based on the evaluation score.

[0447] Input: Rating score

[0448] Specific operation: The server determines rewards and bonuses based on the evaluation score and notifies the user on the web platform.

[0449] Output: Reward and bonus notification

[0450] Step 12:

[0451] The server will announce the practical application case contest on the web platform, accept applications from users, and evaluate and notify the results.

[0452] Input: Application information from the user

[0453] Specific operation: The server announces the contest, accepts user applications, evaluates the applications, incorporates emotional data into the evaluation criteria, and determines the winners. The results are published on the web platform, and the winners are notified.

[0454] Output: Contest results

[0455] (Application example 2)

[0456] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0457] Conventional generative AI tool systems lacked a means to efficiently evaluate user usage performance, and the criteria for promoting usage and determining rewards were unclear. Furthermore, there was no means to incorporate emotional data to improve user motivation and service quality. Furthermore, when dealing with customers, it was difficult to grasp their emotions in real time and provide appropriate services accordingly.

[0458] 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.

[0459] In this invention, the server includes a means for collecting usage data of the generative AI tool, a means for collecting user emotion data using an emotion engine, and a means for analyzing the customer's emotional state in real time and using that information to propose appropriate services. By integrating both the usage data and the emotion data for evaluation, it becomes possible to more accurately reflect the user's usage performance of the generative AI tool and to determine rewards and propose response methods.

[0460] A "generative AI tool" is an artificial intelligence system that automatically generates content or information based on text prompts entered by a user.

[0461] "Usage Data" means data about the usage of the Generative AI Tools, including prompts, generated content, duration of usage, user ID, and other metadata.

[0462] The "emotion engine" is a system that analyzes the user's facial expressions and voice to detect their emotional state in real time.

[0463] A "server" is a data processing system that analyzes and stores collected data and provides feedback to users.

[0464] "Storage" refers to a storage device used by a server to store data.

[0465] A "web platform" is an online system that users can access through a browser and view and manipulate information.

[0466] A "prompt" is text data used as input to a generative AI tool.

[0467] The "evaluation score" is a numerical value calculated based on collected data that evaluates a user's performance in using the generated AI tool.

[0468] A "reward" is a monetary or non-monetary incentive provided to a user based on their rating score.

[0469] "Real-time" means that the system processes and analyzes data and provides results almost immediately.

[0470] "Service proposal" is the act of providing information indicating the optimal response method to users and staff based on the analysis results.

[0471] The system of this invention collects usage data and emotion data from the generative AI tool, analyzes and evaluates them, and determines appropriate rewards. It also uses the emotion data to propose services to customers in real time. This system consists of the following main components: the generative AI tool, user terminal, server, web platform, storage, and emotion engine.

[0472] Overall structure

[0473] Generative AI tools: Artificial intelligence systems that generate content or information based on text prompts entered by the user.

[0474] User device: An interface for using generative AI tools and emotion engines on devices such as smartphones and PCs.

[0475] Server: The central system that analyzes and stores data.

[0476] Web platform: An online system that users access through a browser to view and manipulate data.

[0477] Storage: A storage device where a server stores data persistently.

[0478] Emotion engine: A system that analyzes the user's emotional state in real time.

[0479] Data collection and analysis

[0480] When a user device operates the AI ​​tool, usage data is automatically collected, including prompts, generated content, usage time, and user ID. This data is periodically sent to a server and stored in storage.

[0481] The emotion engine analyzes the user's facial expressions and voice to collect emotional data such as joy, sadness, and anger. For example, while the user is using the generative AI tool, the facial expressions and voice are collected via a camera and microphone, and then analyzed by the emotion engine. The analysis results are sent to the server along with the usage data and displayed on the portal.

[0482] Re-proposal and evaluation

[0483] The server uses natural language processing technology to categorize the received data, and then visualizes the categorized data on a web platform, allowing users and administrators to easily view and analyze usage history and sentiment data.

[0484] Service proposal and compensation determination

[0485] For example, a user device inputs a prompt to the generative AI tool, saying, "It has been detected that the customer is angry. Please suggest how to provide service." The generative AI tool generates an appropriate response in real time and displays a suggestion such as, "Apologize politely in a calm tone, and then make a specific suggestion to resolve the problem." This suggestion is presented to the user via the device.

[0486] The server calculates a fair and reliable evaluation score based on the entire data and determines the user's reward. The evaluation score includes usage data and emotion data, and more accurately reflects the user's experience using the AI ​​tool.

[0487] This system will promote the use of generative AI tools throughout the company, thereby increasing user motivation and improving work efficiency.

[0488] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0489] Step 1:

[0490] The device operates the generative AI tool. The user inputs a prompt (e.g., "It has been detected that the customer is angry. Please suggest how to provide service.") into the generative AI tool, which then receives the generated content. Based on the input text data (prompt), the generative AI tool performs natural language processing and generates an appropriate response. The output is the generated content, a suggestion sentence (e.g., "Please apologize politely in a calm tone, and then make a specific suggestion to resolve the problem.").

[0491] Step 2:

[0492] The device collects usage data of the generated AI tool. The collected data includes prompts, generated content, usage time, user ID, etc. This data is temporarily stored on the device and later sent to a server for processing. The input is the data generated by the user's operations, and the output is the stored usage data.

[0493] Step 3:

[0494] The device collects the user's emotional data. The emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone to detect their emotional state (e.g., joy, sadness, anger, etc.). The input is the user's facial expression images and voice data, and the output is the analyzed emotional data.

[0495] Step 4:

[0496] The device periodically collects usage data and emotion data and sends it to the server. The data is securely transmitted over the network and reaches the server. The input is the usage data and emotion data stored on the device, and the output is the data sent to the server.

[0497] Step 5:

[0498] The server stores the received data in secure storage. It records usage data and emotion data in an appropriate format while ensuring data integrity and safety. The input is the data that arrives at the server, and the output is the stored data.

[0499] Step 6:

[0500] The server analyzes the stored data and classifies it into categories. It uses natural language processing technology to automatically classify prompts and associate them with emotional data. The input is the stored usage data and emotional data, and the output is the classified data.

[0501] Step 7:

[0502] The server visualizes the organized data on a web platform, allowing users to view and search the data through their browsers. The input is the classified data, and the output is a user-accessible data visualization.

[0503] Step 8:

[0504] The server evaluates the user's performance in using the AI ​​tool based on usage data and emotion data. This evaluation calculates a score for each user and determines a reward based on the evaluation criteria. The input is usage data and emotion data, and the output is an evaluation score and a reward based on that decision.

[0505] Step 9:

[0506] The server notifies the evaluation score and reward determination on the web platform. Users can check the evaluation results and reward details by logging in to the web platform. The input is the evaluation score and reward information, and the output is a web interface that notifies them.

[0507] 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.

[0508] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0509] 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.

[0510] [Second embodiment]

[0511] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0512] 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.

[0513] 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).

[0514] 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.

[0515] 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.

[0516] 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).

[0517] 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.

[0518] 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.

[0519] 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.

[0520] 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.

[0521] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0522] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0523] This invention relates to a system for promoting the use of generative AI tools throughout a company. This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on the results. It also holds contests to promote usage.

[0524] System Overview

[0525] The system consists of the following main components:

[0526] Generative AI tools used by users

[0527] User terminal

[0528] Central Server

[0529] Web Platform

[0530] Secure Storage

[0531] Program processing

[0532] 1. Collecting usage data of generative AI tools

[0533] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[0534] A generative AI tool processes the input prompts and returns generated content to the user.

[0535] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[0536] 2. Transmission and storage of log data

[0537] The terminal periodically sends the collected log data to the server.

[0538] The server stores the received log data in secure storage, where the data is encrypted using a secure communication protocol (e.g., HTTPS).

[0539] 3. Data Analysis and Classification

[0540] The server analyzes the stored log data and automatically categorizes the prompt content using natural language processing technology.

[0541] Duplicate prompts are detected and removed as needed, ensuring only the necessary data is ultimately saved to the database.

[0542] 4. Data Visualization

[0543] The server visualizes the organized data on a web platform, making it accessible and viewable by users.

[0544] Users can log in to the platform and view and search other users' prompts and generated results.

[0545] 5. Evaluation of usage record

[0546] The server evaluates each user's performance in using the generated AI tool based on usage data, converting the evaluation into a score and measuring the efficiency and contribution to business performance.

[0547] Based on this score, the server determines the user's rewards and bonuses.

[0548] 6. Hosting a Contest

[0549] The server announces the practical application example contest on the web platform and provides an environment in which users can apply.

[0550] Users can submit their own efforts and compete against other users, with evaluation criteria including practicality, creativity, and contribution to business performance.

[0551] Specific examples

[0552] Specific examples are shown below.

[0553] 1. Use of generative AI tools

[0554] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[0555] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[0556] The device will log this operation.

[0557] 2. Transmission and storage of log data

[0558] The terminal periodically sends log data to the server.

[0559] The server receives the data and stores it in storage.

[0560] 3. Data Analysis and Classification

[0561] The server categorizes the prompt into the "Marketing" category and reflects it in the database.

[0562] 4. Visualization and Evaluation

[0563] The user may access a web platform to view other marketing-related prompts and their generated results.

[0564] The server also evaluates the user's activity and determines the reward for the next year.

[0565] As described above, the system of the present invention provides a concrete means for effectively utilizing generative AI tools throughout the company to achieve efficiency and improved performance.

[0566] The processing flow will be explained below.

[0567] Step 1: Use generative AI tools

[0568] A user logs in to the generative AI tool.

[0569] The user enters a prompt into the generative AI tool (e.g., "Please create a tagline for our new product").

[0570] A generative AI tool processes the input prompts and returns generated content (e.g., innovative products that open up the future) to the user.

[0571] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[0572] Step 2: Sending log data

[0573] The terminal sends the collected log data to the server at regular intervals (e.g., every hour).

[0574] The transmission is done in encrypted form using a secure communication protocol (e.g. HTTPS).

[0575] Step 3: Receiving and storing log data

[0576] The server receives the log data sent from the terminal.

[0577] The server decompresses the received log data and stores it in secure storage.

[0578] The server creates indexes to eliminate data redundancy and enable efficient searching.

[0579] Step 4: Analyze and classify the data

[0580] The server analyzes the stored log data.

[0581] The server uses natural language processing technology to automatically categorize the prompt content into categories (e.g., "Marketing," "Technical Documentation," etc.).

[0582] The server identifies and removes duplicate prompts, creating an optimized database.

[0583] Step 5: Visualize the data

[0584] The server classifies and organizes the log data, which is then visualized on a web platform.

[0585] Allows users to log in to a web platform to browse and search categorized prompts and generated results.

[0586] Step 6: Evaluate usage

[0587] The server evaluates the user's usage performance of the generated AI tool based on the usage data.

[0588] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, etc.).

[0589] Step 7: Determine the reward

[0590] The server determines the user's reward or bonus based on the evaluation score calculated.

[0591] The server notifies the evaluation score and reward determination on the web platform.

[0592] Step 8: Host a Contest

[0593] The server announces the use case contest on the web platform.

[0594] Users submit their work to the contest.

[0595] The server will evaluate the submitted practical applications and determine the winners.

[0596] This is the specific process flow of the invention. This system promotes the use of generative AI tools throughout the company, allowing for efficient data management and improved user motivation.

[0597] Example 1

[0598] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0599] With conventional generative AI models, it has been difficult to effectively evaluate each user's usage and the quality of the generated content, leading to improvements in company-wide operational efficiency. Fair and transparent standards are also needed for evaluating usage performance and determining compensation. Furthermore, there has been a lack of mechanisms for users to share their generated results with each other and a system for promoting performance.

[0600] 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.

[0601] In this invention, the server includes means for collecting usage data of the generative AI model, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for analyzing and categorizing the stored usage data, means for visualizing the categorized usage data on a web platform, means for evaluating users' usage performance of the generative AI model based on the usage data, means for determining user rewards based on the evaluation, means for holding contests to promote usage performance, means for encrypting the collected usage data using a secure communication protocol, means for recording generated content and its prompts as metadata, means for automatically detecting and deleting duplicate prompts, and means for searching and viewing prompts and results generated by users. This enables effective and fair evaluation of business use of the generative AI model, improving company-wide business efficiency, and enabling users to share results.

[0602] A "generative AI model" is a type of computer program that uses artificial intelligence to generate new data or content based on input data.

[0603] A "prompt" refers to textual instructions or requests that a user enters into a generative AI model.

[0604] "Usage Data" means data including log information, prompts, generated content, and associated metadata related to the use of a Generative AI Model.

[0605] A "server" is a computer system that processes, stores, and manages data on a network.

[0606] "Storage" is a data storage device or system for persistently storing data.

[0607] "Web Platform" means a web-based software application for providing data visualization, sharing, and access over the Internet.

[0608] "Analysis" is the process of taking log data and generated content and evaluating and categorizing the data based on specific rules and algorithms.

[0609] "Metadata" is data that includes attribute and descriptive information associated with prompts and generated content.

[0610] A "secure communication protocol" is a communication protocol for encrypting and safely transmitting and receiving data, and examples include HTTPS.

[0611] "Duplicate prompts" refer to identical or very similar instruction or request text.

[0612] "Evaluation" is the process of quantitatively or qualitatively assessing the performance of generative AI models and the quality of the content they generate.

[0613] A "contest" is an event in which user-generated content or prompts are compared based on specific criteria, and the best submissions are selected and rewarded or awarded.

[0614] "Rewards" are incentives such as money or goods given to users based on the evaluation results.

[0615] This invention relates to a system for promoting the business use of generative AI models across the entire company. This system collects, analyzes, and classifies usage data of generative AI models, evaluates user usage performance, and determines rewards based on the results. It also includes a function to hold contests to promote usage.

[0616] System configuration

[0617] The system consists of the following main components:

[0618] Generative AI models used by users

[0619] User terminal

[0620] Central Server

[0621] Web Platform

[0622] Secure Storage

[0623] Collecting usage data for generative AI models

[0624] The user logs in to the generative AI model and inputs a prompt. For example, the user might input a prompt such as, "Please create a catchphrase for a new product." This prompt is processed by the generative AI model, which generates an "innovative product that will open up the future" and returns it to the user. The device records this series of operations as a log. The log includes the prompt, the generation result, the usage time, the user ID, etc.

[0625] Sending and storing log data

[0626] The terminal periodically sends the collected log data to the server. The data is sent in encrypted form using a secure communication protocol such as HTTPS. The server then stores the received log data in secure storage.

[0627] Data analysis and classification

[0628] The server analyzes the stored log data. This analysis uses natural language processing technology to extract keywords for each prompt. It then automatically classifies prompts into categories such as "Marketing" or "Finance" based on the extracted keywords. Duplicate prompts are detected and deleted as necessary.

[0629] Data Visualization

[0630] The server visualizes the organized data on a web platform. Users can view and search other users' prompts and generated results by logging in to the web platform. A visually easy-to-understand dashboard is provided, displaying data by category.

[0631] Evaluation of usage history

[0632] The server evaluates the user's performance in using the generated AI model based on usage data. This evaluation is scored using indicators such as frequency of use, quality of generated results, and usage time. Rewards and bonuses for users are determined based on this score.

[0633] Hosting a contest

[0634] The server will announce the contest on the web platform and provide an environment where users can submit their own work. Users will compete against each other based on evaluation criteria, which may include practicality, creativity, and contribution to business performance, and the best work will be selected.

[0635] Specific examples

[0636] For example, if a marketing department user uses a generative AI model to create a catchphrase for a new product, they would enter the prompt "Please create a catchphrase for our new product." The generated result for this prompt would be "An innovative product that opens up the future." This series of operations is logged by the device and periodically sent to the server. The server then analyzes and classifies the data and visualizes it on a web platform. Finally, the server evaluates the results and determines compensation and bonuses.

[0637] As a result, this system provides a concrete means for effectively utilizing generative AI models across the entire company to improve operational efficiency and performance.

[0638] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0639] Step 1: Getting started with generative AI models

[0640] The user logs into the generative AI model's web interface using their own device. The input requires the user's employee ID and password. The output is an authenticated user session.

[0641] The user enters a prompt such as "Please create a catchphrase for our new product." The prompt becomes input data and is sent to the generative AI model.

[0642] Step 2: Handling prompts and retrieving generated content

[0643] The generative AI model analyzes the received prompt and generates the generated content using the appropriate algorithm. The input is the user's prompt, and the output is the generated content (e.g., "Innovative products that open up the future").

[0644] The device records this generated content along with a log containing prompts, usage time, and user ID, thereby accumulating usage data.

[0645] Step 3: Sending log data

[0646] The terminal sends log data to the server at regular intervals (for example, every 24 hours). The data sent is all collected log information. HTTPS is used as the appropriate communication protocol, and the data is encrypted.

[0647] The server receives this log data and stores it in storage. The input is the log data sent from the terminal, and the output is the data stored in secure storage.

[0648] Step 4: Analyze and categorize the data

[0649] The server analyzes the stored log data and classifies the prompt content into categories using natural language processing technology. The input is the log data, specifically the prompt text. The output is the data classified by category.

[0650] The server detects and, if necessary, removes duplicate prompts using a duplicate detection algorithm.

[0651] Step 5: Visualize the data

[0652] The server converts the organized data into graphs and charts and visualizes them on a web platform. The input is organized log data and the output is a visually easy-to-understand dashboard or report.

[0653] Users log in to the web platform and view other users' prompts and generated results, making it easy to search and view data.

[0654] Step 6: Evaluate usage

[0655] The server scores the user's performance in using the generated AI model based on usage data. The input is various usage data indicators (frequency of use, quality of generated content, usage time, etc.). The output is an evaluation score for each user.

[0656] Based on this evaluation score, the server calculates and determines the user's rewards and bonuses.

[0657] Step 7: Host a Contest

[0658] The server announces the contest on a web platform and provides an environment in which users can enter. The input is the contest information and entry conditions, and the output is an entry form that users can use to enter.

[0659] Users enter the contest by submitting their own generated content or prompts, and the output is that the submitted content is judged and ranked based on a set of evaluation criteria.

[0660] (Application example 1)

[0661] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0662] The present invention relates to a system that effectively utilizes generative AI tools across an entire company to improve business efficiency. Its purpose, in particular, is to efficiently control and support maintenance of automated machinery in factories. Conventional systems have difficulty not only collecting usage data of generative AI tools but also classifying and visualizing the data into appropriate categories. Furthermore, evaluating users' usage records and determining rewards are complex. Furthermore, conventional technologies have not been able to adequately address the need for actual business support using generative AI tools, particularly for improving the efficiency of the operation and maintenance of automated machinery in factories.

[0663] 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.

[0664] In this invention, the server includes: means for collecting usage data of the generating AI tool; means for transmitting the collected usage data to the server; means for storing the transmitted usage data in storage; means for analyzing and categorizing the stored usage data; means for visualizing the categorized usage data on a web platform; means for evaluating a user's usage history of the generating AI tool based on the usage data; means for determining a reward for the user based on the evaluation; means for holding a contest to promote usage history; means for efficiently supporting the control and maintenance procedures of automated machines in a factory using the generating AI tool; means for collecting log data including operation and maintenance records of the automated machines in the factory; and means for analyzing the operation logs of the automated machines in the factory and presenting optimal maintenance procedures. This makes it possible to appropriately collect, classify, and visualize the usage data of the generating AI tool, evaluate the user's usage history, and determine rewards. Furthermore, the generating AI tool can be used to efficiently support the control and maintenance procedures of automated machines in a factory.

[0665] A "generative AI tool" is an artificial intelligence technology that generates content or information based on a user-supplied natural language prompt.

[0666] “Usage Data” means information about the use of a generative AI tool, including prompts, generated content, duration of use, and user interactions.

[0667] A "server" is a computer system that provides the computational resources to receive, store, analyze, categorize, and visualize usage data.

[0668] "Storage" refers to a storage device for safely storing collected usage data and analysis results.

[0669] "Web Platform" means an internet-accessible web application that enables users to view and search the usage and results of the Generative AI Tools.

[0670] "Natural language processing technology" is a technology that aims to enable computers to understand and process human language, and is used for prompt analysis and categorization.

[0671] "Evaluation" refers to the activity of quantifying and measuring the performance of users of generative AI tools based on collected and analyzed usage data.

[0672] A "reward" is a monetary or non-monetary consideration given to a user depending on the evaluation result.

[0673] A "contest" is an event in which users compete with each other to generate content in response to a specific task, with the aim of promoting the use of generative AI tools.

[0674] "Automated machinery in factories" refers to robots and devices installed in factories that perform production tasks automatically.

[0675] "Control and maintenance procedures" are written procedures for safely and efficiently operating automated machinery and for regularly maintaining and inspecting it.

[0676] This invention is a system for effectively utilizing generative AI tools across an entire company, particularly for efficiently controlling and supporting the maintenance of automated machinery in factories. This system is composed of the following main components:

[0677] 1. Generative AI tools used by users

[0678] Users access generative AI tools and generate the necessary information and procedures by entering prompts in natural language.

[0679] For example, if a user inputs the prompt "Please tell me the routine maintenance procedures for a robot," the generative AI tool will generate the procedures and provide them to the user.

[0680] 2. User Device

[0681] This includes devices used by users such as smartphones, smart glasses, and head-mounted displays.

[0682] These devices provide an interface with generative AI tools and record user operation history and log data.

[0683] 3. Central Server

[0684] The central server is responsible for receiving, storing, analyzing, and classifying usage data sent from user terminals.

[0685] The server uses a programming language such as Python to interact with AI generation tools (e.g., OpenAI's GPT-3).

[0686] 4. Secure Storage

[0687] Secure storage (e.g., AWS S3) is used to safely store collected usage data and analysis results.

[0688] Data is encrypted using secure communication protocols (e.g. HTTPS).

[0689] 5. Web Platform

[0690] It is a web application accessible via the internet that allows users to view and search the usage and results of generated AI tools.

[0691] The platform also provides the ability to view other users' prompts and generated results.

[0692] 6. Categorizing and visualizing prompts

[0693] The server analyzes the collected usage data using natural language processing techniques and categorizes prompts.

[0694] The classified data is visualized on a web platform, allowing users to understand it intuitively.

[0695] 7. User evaluation and reward determination

[0696] The server evaluates the user's performance in using the generated AI tool based on the usage data and determines the user's reward based on the evaluation results.

[0697] For example, users who provide efficient maintenance procedures may be given high marks.

[0698] 8. Hosting a Contest

[0699] The server will host a contest on its web platform to recognize creative efforts using generative AI tools.

[0700] Users compete with other users with their proposals and solutions and are evaluated based on their results.

[0701] As a concrete example, if a user wants to learn the maintenance procedures for a robot in a factory, they input the prompt, "Please tell me the routine maintenance procedures for the robot." The generative AI tool generates procedures such as "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation," and returns them to the user. The operation logs are recorded on the device and sent to a central server for analysis and evaluation.

[0702] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0703] Step 1:

[0704] A user logs in to the generative AI tool and enters a prompt to obtain information and procedures. The input is the user's prompt (e.g., "Please tell me the routine maintenance procedures for the robot"), and the generative AI tool generates the necessary information based on this. The output is the generated content (e.g., "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation.").

[0705] Step 2:

[0706] The device records a log of user operations. The input includes the prompt text entered by the user and the content generated by the generative AI tool. The device records this information as a log and saves it along with metadata. The output is the recorded operation log.

[0707] Step 3:

[0708] The terminal periodically sends the collected log data to the server. The input is the operation log recorded on the terminal, which is sent to the server using an encrypted communication protocol (e.g., HTTPS). The output is the log data sent to the server.

[0709] Step 4:

[0710] The server stores the received log data in secure storage. The input is encrypted log data, which is decrypted and stored in secure storage. The output is the data stored in secure storage.

[0711] Step 5:

[0712] The server analyzes the stored log data and classifies the prompt content by category. The input is the log data stored in secure storage, and natural language processing technology is used to analyze and classify the prompts by category. The output is the data classified by category.

[0713] Step 6:

[0714] The server visualizes the organized data on a web platform. The input is data classified by category, which is converted into a format that can be displayed on the web platform. The output is data visualized on the web platform in a format that can be viewed by users.

[0715] Step 7:

[0716] The server evaluates the user's usage performance of the generated AI tool based on usage data. The input is data visualized on the web platform, and the evaluation algorithm quantifies the user's usage performance. The output is an evaluation score for each user.

[0717] Step 8:

[0718] The server determines the reward based on the user's rating score. The input is the rating score, and the reward amount and content are determined using a reward determination algorithm. The output is the user's reward information.

[0719] Step 9:

[0720] The server hosts a contest on a web platform to promote the use of generative AI tools. The input is user submission data, and the server evaluates the user's submission based on the contest's evaluation criteria. The output is the contest results and the user's evaluation.

[0721] Step 10:

[0722] The server publishes users' contest results on a web platform and provides prizes or additional rewards as needed. The input is the evaluated contest results, which are published appropriately and notified to users. The output is the published contest results and a notification to users.

[0723] 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.

[0724] This invention is a system for promoting the use of generative AI tools in business processes across the entire company, and also combines it with an emotion engine that recognizes user emotions. This allows for the collection of user emotion data, improving work efficiency and user motivation. The system of this invention consists of the following main components:

[0725] Generative AI Tools

[0726] User terminal

[0727] Central Server

[0728] Web Platform

[0729] Secure Storage

[0730] Emotion Engine

[0731] System Overview

[0732] This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on that. It also collects users' emotional data and reflects it in the evaluation to provide a comprehensive evaluation. The system aims to promote the use of generative AI tools and improve user motivation.

[0733] Program processing

[0734] 1. Collecting usage data of generative AI tools

[0735] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[0736] A generative AI tool processes the input prompts and returns generated content to the user.

[0737] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[0738] 2. Collecting Emotional Data

[0739] When a user uses the generative AI tool, emotional data is collected in real time using the built-in camera and microphone.

[0740] The emotion engine analyzes the user's facial expressions and tone of voice to detect their emotional state (e.g., stress, joy, excitement, etc.).

[0741] The device records the emotional data along with usage data of the generated AI tool.

[0742] 3. Transmission and storage of log data and emotional data

[0743] The terminal periodically transmits the collected log data and emotion data to the server.

[0744] The server stores the received data in secure storage.

[0745] 4. Data Analysis and Classification

[0746] The server analyzes the stored log data and emotion data.

[0747] The server uses natural language processing technology to automatically categorize the prompt content and associate it with emotional data.

[0748] It also simultaneously removes duplicate data and optimizes data.

[0749] 5. Data Visualization

[0750] The server then visualizes the organized data on a web platform.

[0751] It allows users to log in to a web platform and view and search other users' prompts, generation results, and sentiment data.

[0752] 6. Evaluation of usage history and emotional data

[0753] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[0754] The server calculates a score for each user based on the evaluation criteria, and also reflects emotional data in the overall evaluation.

[0755] 7. Determination of Remuneration

[0756] The server determines the user's reward or bonus based on the evaluation score calculated.

[0757] The server notifies the evaluation score and reward determination on the web platform.

[0758] 8. Hosting a Contest

[0759] The server announces the use case contest on the web platform.

[0760] Users submit their work to the contest.

[0761] The server evaluates the submitted practical applications and also refers to emotional data to determine the winners.

[0762] Specific examples

[0763] Specific examples are shown below.

[0764] 1. Use of generative AI tools

[0765] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[0766] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[0767] The device will log this operation.

[0768] 2. Collecting Emotional Data

[0769] While the user is using the generative AI tool, the emotion engine collects the user's facial expression data and detects the emotion of joy.

[0770] The device records this emotion data together with the log data.

[0771] 3. Transmission and storage of log data and emotional data

[0772] The device periodically sends log data and emotion data to the server.

[0773] The server receives the data and stores it in storage.

[0774] 4. Data Analysis and Classification

[0775] The server categorizes the prompt into a "marketing" category, associates sentiment data with it, and reflects it in a database.

[0776] 5. Visualization and Evaluation

[0777] Users can access the web platform to view other marketing-related prompts, their generated results, and sentiment data.

[0778] The server evaluates the user's activity and determines the reward for the next year, taking into account their emotional data.

[0779] As described above, the system of the present invention promotes the use of generative AI tools throughout the company, and by taking emotional data into account, it performs more comprehensive evaluations, thereby improving motivation and work efficiency.

[0780] The processing flow will be explained below.

[0781] Step 1: Use generative AI tools

[0782] A user logs in to the generative AI tool.

[0783] A user enters a prompt into a generative AI tool (e.g., "Please create a tagline for our new product").

[0784] A generative AI tool processes the input prompt and returns generated content (e.g., "Innovative products that open up the future") to the user.

[0785] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[0786] Step 2: Collecting emotion data

[0787] While you are using the generative AI tool, it uses your camera and microphone to analyze your facial expressions and tone of voice.

[0788] The emotion engine recognizes the user's facial expressions and voice to detect their emotional state (e.g., joy, excitement, stress).

[0789] The device records the detected emotion data as a log.

[0790] Step 3: Sending log data and emotion data

[0791] The device periodically sends the collected log data and emotion data to a server. The data is sent in encrypted form using a secure communication protocol (e.g., HTTPS).

[0792] Step 4: Receiving and storing data

[0793] The server receives the log data and emotion data sent from the terminal.

[0794] The server decompresses the received log data and emotion data and stores them in secure storage.

[0795] The server creates indexes to eliminate data redundancy and enable efficient searching.

[0796] Step 5: Analyze and classify the data

[0797] The server analyzes the stored log data and emotion data.

[0798] The server uses natural language processing technology to automatically categorize the prompt content (e.g., "Marketing," "Technical Documentation," etc.).

[0799] The server associates the emotional data with the prompt and generated content.

[0800] Duplicate data is also detected and removed at the same time.

[0801] Step 6: Visualize the data

[0802] The server organizes and classifies the log data and emotion data, which are then visualized on a web platform.

[0803] Users can log in to the platform and view and search other users' prompts, generated results, and sentiment data.

[0804] Step 7: Evaluate usage and sentiment data

[0805] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[0806] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, emotional control, etc.).

[0807] Step 8: Determine the reward

[0808] The server determines the user's rewards and bonuses based on the evaluation score.

[0809] The server notifies the user of the evaluation results and reward details through the web platform.

[0810] Step 9: Host a Contest

[0811] The server announces the use case contest on the web platform.

[0812] Users submit their efforts to the contest, which includes performance and emotion data generated by the generative AI tool.

[0813] The server evaluates the submitted practical applications and also refers to the emotional data to determine the winners.

[0814] As described above, the system of the present invention promotes the use of generative AI tools in business operations throughout the company, performs comprehensive evaluations by taking into account user emotional data, and aims to improve business efficiency and user motivation.

[0815] Example 2

[0816] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0817] Conventional systems for collecting usage data on generative AI tools evaluate users based on their frequency of use and the results of their generation, but do not take into account the user's emotional state. This has resulted in problems such as insufficient reflection of the user's actual satisfaction and motivation. Furthermore, it is difficult to determine rewards based on the evaluation results or provide appropriate feedback to promote usage, resulting in limitations on improving work efficiency and user motivation.

[0818] 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.

[0819] In this invention, the server includes means for collecting usage data of the generation AI tool, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for collecting user emotional data, means for analyzing the collected emotional data to detect the emotional state, means for analyzing the stored usage data and emotional data and classifying them by category, means for visualizing the classified usage data and emotional data on a web platform, means for evaluating the user's usage performance of the generation AI tool based on the usage data and emotional data, means for determining the user's reward based on the evaluation, and means for holding contests to promote usage performance. This enables comprehensive evaluation that takes the user's emotional state into consideration, thereby improving work efficiency and user motivation.

[0820] A "generative AI tool" is an artificial intelligence system that analyzes prompts entered by users and generates specific content.

[0821] "Usage data" refers to information about the use of the generative AI tool, specifically metadata including prompt text, generated results, usage time, usage date and time, user ID, etc.

[0822] "Emotion data" is data that represents the user's emotional state, and is analyzed from the user's facial expressions and tone of voice collected using a camera or microphone.

[0823] A "server" is a central computer system that receives, stores, and analyzes data sent from the terminals.

[0824] "Storage" refers to a data storage device for safely storing usage data and emotion data collected by the server.

[0825] A "web platform" is an online system that users can access via the Internet and that provides data visualization and search functions.

[0826] An "emotion engine" is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state.

[0827] The "evaluation score" is the user's overall evaluation value calculated based on the usage data and emotional data of the generation AI tool.

[0828] "Rewards" are monetary or other incentives awarded to users based on their rating scores.

[0829] A "contest" is a competition or awards event held based on users' performance in using the AI ​​generation tool.

[0830] This invention is a system that promotes the use of generative AI tools in business processes across the entire company. By combining it with an emotion engine that recognizes users' emotions, it collects user emotion data and improves work efficiency and user motivation. The system of this invention consists of the following main components:

[0831] Generative AI Tools

[0832] User terminal

[0833] Central Server

[0834] Web Platform

[0835] Secure Storage

[0836] Emotion Engine

[0837] This system collects, analyzes, and classifies usage data and emotional data from the generative AI tool to comprehensively evaluate users' usage performance and determine rewards and bonuses based on that data. Contests will also be held to promote usage performance. Specific implementation methods are described in detail below.

[0838] Hardware and Software Configuration

[0839] User terminal

[0840] This is a device that allows users to access and use generative AI tools. The device has a built-in camera and microphone, and is equipped with hardware for collecting emotional data.

[0841] Generative AI Tools

[0842] A generative AI tool is an artificial intelligence system that analyzes prompts entered by users and generates specific content. As a specific example of its use, if the prompt is "Please create a catchphrase for a new product," the generated result will be "An innovative product that opens up the future."

[0843] Central Server

[0844] The server is a computer system that receives, analyzes, and stores usage data and emotion data sent from the devices. The server is equipped with an analysis system that uses natural language processing technology to classify and evaluate the data.

[0845] Secure Storage

[0846] The storage is a data storage device for safely storing the usage data and emotion data received by the server, and is equipped with security measures such as access control and encryption.

[0847] Web Platform

[0848] The web platform is an online system that users can access via the Internet and use data visualization and search functions. On this platform, users can view other users' prompts, generated results, and emotion data.

[0849] Emotion Engine

[0850] An emotion engine is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state. It detects emotional states such as stress, joy, and excitement in real time and collects them as data on the device.

[0851] Specific examples

[0852] Use of generative AI tools

[0853] A user uses a generative AI tool to create a catchphrase for a new product in the marketing department. The user enters "Please create a catchphrase for our new product" as the prompt, and the generated result is "An innovative product that will open up the future." The device records a log of this operation and saves details such as the user ID, prompt, generated result, usage time, and usage date and time.

[0854] Collecting Emotional Data

[0855] While the user is using the generative AI tool, the built-in camera captures the user's facial expressions and the microphone records the tone of voice. The emotion engine analyzes this data in real time to detect emotions such as joy. The device records this emotion data along with the log data.

[0856] Data transmission and storage

[0857] The device periodically collects log data and emotional data and sends it to a server, which then stores the received data in secure storage and applies access control and encryption.

[0858] Data analysis and classification

[0859] The server analyzes the stored log data and sentiment data, and uses natural language processing technology to categorize prompts and associate sentiment data with them, such as marketing, technical support, and product development.

[0860] Data Visualization

[0861] The server displays the organized data on a web platform dashboard, where users can log in and view prompts, results, and sentiment data in the "Marketing" category, filtering for the information they need.

[0862] Evaluation of usage history and emotional data

[0863] The server analyzes the data of all users and calculates an evaluation score based on the frequency of use, the quality of the generated results, the positivity of the emotional data, etc. Based on this score, the server notifies each user of the evaluation result.

[0864] Determining compensation

[0865] The server determines the amount of rewards and bonuses for each user based on the evaluation score, and notifies the user of the details of the determined rewards and bonuses on the web platform dashboard.

[0866] Hosting a contest

[0867] The server announces the "Practical Case Contest" on the web platform. Users enter the necessary information into the application form and submit it with their own efforts attached. The server evaluates all applications, incorporating emotional data into the evaluation criteria, and determines the winners. The results are announced on the web platform, and the winners are notified.

[0868] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0869] Step 1:

[0870] The user logs into the generative AI tool and enters a prompt.

[0871] Input: User ID, prompt

[0872] Specific operation: The user enters their ID and password to log in to the generation AI tool. The prompt text is "Please create a catchphrase for our new product."

[0873] Output: Logged in to the generation AI tool, and the prompt entered

[0874] Step 2:

[0875] The generative AI tool processes the input prompt sentence and produces a generated result.

[0876] Input: prompt statement

[0877] Specific operation: The generative AI tool analyzes the prompt sentence and generates the generated result, "An innovative product that opens up the future."

[0878] Output: Generated result

[0879] Step 3:

[0880] The device records usage data of the generated AI tool.

[0881] Input: User ID, prompt, generated result, usage time, usage date and time

[0882] Specific operation: The terminal records detailed logs such as the user ID, prompt text, generated results, usage time, and usage date and time.

[0883] Output: Recorded usage data

[0884] Step 4:

[0885] While the user is using the generative AI tool, the device's camera and microphone collect emotional data.

[0886] Input: User's facial expression, tone of voice

[0887] Specific operations: The camera captures the user's facial expressions and the microphone records the tone of voice.

[0888] Output: Collected emotion data

[0889] Step 5:

[0890] The emotion engine analyzes the collected emotion data to detect the emotional state.

[0891] Input: Emotion data

[0892] Specific operation: The emotion engine analyzes collected facial expression data and tone of voice to detect emotional states such as joy, stress, and excitement.

[0893] Output: Detected emotional state

[0894] Step 6:

[0895] The terminal transmits the log data and the emotion data to the server.

[0896] Input: Log data, emotion data

[0897] Specific operation: The terminal periodically sends the collected log data and emotion data to the server.

[0898] Output: Data sent to the server

[0899] Step 7:

[0900] The server stores the received data in secure storage.

[0901] Input: Log data, emotion data

[0902] Specific operation: The server stores the received log data and emotion data in storage. Access control and encryption are applied.

[0903] Output: Saved data

[0904] Step 8:

[0905] The server analyzes the stored data, categorizes the prompts, and associates them with emotion data.

[0906] Input: Saved log data, emotion data

[0907] How it works: The server uses natural language processing technology to analyze the prompt and classify it into categories such as marketing, technical support, product development, etc. It also associates sentiment data.

[0908] Output: Categorized and linked data

[0909] Step 9:

[0910] The server then visualizes the organized data on a web platform.

[0911] Input: Categorized and linked data

[0912] What it does: The server displays the data in a dashboard, allowing users to log in and search / view it.

[0913] Output: visualized data

[0914] Step 10:

[0915] The server analyzes the usage data and emotion data of all users and calculates an evaluation score.

[0916] Input: Categorized and linked data

[0917] Specific operation: Based on the data, the server evaluates the frequency of use, the quality of the generated results, the positivity of the emotional data, etc., and calculates a score.

[0918] Output: Evaluation score

[0919] Step 11:

[0920] The server determines and notifies the user of rewards and bonuses based on the evaluation score.

[0921] Input: Rating score

[0922] Specific operation: The server determines rewards and bonuses based on the evaluation score and notifies the user on the web platform.

[0923] Output: Reward and bonus notification

[0924] Step 12:

[0925] The server will announce the practical application case contest on the web platform, accept applications from users, and evaluate and notify the results.

[0926] Input: Application information from the user

[0927] Specific operation: The server announces the contest, accepts user applications, evaluates the applications, incorporates emotional data into the evaluation criteria, and determines the winners. The results are published on the web platform, and the winners are notified.

[0928] Output: Contest results

[0929] (Application example 2)

[0930] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0931] Conventional generative AI tool systems lacked a means to efficiently evaluate user usage performance, and the criteria for promoting usage and determining rewards were unclear. Furthermore, there was no means to incorporate emotional data to improve user motivation and service quality. Furthermore, when dealing with customers, it was difficult to grasp their emotions in real time and provide appropriate services accordingly.

[0932] 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.

[0933] In this invention, the server includes a means for collecting usage data of the generative AI tool, a means for collecting user emotion data using an emotion engine, and a means for analyzing the customer's emotional state in real time and using that information to propose appropriate services. By integrating both the usage data and the emotion data for evaluation, it becomes possible to more accurately reflect the user's usage performance of the generative AI tool and to determine rewards and propose response methods.

[0934] A "generative AI tool" is an artificial intelligence system that automatically generates content or information based on text prompts entered by a user.

[0935] "Usage Data" means data about the usage of the Generative AI Tools, including prompts, generated content, duration of usage, user ID, and other metadata.

[0936] The "emotion engine" is a system that analyzes the user's facial expressions and voice to detect their emotional state in real time.

[0937] A "server" is a data processing system that analyzes and stores collected data and provides feedback to users.

[0938] "Storage" refers to a storage device used by a server to store data.

[0939] A "web platform" is an online system that users can access through a browser and view and manipulate information.

[0940] A "prompt" is text data used as input to a generative AI tool.

[0941] The "evaluation score" is a numerical value calculated based on collected data that evaluates a user's performance in using the generated AI tool.

[0942] A "reward" is a monetary or non-monetary incentive provided to a user based on their rating score.

[0943] "Real-time" means that the system processes and analyzes data and provides results almost immediately.

[0944] "Service proposal" is the act of providing information indicating the optimal response method to users and staff based on the analysis results.

[0945] The system of this invention collects usage data and emotion data from the generative AI tool, analyzes and evaluates them, and determines appropriate rewards. It also uses the emotion data to propose services to customers in real time. This system consists of the following main components: the generative AI tool, user terminal, server, web platform, storage, and emotion engine.

[0946] Overall structure

[0947] Generative AI tools: Artificial intelligence systems that generate content or information based on text prompts entered by the user.

[0948] User device: An interface for using generative AI tools and emotion engines on devices such as smartphones and PCs.

[0949] Server: The central system that analyzes and stores data.

[0950] Web platform: An online system that users access through a browser to view and manipulate data.

[0951] Storage: A storage device where a server stores data persistently.

[0952] Emotion engine: A system that analyzes the user's emotional state in real time.

[0953] Data collection and analysis

[0954] When a user device operates the AI ​​tool, usage data is automatically collected, including prompts, generated content, usage time, and user ID. This data is periodically sent to a server and stored in storage.

[0955] The emotion engine analyzes the user's facial expressions and voice to collect emotional data such as joy, sadness, and anger. For example, while the user is using the generative AI tool, the facial expressions and voice are collected via a camera and microphone, and then analyzed by the emotion engine. The analysis results are sent to the server along with the usage data and displayed on the portal.

[0956] Re-proposal and evaluation

[0957] The server uses natural language processing technology to categorize the received data, and then visualizes the categorized data on a web platform, allowing users and administrators to easily view and analyze usage history and sentiment data.

[0958] Service proposal and compensation determination

[0959] For example, a user device inputs a prompt to the generative AI tool, saying, "It has been detected that the customer is angry. Please suggest how to provide service." The generative AI tool generates an appropriate response in real time and displays a suggestion such as, "Apologize politely in a calm tone, and then make a specific suggestion to resolve the problem." This suggestion is presented to the user via the device.

[0960] The server calculates a fair and reliable evaluation score based on the entire data and determines the user's reward. The evaluation score includes usage data and emotion data, and more accurately reflects the user's experience using the AI ​​tool.

[0961] This system will promote the use of generative AI tools throughout the company, thereby increasing user motivation and improving work efficiency.

[0962] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0963] Step 1:

[0964] The device operates the generative AI tool. The user inputs a prompt (e.g., "It has been detected that the customer is angry. Please suggest how to provide service.") into the generative AI tool, which then receives the generated content. Based on the input text data (prompt), the generative AI tool performs natural language processing and generates an appropriate response. The output is the generated content, a suggestion sentence (e.g., "Please apologize politely in a calm tone, and then make a specific suggestion to resolve the problem.").

[0965] Step 2:

[0966] The device collects usage data of the generated AI tool. The collected data includes prompts, generated content, usage time, user ID, etc. This data is temporarily stored on the device and later sent to a server for processing. The input is the data generated by the user's operations, and the output is the stored usage data.

[0967] Step 3:

[0968] The device collects the user's emotional data. The emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone to detect their emotional state (e.g., joy, sadness, anger, etc.). The input is the user's facial expression images and voice data, and the output is the analyzed emotional data.

[0969] Step 4:

[0970] The device periodically collects usage data and emotion data and sends it to the server. The data is securely transmitted over the network and reaches the server. The input is the usage data and emotion data stored on the device, and the output is the data sent to the server.

[0971] Step 5:

[0972] The server stores the received data in secure storage. It records usage data and emotion data in an appropriate format while ensuring data integrity and safety. The input is the data that arrives at the server, and the output is the stored data.

[0973] Step 6:

[0974] The server analyzes the stored data and classifies it into categories. It uses natural language processing technology to automatically classify prompts and associate them with emotional data. The input is the stored usage data and emotional data, and the output is the classified data.

[0975] Step 7:

[0976] The server visualizes the organized data on a web platform, allowing users to view and search the data through their browsers. The input is the classified data, and the output is a user-accessible data visualization.

[0977] Step 8:

[0978] The server evaluates the user's performance in using the AI ​​tool based on usage data and emotion data. This evaluation calculates a score for each user and determines a reward based on the evaluation criteria. The input is usage data and emotion data, and the output is an evaluation score and a reward based on that decision.

[0979] Step 9:

[0980] The server notifies the evaluation score and reward determination on the web platform. Users can check the evaluation results and reward details by logging in to the web platform. The input is the evaluation score and reward information, and the output is a web interface that notifies them.

[0981] 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.

[0982] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0983] 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.

[0984] [Third embodiment]

[0985] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0986] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0987] 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).

[0988] 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.

[0989] 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.

[0990] 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).

[0991] 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.

[0992] 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.

[0993] 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.

[0994] 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.

[0995] 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.

[0996] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0997] This invention relates to a system for promoting the use of generative AI tools throughout a company. This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on the results. It also holds contests to promote usage.

[0998] System Overview

[0999] The system consists of the following main components:

[1000] Generative AI tools used by users

[1001] User terminal

[1002] Central Server

[1003] Web Platform

[1004] Secure Storage

[1005] Program processing

[1006] 1. Collecting usage data of generative AI tools

[1007] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[1008] A generative AI tool processes the input prompts and returns generated content to the user.

[1009] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[1010] 2. Transmission and storage of log data

[1011] The terminal periodically sends the collected log data to the server.

[1012] The server stores the received log data in secure storage, where the data is encrypted using a secure communication protocol (e.g., HTTPS).

[1013] 3. Data Analysis and Classification

[1014] The server analyzes the stored log data and automatically categorizes the prompt content using natural language processing technology.

[1015] Duplicate prompts are detected and removed as needed, ensuring only the necessary data is ultimately saved to the database.

[1016] 4. Data Visualization

[1017] The server visualizes the organized data on a web platform, making it accessible and viewable by users.

[1018] Users can log in to the platform and view and search other users' prompts and generated results.

[1019] 5. Evaluation of usage record

[1020] The server evaluates each user's performance in using the generated AI tool based on usage data, converting the evaluation into a score and measuring the efficiency and contribution to business performance.

[1021] Based on this score, the server determines the user's rewards and bonuses.

[1022] 6. Hosting a Contest

[1023] The server announces the practical application example contest on the web platform and provides an environment in which users can apply.

[1024] Users can submit their own efforts and compete against other users, with evaluation criteria including practicality, creativity, and contribution to business performance.

[1025] Specific examples

[1026] Specific examples are shown below.

[1027] 1. Use of generative AI tools

[1028] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[1029] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[1030] The device will log this operation.

[1031] 2. Transmission and storage of log data

[1032] The terminal periodically sends log data to the server.

[1033] The server receives the data and stores it in storage.

[1034] 3. Data Analysis and Classification

[1035] The server categorizes the prompt into the "Marketing" category and reflects it in the database.

[1036] 4. Visualization and Evaluation

[1037] The user may access a web platform to view other marketing-related prompts and their generated results.

[1038] The server also evaluates the user's activity and determines the reward for the next year.

[1039] As described above, the system of the present invention provides a concrete means for effectively utilizing generative AI tools throughout the company to achieve efficiency and improved performance.

[1040] The processing flow will be explained below.

[1041] Step 1: Use generative AI tools

[1042] A user logs in to the generative AI tool.

[1043] The user enters a prompt into the generative AI tool (e.g., "Please create a tagline for our new product").

[1044] A generative AI tool processes the input prompts and returns generated content (e.g., innovative products that open up the future) to the user.

[1045] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[1046] Step 2: Sending log data

[1047] The terminal sends the collected log data to the server at regular intervals (e.g., every hour).

[1048] The transmission is done in encrypted form using a secure communication protocol (e.g. HTTPS).

[1049] Step 3: Receiving and storing log data

[1050] The server receives the log data sent from the terminal.

[1051] The server decompresses the received log data and stores it in secure storage.

[1052] The server creates indexes to eliminate data redundancy and enable efficient searching.

[1053] Step 4: Analyze and classify the data

[1054] The server analyzes the stored log data.

[1055] The server uses natural language processing technology to automatically categorize the prompt content into categories (e.g., "Marketing," "Technical Documentation," etc.).

[1056] The server identifies and removes duplicate prompts, creating an optimized database.

[1057] Step 5: Visualize the data

[1058] The server classifies and organizes the log data, which is then visualized on a web platform.

[1059] Allows users to log in to a web platform to browse and search categorized prompts and generated results.

[1060] Step 6: Evaluate usage

[1061] The server evaluates the user's usage performance of the generated AI tool based on the usage data.

[1062] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, etc.).

[1063] Step 7: Determine the reward

[1064] The server determines the user's reward or bonus based on the evaluation score calculated.

[1065] The server notifies the evaluation score and reward determination on the web platform.

[1066] Step 8: Host a Contest

[1067] The server announces the use case contest on the web platform.

[1068] Users submit their work to the contest.

[1069] The server will evaluate the submitted practical applications and determine the winners.

[1070] This is the specific process flow of the invention. This system promotes the use of generative AI tools throughout the company, allowing for efficient data management and improved user motivation.

[1071] Example 1

[1072] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1073] With conventional generative AI models, it has been difficult to effectively evaluate each user's usage and the quality of the generated content, leading to improvements in company-wide operational efficiency. Fair and transparent standards are also needed for evaluating usage performance and determining compensation. Furthermore, there has been a lack of mechanisms for users to share their generated results with each other and a system for promoting performance.

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

[1075] In this invention, the server includes means for collecting usage data of the generative AI model, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for analyzing and categorizing the stored usage data, means for visualizing the categorized usage data on a web platform, means for evaluating users' usage performance of the generative AI model based on the usage data, means for determining user rewards based on the evaluation, means for holding contests to promote usage performance, means for encrypting the collected usage data using a secure communication protocol, means for recording generated content and its prompts as metadata, means for automatically detecting and deleting duplicate prompts, and means for searching and viewing prompts and results generated by users. This enables effective and fair evaluation of business use of the generative AI model, improving company-wide business efficiency, and enabling users to share results.

[1076] A "generative AI model" is a type of computer program that uses artificial intelligence to generate new data or content based on input data.

[1077] A "prompt" refers to textual instructions or requests that a user enters into a generative AI model.

[1078] "Usage Data" means data including log information, prompts, generated content, and associated metadata related to the use of a Generative AI Model.

[1079] A "server" is a computer system that processes, stores, and manages data on a network.

[1080] "Storage" is a data storage device or system for persistently storing data.

[1081] "Web Platform" means a web-based software application for providing data visualization, sharing, and access over the Internet.

[1082] "Analysis" is the process of taking log data and generated content and evaluating and categorizing the data based on specific rules and algorithms.

[1083] "Metadata" is data that includes attribute and descriptive information associated with prompts and generated content.

[1084] A "secure communication protocol" is a communication protocol for encrypting and safely transmitting and receiving data, and examples include HTTPS.

[1085] "Duplicate prompts" refer to identical or very similar instruction or request text.

[1086] "Evaluation" is the process of quantitatively or qualitatively assessing the performance of generative AI models and the quality of the content they generate.

[1087] A "contest" is an event in which user-generated content or prompts are compared based on specific criteria, and the best submissions are selected and rewarded or awarded.

[1088] "Rewards" are incentives such as money or goods given to users based on the evaluation results.

[1089] This invention relates to a system for promoting the business use of generative AI models across the entire company. This system collects, analyzes, and classifies usage data of generative AI models, evaluates user usage performance, and determines rewards based on the results. It also includes a function to hold contests to promote usage.

[1090] System configuration

[1091] The system consists of the following main components:

[1092] Generative AI models used by users

[1093] User terminal

[1094] Central Server

[1095] Web Platform

[1096] Secure Storage

[1097] Collecting usage data for generative AI models

[1098] The user logs in to the generative AI model and inputs a prompt. For example, the user might input a prompt such as, "Please create a catchphrase for a new product." This prompt is processed by the generative AI model, which generates an "innovative product that will open up the future" and returns it to the user. The device records this series of operations as a log. The log includes the prompt, the generation result, the usage time, the user ID, etc.

[1099] Sending and storing log data

[1100] The terminal periodically sends the collected log data to the server. The data is sent in encrypted form using a secure communication protocol such as HTTPS. The server then stores the received log data in secure storage.

[1101] Data analysis and classification

[1102] The server analyzes the stored log data. This analysis uses natural language processing technology to extract keywords for each prompt. It then automatically classifies prompts into categories such as "Marketing" or "Finance" based on the extracted keywords. Duplicate prompts are detected and deleted as necessary.

[1103] Data Visualization

[1104] The server visualizes the organized data on a web platform. Users can view and search other users' prompts and generated results by logging in to the web platform. A visually easy-to-understand dashboard is provided, displaying data by category.

[1105] Evaluation of usage history

[1106] The server evaluates the user's performance in using the generated AI model based on usage data. This evaluation is scored using indicators such as frequency of use, quality of generated results, and usage time. Rewards and bonuses for users are determined based on this score.

[1107] Hosting a contest

[1108] The server will announce the contest on the web platform and provide an environment where users can submit their own work. Users will compete against each other based on evaluation criteria, which may include practicality, creativity, and contribution to business performance, and the best work will be selected.

[1109] Specific examples

[1110] For example, if a marketing department user uses a generative AI model to create a catchphrase for a new product, they would enter the prompt "Please create a catchphrase for our new product." The generated result for this prompt would be "An innovative product that opens up the future." This series of operations is logged by the device and periodically sent to the server. The server then analyzes and classifies the data and visualizes it on a web platform. Finally, the server evaluates the results and determines compensation and bonuses.

[1111] As a result, this system provides a concrete means for effectively utilizing generative AI models across the entire company to improve operational efficiency and performance.

[1112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1113] Step 1: Getting started with generative AI models

[1114] The user logs into the generative AI model's web interface using their own device. The input requires the user's employee ID and password. The output is an authenticated user session.

[1115] The user enters a prompt such as "Please create a catchphrase for our new product." The prompt becomes input data and is sent to the generative AI model.

[1116] Step 2: Handling prompts and retrieving generated content

[1117] The generative AI model analyzes the received prompt and generates the generated content using the appropriate algorithm. The input is the user's prompt, and the output is the generated content (e.g., "Innovative products that open up the future").

[1118] The device records this generated content along with a log containing prompts, usage time, and user ID, thereby accumulating usage data.

[1119] Step 3: Sending log data

[1120] The terminal sends log data to the server at regular intervals (for example, every 24 hours). The data sent is all collected log information. HTTPS is used as the appropriate communication protocol, and the data is encrypted.

[1121] The server receives this log data and stores it in storage. The input is the log data sent from the terminal, and the output is the data stored in secure storage.

[1122] Step 4: Analyze and categorize the data

[1123] The server analyzes the stored log data and classifies the prompt content into categories using natural language processing technology. The input is the log data, specifically the prompt text. The output is the data classified by category.

[1124] The server detects and, if necessary, removes duplicate prompts using a duplicate detection algorithm.

[1125] Step 5: Visualize the data

[1126] The server converts the organized data into graphs and charts and visualizes them on a web platform. The input is organized log data and the output is a visually easy-to-understand dashboard or report.

[1127] Users log in to the web platform and view other users' prompts and generated results, making it easy to search and view data.

[1128] Step 6: Evaluate usage

[1129] The server scores the user's performance in using the generated AI model based on usage data. The input is various usage data indicators (frequency of use, quality of generated content, usage time, etc.). The output is an evaluation score for each user.

[1130] Based on this evaluation score, the server calculates and determines the user's rewards and bonuses.

[1131] Step 7: Host a Contest

[1132] The server announces the contest on a web platform and provides an environment in which users can enter. The input is the contest information and entry conditions, and the output is an entry form that users can use to enter.

[1133] Users enter the contest by submitting their own generated content or prompts, and the output is that the submitted content is judged and ranked based on a set of evaluation criteria.

[1134] (Application example 1)

[1135] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1136] The present invention relates to a system that effectively utilizes generative AI tools across an entire company to improve business efficiency. Its purpose, in particular, is to efficiently control and support maintenance of automated machinery in factories. Conventional systems have difficulty not only collecting usage data of generative AI tools but also classifying and visualizing the data into appropriate categories. Furthermore, evaluating users' usage records and determining rewards are complex. Furthermore, conventional technologies have not been able to adequately address the need for actual business support using generative AI tools, particularly for improving the efficiency of the operation and maintenance of automated machinery in factories.

[1137] 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.

[1138] In this invention, the server includes: means for collecting usage data of the generating AI tool; means for transmitting the collected usage data to the server; means for storing the transmitted usage data in storage; means for analyzing and categorizing the stored usage data; means for visualizing the categorized usage data on a web platform; means for evaluating a user's usage history of the generating AI tool based on the usage data; means for determining a reward for the user based on the evaluation; means for holding a contest to promote usage history; means for efficiently supporting the control and maintenance procedures of automated machines in a factory using the generating AI tool; means for collecting log data including operation and maintenance records of the automated machines in the factory; and means for analyzing the operation logs of the automated machines in the factory and presenting optimal maintenance procedures. This makes it possible to appropriately collect, classify, and visualize the usage data of the generating AI tool, evaluate the user's usage history, and determine rewards. Furthermore, the generating AI tool can be used to efficiently support the control and maintenance procedures of automated machines in a factory.

[1139] A "generative AI tool" is an artificial intelligence technology that generates content or information based on a user-supplied natural language prompt.

[1140] “Usage Data” means information about the use of a generative AI tool, including prompts, generated content, duration of use, and user interactions.

[1141] A "server" is a computer system that provides the computational resources to receive, store, analyze, categorize, and visualize usage data.

[1142] "Storage" refers to a storage device for safely storing collected usage data and analysis results.

[1143] "Web Platform" means an internet-accessible web application that enables users to view and search the usage and results of the Generative AI Tools.

[1144] "Natural language processing technology" is a technology that aims to enable computers to understand and process human language, and is used for prompt analysis and categorization.

[1145] "Evaluation" refers to the activity of quantifying and measuring the performance of users of generative AI tools based on collected and analyzed usage data.

[1146] A "reward" is a monetary or non-monetary consideration given to a user depending on the evaluation result.

[1147] A "contest" is an event in which users compete with each other to generate content in response to a specific task, with the aim of promoting the use of generative AI tools.

[1148] "Automated machinery in factories" refers to robots and devices installed in factories that perform production tasks automatically.

[1149] "Control and maintenance procedures" are written procedures for safely and efficiently operating automated machinery and for regularly maintaining and inspecting it.

[1150] This invention is a system for effectively utilizing generative AI tools across an entire company, particularly for efficiently controlling and supporting the maintenance of automated machinery in factories. This system is composed of the following main components:

[1151] 1. Generative AI tools used by users

[1152] Users access generative AI tools and generate the necessary information and procedures by entering prompts in natural language.

[1153] For example, if a user inputs the prompt "Please tell me the routine maintenance procedures for a robot," the generative AI tool will generate the procedures and provide them to the user.

[1154] 2. User Device

[1155] This includes devices used by users such as smartphones, smart glasses, and head-mounted displays.

[1156] These devices provide an interface with generative AI tools and record user operation history and log data.

[1157] 3. Central Server

[1158] The central server is responsible for receiving, storing, analyzing, and classifying usage data sent from user terminals.

[1159] The server uses a programming language such as Python to interact with AI generation tools (e.g., OpenAI's GPT-3).

[1160] 4. Secure Storage

[1161] Secure storage (e.g., AWS S3) is used to safely store collected usage data and analysis results.

[1162] Data is encrypted using secure communication protocols (e.g. HTTPS).

[1163] 5. Web Platform

[1164] It is a web application accessible via the internet that allows users to view and search the usage and results of generated AI tools.

[1165] The platform also provides the ability to view other users' prompts and generated results.

[1166] 6. Categorizing and visualizing prompts

[1167] The server analyzes the collected usage data using natural language processing techniques and categorizes prompts.

[1168] The classified data is visualized on a web platform, allowing users to understand it intuitively.

[1169] 7. User evaluation and reward determination

[1170] The server evaluates the user's performance in using the generated AI tool based on the usage data and determines the user's reward based on the evaluation results.

[1171] For example, users who provide efficient maintenance procedures may be given high marks.

[1172] 8. Hosting a Contest

[1173] The server will host a contest on its web platform to recognize creative efforts using generative AI tools.

[1174] Users compete with other users with their proposals and solutions and are evaluated based on their results.

[1175] As a concrete example, if a user wants to learn the maintenance procedures for a robot in a factory, they input the prompt, "Please tell me the routine maintenance procedures for the robot." The generative AI tool generates procedures such as "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation," and returns them to the user. The operation logs are recorded on the device and sent to a central server for analysis and evaluation.

[1176] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1177] Step 1:

[1178] A user logs in to the generative AI tool and enters a prompt to obtain information and procedures. The input is the user's prompt (e.g., "Please tell me the routine maintenance procedures for the robot"), and the generative AI tool generates the necessary information based on this. The output is the generated content (e.g., "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation.").

[1179] Step 2:

[1180] The device records a log of user operations. The input includes the prompt text entered by the user and the content generated by the generative AI tool. The device records this information as a log and saves it along with metadata. The output is the recorded operation log.

[1181] Step 3:

[1182] The terminal periodically sends the collected log data to the server. The input is the operation log recorded on the terminal, which is sent to the server using an encrypted communication protocol (e.g., HTTPS). The output is the log data sent to the server.

[1183] Step 4:

[1184] The server stores the received log data in secure storage. The input is encrypted log data, which is decrypted and stored in secure storage. The output is the data stored in secure storage.

[1185] Step 5:

[1186] The server analyzes the stored log data and classifies the prompt content by category. The input is the log data stored in secure storage, and natural language processing technology is used to analyze and classify the prompts by category. The output is the data classified by category.

[1187] Step 6:

[1188] The server visualizes the organized data on a web platform. The input is data classified by category, which is converted into a format that can be displayed on the web platform. The output is data visualized on the web platform in a format that can be viewed by users.

[1189] Step 7:

[1190] The server evaluates the user's usage performance of the generated AI tool based on usage data. The input is data visualized on the web platform, and the evaluation algorithm quantifies the user's usage performance. The output is an evaluation score for each user.

[1191] Step 8:

[1192] The server determines the reward based on the user's rating score. The input is the rating score, and the reward amount and content are determined using a reward determination algorithm. The output is the user's reward information.

[1193] Step 9:

[1194] The server hosts a contest on a web platform to promote the use of generative AI tools. The input is user submission data, and the server evaluates the user's submission based on the contest's evaluation criteria. The output is the contest results and the user's evaluation.

[1195] Step 10:

[1196] The server publishes users' contest results on a web platform and provides prizes or additional rewards as needed. The input is the evaluated contest results, which are published appropriately and notified to users. The output is the published contest results and a notification to users.

[1197] 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.

[1198] This invention is a system for promoting the use of generative AI tools in business processes across the entire company, and also combines it with an emotion engine that recognizes user emotions. This allows for the collection of user emotion data, improving work efficiency and user motivation. The system of this invention consists of the following main components:

[1199] Generative AI Tools

[1200] User terminal

[1201] Central Server

[1202] Web Platform

[1203] Secure Storage

[1204] Emotion Engine

[1205] System Overview

[1206] This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on that. It also collects users' emotional data and reflects it in the evaluation to provide a comprehensive evaluation. The system aims to promote the use of generative AI tools and improve user motivation.

[1207] Program processing

[1208] 1. Collecting usage data of generative AI tools

[1209] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[1210] A generative AI tool processes the input prompts and returns generated content to the user.

[1211] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[1212] 2. Collecting Emotional Data

[1213] When a user uses the generative AI tool, emotional data is collected in real time using the built-in camera and microphone.

[1214] The emotion engine analyzes the user's facial expressions and tone of voice to detect their emotional state (e.g., stress, joy, excitement, etc.).

[1215] The device records the emotional data along with usage data of the generated AI tool.

[1216] 3. Transmission and storage of log data and emotional data

[1217] The terminal periodically transmits the collected log data and emotion data to the server.

[1218] The server stores the received data in secure storage.

[1219] 4. Data Analysis and Classification

[1220] The server analyzes the stored log data and emotion data.

[1221] The server uses natural language processing technology to automatically categorize the prompt content and associate it with emotional data.

[1222] It also simultaneously removes duplicate data and optimizes data.

[1223] 5. Data Visualization

[1224] The server then visualizes the organized data on a web platform.

[1225] It allows users to log in to a web platform and view and search other users' prompts, generation results, and sentiment data.

[1226] 6. Evaluation of usage history and emotional data

[1227] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[1228] The server calculates a score for each user based on the evaluation criteria, and also reflects emotional data in the overall evaluation.

[1229] 7. Determination of Remuneration

[1230] The server determines the user's reward or bonus based on the evaluation score calculated.

[1231] The server notifies the evaluation score and reward determination on the web platform.

[1232] 8. Hosting a Contest

[1233] The server announces the use case contest on the web platform.

[1234] Users submit their work to the contest.

[1235] The server evaluates the submitted practical applications and also refers to emotional data to determine the winners.

[1236] Specific examples

[1237] Specific examples are shown below.

[1238] 1. Use of generative AI tools

[1239] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[1240] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[1241] The device will log this operation.

[1242] 2. Collecting Emotional Data

[1243] While the user is using the generative AI tool, the emotion engine collects the user's facial expression data and detects the emotion of joy.

[1244] The device records this emotion data together with the log data.

[1245] 3. Transmission and storage of log data and emotional data

[1246] The device periodically sends log data and emotion data to the server.

[1247] The server receives the data and stores it in storage.

[1248] 4. Data Analysis and Classification

[1249] The server categorizes the prompt into a "marketing" category, associates sentiment data with it, and reflects it in a database.

[1250] 5. Visualization and Evaluation

[1251] Users can access the web platform to view other marketing-related prompts, their generated results, and sentiment data.

[1252] The server evaluates the user's activity and determines the reward for the next year, taking into account their emotional data.

[1253] As described above, the system of the present invention promotes the use of generative AI tools throughout the company, and by taking emotional data into account, it performs more comprehensive evaluations, thereby improving motivation and work efficiency.

[1254] The processing flow will be explained below.

[1255] Step 1: Use generative AI tools

[1256] A user logs in to the generative AI tool.

[1257] A user enters a prompt into a generative AI tool (e.g., "Please create a tagline for our new product").

[1258] A generative AI tool processes the input prompt and returns generated content (e.g., "Innovative products that open up the future") to the user.

[1259] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[1260] Step 2: Collecting emotion data

[1261] While you are using the generative AI tool, it uses your camera and microphone to analyze your facial expressions and tone of voice.

[1262] The emotion engine recognizes the user's facial expressions and voice to detect their emotional state (e.g., joy, excitement, stress).

[1263] The device records the detected emotion data as a log.

[1264] Step 3: Sending log data and emotion data

[1265] The device periodically sends the collected log data and emotion data to a server. The data is sent in encrypted form using a secure communication protocol (e.g., HTTPS).

[1266] Step 4: Receiving and storing data

[1267] The server receives the log data and emotion data sent from the terminal.

[1268] The server decompresses the received log data and emotion data and stores them in secure storage.

[1269] The server creates indexes to eliminate data redundancy and enable efficient searching.

[1270] Step 5: Analyze and classify the data

[1271] The server analyzes the stored log data and emotion data.

[1272] The server uses natural language processing technology to automatically categorize the prompt content (e.g., "Marketing," "Technical Documentation," etc.).

[1273] The server associates the emotional data with the prompt and generated content.

[1274] Duplicate data is also detected and removed at the same time.

[1275] Step 6: Visualize the data

[1276] The server organizes and classifies the log data and emotion data, which are then visualized on a web platform.

[1277] Users can log in to the platform and view and search other users' prompts, generated results, and sentiment data.

[1278] Step 7: Evaluate usage and sentiment data

[1279] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[1280] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, emotional control, etc.).

[1281] Step 8: Determine the reward

[1282] The server determines the user's rewards and bonuses based on the evaluation score.

[1283] The server notifies the user of the evaluation results and reward details through the web platform.

[1284] Step 9: Host a Contest

[1285] The server announces the use case contest on the web platform.

[1286] Users submit their efforts to the contest, which includes performance and emotion data generated by the generative AI tool.

[1287] The server evaluates the submitted practical applications and also refers to the emotional data to determine the winners.

[1288] As described above, the system of the present invention promotes the use of generative AI tools in business operations throughout the company, performs comprehensive evaluations by taking into account user emotional data, and aims to improve business efficiency and user motivation.

[1289] Example 2

[1290] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1291] Conventional systems for collecting usage data on generative AI tools evaluate users based on their frequency of use and the results of their generation, but do not take into account the user's emotional state. This has resulted in problems such as insufficient reflection of the user's actual satisfaction and motivation. Furthermore, it is difficult to determine rewards based on the evaluation results or provide appropriate feedback to promote usage, resulting in limitations on improving work efficiency and user motivation.

[1292] 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.

[1293] In this invention, the server includes means for collecting usage data of the generation AI tool, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for collecting user emotional data, means for analyzing the collected emotional data to detect the emotional state, means for analyzing the stored usage data and emotional data and classifying them by category, means for visualizing the classified usage data and emotional data on a web platform, means for evaluating the user's usage performance of the generation AI tool based on the usage data and emotional data, means for determining the user's reward based on the evaluation, and means for holding contests to promote usage performance. This enables comprehensive evaluation that takes the user's emotional state into consideration, thereby improving work efficiency and user motivation.

[1294] A "generative AI tool" is an artificial intelligence system that analyzes prompts entered by users and generates specific content.

[1295] "Usage data" refers to information about the use of the generative AI tool, specifically metadata including prompt text, generated results, usage time, usage date and time, user ID, etc.

[1296] "Emotion data" is data that represents the user's emotional state, and is analyzed from the user's facial expressions and tone of voice collected using a camera or microphone.

[1297] A "server" is a central computer system that receives, stores, and analyzes data sent from the terminals.

[1298] "Storage" refers to a data storage device for safely storing usage data and emotion data collected by the server.

[1299] A "web platform" is an online system that users can access via the Internet and that provides data visualization and search functions.

[1300] An "emotion engine" is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state.

[1301] The "evaluation score" is the user's overall evaluation value calculated based on the usage data and emotional data of the generation AI tool.

[1302] "Rewards" are monetary or other incentives awarded to users based on their rating scores.

[1303] A "contest" is a competition or awards event held based on users' performance in using the AI ​​generation tool.

[1304] This invention is a system that promotes the use of generative AI tools in business processes across the entire company. By combining it with an emotion engine that recognizes users' emotions, it collects user emotion data and improves work efficiency and user motivation. The system of this invention consists of the following main components:

[1305] Generative AI Tools

[1306] User terminal

[1307] Central Server

[1308] Web Platform

[1309] Secure Storage

[1310] Emotion Engine

[1311] This system collects, analyzes, and classifies usage data and emotional data from the generative AI tool to comprehensively evaluate users' usage performance and determine rewards and bonuses based on that data. Contests will also be held to promote usage performance. Specific implementation methods are described in detail below.

[1312] Hardware and Software Configuration

[1313] User terminal

[1314] This is a device that allows users to access and use generative AI tools. The device has a built-in camera and microphone, and is equipped with hardware for collecting emotional data.

[1315] Generative AI Tools

[1316] A generative AI tool is an artificial intelligence system that analyzes prompts entered by users and generates specific content. As a specific example of its use, if the prompt is "Please create a catchphrase for a new product," the generated result will be "An innovative product that opens up the future."

[1317] Central Server

[1318] The server is a computer system that receives, analyzes, and stores usage data and emotion data sent from the devices. The server is equipped with an analysis system that uses natural language processing technology to classify and evaluate the data.

[1319] Secure Storage

[1320] The storage is a data storage device for safely storing the usage data and emotion data received by the server, and is equipped with security measures such as access control and encryption.

[1321] Web Platform

[1322] The web platform is an online system that users can access via the Internet and use data visualization and search functions. On this platform, users can view other users' prompts, generated results, and emotion data.

[1323] Emotion Engine

[1324] An emotion engine is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state. It detects emotional states such as stress, joy, and excitement in real time and collects them as data on the device.

[1325] Specific examples

[1326] Use of generative AI tools

[1327] A user uses a generative AI tool to create a catchphrase for a new product in the marketing department. The user enters "Please create a catchphrase for our new product" as the prompt, and the generated result is "An innovative product that will open up the future." The device records a log of this operation and saves details such as the user ID, prompt, generated result, usage time, and usage date and time.

[1328] Collecting Emotional Data

[1329] While the user is using the generative AI tool, the built-in camera captures the user's facial expressions and the microphone records the tone of voice. The emotion engine analyzes this data in real time to detect emotions such as joy. The device records this emotion data along with the log data.

[1330] Data transmission and storage

[1331] The device periodically collects log data and emotional data and sends it to a server, which then stores the received data in secure storage and applies access control and encryption.

[1332] Data analysis and classification

[1333] The server analyzes the stored log data and sentiment data, and uses natural language processing technology to categorize prompts and associate sentiment data with them, such as marketing, technical support, and product development.

[1334] Data Visualization

[1335] The server displays the organized data on a web platform dashboard, where users can log in and view prompts, results, and sentiment data in the "Marketing" category, filtering for the information they need.

[1336] Evaluation of usage history and emotional data

[1337] The server analyzes the data of all users and calculates an evaluation score based on the frequency of use, the quality of the generated results, the positivity of the emotional data, etc. Based on this score, the server notifies each user of the evaluation result.

[1338] Determining compensation

[1339] The server determines the amount of rewards and bonuses for each user based on the evaluation score, and notifies the user of the details of the determined rewards and bonuses on the web platform dashboard.

[1340] Hosting a contest

[1341] The server announces the "Practical Case Contest" on the web platform. Users enter the necessary information into the application form and submit it with their own efforts attached. The server evaluates all applications, incorporating emotional data into the evaluation criteria, and determines the winners. The results are announced on the web platform, and the winners are notified.

[1342] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1343] Step 1:

[1344] The user logs into the generative AI tool and enters a prompt.

[1345] Input: User ID, prompt

[1346] Specific operation: The user enters their ID and password to log in to the generation AI tool. The prompt text is "Please create a catchphrase for our new product."

[1347] Output: Logged in to the generation AI tool, and the prompt entered

[1348] Step 2:

[1349] The generative AI tool processes the input prompt sentence and produces a generated result.

[1350] Input: prompt statement

[1351] Specific operation: The generative AI tool analyzes the prompt sentence and generates the generated result, "An innovative product that opens up the future."

[1352] Output: Generated result

[1353] Step 3:

[1354] The device records usage data of the generated AI tool.

[1355] Input: User ID, prompt, generated result, usage time, usage date and time

[1356] Specific operation: The terminal records detailed logs such as the user ID, prompt text, generated results, usage time, and usage date and time.

[1357] Output: Recorded usage data

[1358] Step 4:

[1359] While the user is using the generative AI tool, the device's camera and microphone collect emotional data.

[1360] Input: User's facial expression, tone of voice

[1361] Specific operations: The camera captures the user's facial expressions and the microphone records the tone of voice.

[1362] Output: Collected emotion data

[1363] Step 5:

[1364] The emotion engine analyzes the collected emotion data to detect the emotional state.

[1365] Input: Emotion data

[1366] Specific operation: The emotion engine analyzes collected facial expression data and tone of voice to detect emotional states such as joy, stress, and excitement.

[1367] Output: Detected emotional state

[1368] Step 6:

[1369] The terminal transmits the log data and the emotion data to the server.

[1370] Input: Log data, emotion data

[1371] Specific operation: The terminal periodically sends the collected log data and emotion data to the server.

[1372] Output: Data sent to the server

[1373] Step 7:

[1374] The server stores the received data in secure storage.

[1375] Input: Log data, emotion data

[1376] Specific operation: The server stores the received log data and emotion data in storage. Access control and encryption are applied.

[1377] Output: Saved data

[1378] Step 8:

[1379] The server analyzes the stored data, categorizes the prompts, and associates them with emotion data.

[1380] Input: Saved log data, emotion data

[1381] How it works: The server uses natural language processing technology to analyze the prompt and classify it into categories such as marketing, technical support, product development, etc. It also associates sentiment data.

[1382] Output: Categorized and linked data

[1383] Step 9:

[1384] The server then visualizes the organized data on a web platform.

[1385] Input: Categorized and linked data

[1386] What it does: The server displays the data in a dashboard, allowing users to log in and search / view it.

[1387] Output: visualized data

[1388] Step 10:

[1389] The server analyzes the usage data and emotion data of all users and calculates an evaluation score.

[1390] Input: Categorized and linked data

[1391] Specific operation: Based on the data, the server evaluates the frequency of use, the quality of the generated results, the positivity of the emotional data, etc., and calculates a score.

[1392] Output: Evaluation score

[1393] Step 11:

[1394] The server determines and notifies the user of rewards and bonuses based on the evaluation score.

[1395] Input: Rating score

[1396] Specific operation: The server determines rewards and bonuses based on the evaluation score and notifies the user on the web platform.

[1397] Output: Reward and bonus notification

[1398] Step 12:

[1399] The server will announce the practical application case contest on the web platform, accept applications from users, and evaluate and notify the results.

[1400] Input: Application information from the user

[1401] Specific operation: The server announces the contest, accepts user applications, evaluates the applications, incorporates emotional data into the evaluation criteria, and determines the winners. The results are published on the web platform, and the winners are notified.

[1402] Output: Contest results

[1403] (Application example 2)

[1404] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1405] Conventional generative AI tool systems lacked a means to efficiently evaluate user usage performance, and the criteria for promoting usage and determining rewards were unclear. Furthermore, there was no means to incorporate emotional data to improve user motivation and service quality. Furthermore, when dealing with customers, it was difficult to grasp their emotions in real time and provide appropriate services accordingly.

[1406] 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.

[1407] In this invention, the server includes a means for collecting usage data of the generative AI tool, a means for collecting user emotion data using an emotion engine, and a means for analyzing the customer's emotional state in real time and using that information to propose appropriate services. By integrating both the usage data and the emotion data for evaluation, it becomes possible to more accurately reflect the user's usage performance of the generative AI tool and to determine rewards and propose response methods.

[1408] A "generative AI tool" is an artificial intelligence system that automatically generates content or information based on text prompts entered by a user.

[1409] "Usage Data" means data about the usage of the Generative AI Tools, including prompts, generated content, duration of usage, user ID, and other metadata.

[1410] The "emotion engine" is a system that analyzes the user's facial expressions and voice to detect their emotional state in real time.

[1411] A "server" is a data processing system that analyzes and stores collected data and provides feedback to users.

[1412] "Storage" refers to a storage device used by a server to store data.

[1413] A "web platform" is an online system that users can access through a browser and view and manipulate information.

[1414] A "prompt" is text data used as input to a generative AI tool.

[1415] The "evaluation score" is a numerical value calculated based on collected data that evaluates a user's performance in using the generated AI tool.

[1416] A "reward" is a monetary or non-monetary incentive provided to a user based on their rating score.

[1417] "Real-time" means that the system processes and analyzes data and provides results almost immediately.

[1418] "Service proposal" is the act of providing information indicating the optimal response method to users and staff based on the analysis results.

[1419] The system of this invention collects usage data and emotion data from the generative AI tool, analyzes and evaluates them, and determines appropriate rewards. It also uses the emotion data to propose services to customers in real time. This system consists of the following main components: the generative AI tool, user terminal, server, web platform, storage, and emotion engine.

[1420] Overall structure

[1421] Generative AI tools: Artificial intelligence systems that generate content or information based on text prompts entered by the user.

[1422] User device: An interface for using generative AI tools and emotion engines on devices such as smartphones and PCs.

[1423] Server: The central system that analyzes and stores data.

[1424] Web platform: An online system that users access through a browser to view and manipulate data.

[1425] Storage: A storage device where a server stores data persistently.

[1426] Emotion engine: A system that analyzes the user's emotional state in real time.

[1427] Data collection and analysis

[1428] When a user device operates the AI ​​tool, usage data is automatically collected, including prompts, generated content, usage time, and user ID. This data is periodically sent to a server and stored in storage.

[1429] The emotion engine analyzes the user's facial expressions and voice to collect emotional data such as joy, sadness, and anger. For example, while the user is using the generative AI tool, the facial expressions and voice are collected via a camera and microphone, and then analyzed by the emotion engine. The analysis results are sent to the server along with the usage data and displayed on the portal.

[1430] Re-proposal and evaluation

[1431] The server uses natural language processing technology to categorize the received data, and then visualizes the categorized data on a web platform, allowing users and administrators to easily view and analyze usage history and sentiment data.

[1432] Service proposal and compensation determination

[1433] For example, a user device inputs a prompt to the generative AI tool, saying, "It has been detected that the customer is angry. Please suggest how to provide service." The generative AI tool generates an appropriate response in real time and displays a suggestion such as, "Apologize politely in a calm tone, and then make a specific suggestion to resolve the problem." This suggestion is presented to the user via the device.

[1434] The server calculates a fair and reliable evaluation score based on the entire data and determines the user's reward. The evaluation score includes usage data and emotion data, and more accurately reflects the user's experience using the AI ​​tool.

[1435] This system will promote the use of generative AI tools throughout the company, thereby increasing user motivation and improving work efficiency.

[1436] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1437] Step 1:

[1438] The device operates the generative AI tool. The user inputs a prompt (e.g., "It has been detected that the customer is angry. Please suggest how to provide service.") into the generative AI tool, which then receives the generated content. Based on the input text data (prompt), the generative AI tool performs natural language processing and generates an appropriate response. The output is the generated content, a suggestion sentence (e.g., "Please apologize politely in a calm tone, and then make a specific suggestion to resolve the problem.").

[1439] Step 2:

[1440] The device collects usage data of the generated AI tool. The collected data includes prompts, generated content, usage time, user ID, etc. This data is temporarily stored on the device and later sent to a server for processing. The input is the data generated by the user's operations, and the output is the stored usage data.

[1441] Step 3:

[1442] The device collects the user's emotional data. The emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone to detect their emotional state (e.g., joy, sadness, anger, etc.). The input is the user's facial expression images and voice data, and the output is the analyzed emotional data.

[1443] Step 4:

[1444] The device periodically collects usage data and emotion data and sends it to the server. The data is securely transmitted over the network and reaches the server. The input is the usage data and emotion data stored on the device, and the output is the data sent to the server.

[1445] Step 5:

[1446] The server stores the received data in secure storage. It records usage data and emotion data in an appropriate format while ensuring data integrity and safety. The input is the data that arrives at the server, and the output is the stored data.

[1447] Step 6:

[1448] The server analyzes the stored data and classifies it into categories. It uses natural language processing technology to automatically classify prompts and associate them with emotional data. The input is the stored usage data and emotional data, and the output is the classified data.

[1449] Step 7:

[1450] The server visualizes the organized data on a web platform, allowing users to view and search the data through their browsers. The input is the classified data, and the output is a user-accessible data visualization.

[1451] Step 8:

[1452] The server evaluates the user's performance in using the AI ​​tool based on usage data and emotion data. This evaluation calculates a score for each user and determines a reward based on the evaluation criteria. The input is usage data and emotion data, and the output is an evaluation score and a reward based on that decision.

[1453] Step 9:

[1454] The server notifies the evaluation score and reward determination on the web platform. Users can check the evaluation results and reward details by logging in to the web platform. The input is the evaluation score and reward information, and the output is a web interface that notifies them.

[1455] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1456] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1457] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1458] [Fourth embodiment]

[1459] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1460] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1461] 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).

[1462] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1463] 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.

[1464] 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).

[1465] 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.

[1466] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1467] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1468] 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.

[1469] 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.

[1470] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1471] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1472] This invention relates to a system for promoting the use of generative AI tools throughout a company. This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on the results. It also holds contests to promote usage.

[1473] System Overview

[1474] The system consists of the following main components:

[1475] Generative AI tools used by users

[1476] User terminal

[1477] Central Server

[1478] Web Platform

[1479] Secure Storage

[1480] Program processing

[1481] 1. Collecting usage data of generative AI tools

[1482] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[1483] A generative AI tool processes the input prompts and returns generated content to the user.

[1484] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[1485] 2. Transmission and storage of log data

[1486] The terminal periodically sends the collected log data to the server.

[1487] The server stores the received log data in secure storage, where the data is encrypted using a secure communication protocol (e.g., HTTPS).

[1488] 3. Data Analysis and Classification

[1489] The server analyzes the stored log data and automatically categorizes the prompt content using natural language processing technology.

[1490] Duplicate prompts are detected and removed as needed, ensuring only the necessary data is ultimately saved to the database.

[1491] 4. Data Visualization

[1492] The server visualizes the organized data on a web platform, making it accessible and viewable by users.

[1493] Users can log in to the platform and view and search other users' prompts and generated results.

[1494] 5. Evaluation of usage record

[1495] The server evaluates each user's performance in using the generated AI tool based on usage data, converting the evaluation into a score and measuring the efficiency and contribution to business performance.

[1496] Based on this score, the server determines the user's rewards and bonuses.

[1497] 6. Hosting a Contest

[1498] The server announces the practical application example contest on the web platform and provides an environment in which users can apply.

[1499] Users can submit their own efforts and compete against other users, with evaluation criteria including practicality, creativity, and contribution to business performance.

[1500] Specific examples

[1501] Specific examples are shown below.

[1502] 1. Use of generative AI tools

[1503] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[1504] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[1505] The device will log this operation.

[1506] 2. Transmission and storage of log data

[1507] The terminal periodically sends log data to the server.

[1508] The server receives the data and stores it in storage.

[1509] 3. Data Analysis and Classification

[1510] The server categorizes the prompt into the "Marketing" category and reflects it in the database.

[1511] 4. Visualization and Evaluation

[1512] The user may access a web platform to view other marketing-related prompts and their generated results.

[1513] The server also evaluates the user's activity and determines the reward for the next year.

[1514] As described above, the system of the present invention provides a concrete means for effectively utilizing generative AI tools throughout the company to achieve efficiency and improved performance.

[1515] The processing flow will be explained below.

[1516] Step 1: Use generative AI tools

[1517] A user logs in to the generative AI tool.

[1518] The user enters a prompt into the generative AI tool (e.g., "Please create a tagline for our new product").

[1519] A generative AI tool processes the input prompts and returns generated content (e.g., innovative products that open up the future) to the user.

[1520] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[1521] Step 2: Sending log data

[1522] The terminal sends the collected log data to the server at regular intervals (e.g., every hour).

[1523] The transmission is done in encrypted form using a secure communication protocol (e.g. HTTPS).

[1524] Step 3: Receiving and storing log data

[1525] The server receives the log data sent from the terminal.

[1526] The server decompresses the received log data and stores it in secure storage.

[1527] The server creates indexes to eliminate data redundancy and enable efficient searching.

[1528] Step 4: Analyze and classify the data

[1529] The server analyzes the stored log data.

[1530] The server uses natural language processing technology to automatically categorize the prompt content into categories (e.g., "Marketing," "Technical Documentation," etc.).

[1531] The server identifies and removes duplicate prompts, creating an optimized database.

[1532] Step 5: Visualize the data

[1533] The server classifies and organizes the log data, which is then visualized on a web platform.

[1534] Allows users to log in to a web platform to browse and search categorized prompts and generated results.

[1535] Step 6: Evaluate usage

[1536] The server evaluates the user's usage performance of the generated AI tool based on the usage data.

[1537] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, etc.).

[1538] Step 7: Determine the reward

[1539] The server determines the user's reward or bonus based on the evaluation score calculated.

[1540] The server notifies the evaluation score and reward determination on the web platform.

[1541] Step 8: Host a Contest

[1542] The server announces the use case contest on the web platform.

[1543] Users submit their work to the contest.

[1544] The server will evaluate the submitted practical applications and determine the winners.

[1545] This is the specific process flow of the invention. This system promotes the use of generative AI tools throughout the company, allowing for efficient data management and improved user motivation.

[1546] Example 1

[1547] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1548] With conventional generative AI models, it has been difficult to effectively evaluate each user's usage and the quality of the generated content, leading to improvements in company-wide operational efficiency. Fair and transparent standards are also needed for evaluating usage performance and determining compensation. Furthermore, there has been a lack of mechanisms for users to share their generated results with each other and a system for promoting performance.

[1549] 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.

[1550] In this invention, the server includes means for collecting usage data of the generative AI model, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for analyzing and categorizing the stored usage data, means for visualizing the categorized usage data on a web platform, means for evaluating users' usage performance of the generative AI model based on the usage data, means for determining user rewards based on the evaluation, means for holding contests to promote usage performance, means for encrypting the collected usage data using a secure communication protocol, means for recording generated content and its prompts as metadata, means for automatically detecting and deleting duplicate prompts, and means for searching and viewing prompts and results generated by users. This enables effective and fair evaluation of business use of the generative AI model, improving company-wide business efficiency, and enabling users to share results.

[1551] A "generative AI model" is a type of computer program that uses artificial intelligence to generate new data or content based on input data.

[1552] A "prompt" refers to textual instructions or requests that a user enters into a generative AI model.

[1553] "Usage Data" means data including log information, prompts, generated content, and associated metadata related to the use of a Generative AI Model.

[1554] A "server" is a computer system that processes, stores, and manages data on a network.

[1555] "Storage" is a data storage device or system for persistently storing data.

[1556] "Web Platform" means a web-based software application for providing data visualization, sharing, and access over the Internet.

[1557] "Analysis" is the process of taking log data and generated content and evaluating and categorizing the data based on specific rules and algorithms.

[1558] "Metadata" is data that includes attribute and descriptive information associated with prompts and generated content.

[1559] A "secure communication protocol" is a communication protocol for encrypting and safely transmitting and receiving data, and examples include HTTPS.

[1560] "Duplicate prompts" refer to identical or very similar instruction or request text.

[1561] "Evaluation" is the process of quantitatively or qualitatively assessing the performance of generative AI models and the quality of the content they generate.

[1562] A "contest" is an event in which user-generated content or prompts are compared based on specific criteria, and the best submissions are selected and rewarded or awarded.

[1563] "Rewards" are incentives such as money or goods given to users based on the evaluation results.

[1564] This invention relates to a system for promoting the business use of generative AI models across the entire company. This system collects, analyzes, and classifies usage data of generative AI models, evaluates user usage performance, and determines rewards based on the results. It also includes a function to hold contests to promote usage.

[1565] System configuration

[1566] The system consists of the following main components:

[1567] Generative AI models used by users

[1568] User terminal

[1569] Central Server

[1570] Web Platform

[1571] Secure Storage

[1572] Collecting usage data for generative AI models

[1573] The user logs in to the generative AI model and inputs a prompt. For example, the user might input a prompt such as, "Please create a catchphrase for a new product." This prompt is processed by the generative AI model, which generates an "innovative product that will open up the future" and returns it to the user. The device records this series of operations as a log. The log includes the prompt, the generation result, the usage time, the user ID, etc.

[1574] Sending and storing log data

[1575] The terminal periodically sends the collected log data to the server. The data is sent in encrypted form using a secure communication protocol such as HTTPS. The server then stores the received log data in secure storage.

[1576] Data analysis and classification

[1577] The server analyzes the stored log data. This analysis uses natural language processing technology to extract keywords for each prompt. It then automatically classifies prompts into categories such as "Marketing" or "Finance" based on the extracted keywords. Duplicate prompts are detected and deleted as necessary.

[1578] Data Visualization

[1579] The server visualizes the organized data on a web platform. Users can view and search other users' prompts and generated results by logging in to the web platform. A visually easy-to-understand dashboard is provided, displaying data by category.

[1580] Evaluation of usage history

[1581] The server evaluates the user's performance in using the generated AI model based on usage data. This evaluation is scored using indicators such as frequency of use, quality of generated results, and usage time. Rewards and bonuses for users are determined based on this score.

[1582] Hosting a contest

[1583] The server will announce the contest on the web platform and provide an environment where users can submit their own work. Users will compete against each other based on evaluation criteria, which may include practicality, creativity, and contribution to business performance, and the best work will be selected.

[1584] Specific examples

[1585] For example, if a marketing department user uses a generative AI model to create a catchphrase for a new product, they would enter the prompt "Please create a catchphrase for our new product." The generated result for this prompt would be "An innovative product that opens up the future." This series of operations is logged by the device and periodically sent to the server. The server then analyzes and classifies the data and visualizes it on a web platform. Finally, the server evaluates the results and determines compensation and bonuses.

[1586] As a result, this system provides a concrete means for effectively utilizing generative AI models across the entire company to improve operational efficiency and performance.

[1587] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1588] Step 1: Getting started with generative AI models

[1589] The user logs into the generative AI model's web interface using their own device. The input requires the user's employee ID and password. The output is an authenticated user session.

[1590] The user enters a prompt such as "Please create a catchphrase for our new product." The prompt becomes input data and is sent to the generative AI model.

[1591] Step 2: Handling prompts and retrieving generated content

[1592] The generative AI model analyzes the received prompt and generates the generated content using the appropriate algorithm. The input is the user's prompt, and the output is the generated content (e.g., "Innovative products that open up the future").

[1593] The device records this generated content along with a log containing prompts, usage time, and user ID, thereby accumulating usage data.

[1594] Step 3: Sending log data

[1595] The terminal sends log data to the server at regular intervals (for example, every 24 hours). The data sent is all collected log information. HTTPS is used as the appropriate communication protocol, and the data is encrypted.

[1596] The server receives this log data and stores it in storage. The input is the log data sent from the terminal, and the output is the data stored in secure storage.

[1597] Step 4: Analyze and categorize the data

[1598] The server analyzes the stored log data and classifies the prompt content into categories using natural language processing technology. The input is the log data, specifically the prompt text. The output is the data classified by category.

[1599] The server detects and, if necessary, removes duplicate prompts using a duplicate detection algorithm.

[1600] Step 5: Visualize the data

[1601] The server converts the organized data into graphs and charts and visualizes them on a web platform. The input is organized log data and the output is a visually easy-to-understand dashboard or report.

[1602] Users log in to the web platform and view other users' prompts and generated results, making it easy to search and view data.

[1603] Step 6: Evaluate usage

[1604] The server scores the user's performance in using the generated AI model based on usage data. The input is various usage data indicators (frequency of use, quality of generated content, usage time, etc.). The output is an evaluation score for each user.

[1605] Based on this evaluation score, the server calculates and determines the user's rewards and bonuses.

[1606] Step 7: Host a Contest

[1607] The server announces the contest on a web platform and provides an environment in which users can enter. The input is the contest information and entry conditions, and the output is an entry form that users can use to enter.

[1608] Users enter the contest by submitting their own generated content or prompts, and the output is that the submitted content is judged and ranked based on a set of evaluation criteria.

[1609] (Application example 1)

[1610] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1611] The present invention relates to a system that effectively utilizes generative AI tools across an entire company to improve business efficiency. Its purpose, in particular, is to efficiently control and support maintenance of automated machinery in factories. Conventional systems have difficulty not only collecting usage data of generative AI tools but also classifying and visualizing the data into appropriate categories. Furthermore, evaluating users' usage records and determining rewards are complex. Furthermore, conventional technologies have not been able to adequately address the need for actual business support using generative AI tools, particularly for improving the efficiency of the operation and maintenance of automated machinery in factories.

[1612] 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.

[1613] In this invention, the server includes: means for collecting usage data of the generating AI tool; means for transmitting the collected usage data to the server; means for storing the transmitted usage data in storage; means for analyzing and categorizing the stored usage data; means for visualizing the categorized usage data on a web platform; means for evaluating a user's usage history of the generating AI tool based on the usage data; means for determining a reward for the user based on the evaluation; means for holding a contest to promote usage history; means for efficiently supporting the control and maintenance procedures of automated machines in a factory using the generating AI tool; means for collecting log data including operation and maintenance records of the automated machines in the factory; and means for analyzing the operation logs of the automated machines in the factory and presenting optimal maintenance procedures. This makes it possible to appropriately collect, classify, and visualize the usage data of the generating AI tool, evaluate the user's usage history, and determine rewards. Furthermore, the generating AI tool can be used to efficiently support the control and maintenance procedures of automated machines in a factory.

[1614] A "generative AI tool" is an artificial intelligence technology that generates content or information based on a user-supplied natural language prompt.

[1615] “Usage Data” means information about the use of a generative AI tool, including prompts, generated content, duration of use, and user interactions.

[1616] A "server" is a computer system that provides the computational resources to receive, store, analyze, categorize, and visualize usage data.

[1617] "Storage" refers to a storage device for safely storing collected usage data and analysis results.

[1618] "Web Platform" means an internet-accessible web application that enables users to view and search the usage and results of the Generative AI Tools.

[1619] "Natural language processing technology" is a technology that aims to enable computers to understand and process human language, and is used for prompt analysis and categorization.

[1620] "Evaluation" refers to the activity of quantifying and measuring the performance of users of generative AI tools based on collected and analyzed usage data.

[1621] A "reward" is a monetary or non-monetary consideration given to a user depending on the evaluation result.

[1622] A "contest" is an event in which users compete with each other to generate content in response to a specific task, with the aim of promoting the use of generative AI tools.

[1623] "Automated machinery in factories" refers to robots and devices installed in factories that perform production tasks automatically.

[1624] "Control and maintenance procedures" are written procedures for safely and efficiently operating automated machinery and for regularly maintaining and inspecting it.

[1625] This invention is a system for effectively utilizing generative AI tools across an entire company, particularly for efficiently controlling and supporting the maintenance of automated machinery in factories. This system is composed of the following main components:

[1626] 1. Generative AI tools used by users

[1627] Users access generative AI tools and generate the necessary information and procedures by entering prompts in natural language.

[1628] For example, if a user inputs the prompt "Please tell me the routine maintenance procedures for a robot," the generative AI tool will generate the procedures and provide them to the user.

[1629] 2. User Device

[1630] This includes devices used by users such as smartphones, smart glasses, and head-mounted displays.

[1631] These devices provide an interface with generative AI tools and record user operation history and log data.

[1632] 3. Central Server

[1633] The central server is responsible for receiving, storing, analyzing, and classifying usage data sent from user terminals.

[1634] The server uses a programming language such as Python to interact with AI generation tools (e.g., OpenAI's GPT-3).

[1635] 4. Secure Storage

[1636] Secure storage (e.g., AWS S3) is used to safely store collected usage data and analysis results.

[1637] Data is encrypted using secure communication protocols (e.g. HTTPS).

[1638] 5. Web Platform

[1639] It is a web application accessible via the internet that allows users to view and search the usage and results of generated AI tools.

[1640] The platform also provides the ability to view other users' prompts and generated results.

[1641] 6. Categorizing and visualizing prompts

[1642] The server analyzes the collected usage data using natural language processing techniques and categorizes prompts.

[1643] The classified data is visualized on a web platform, allowing users to understand it intuitively.

[1644] 7. User evaluation and reward determination

[1645] The server evaluates the user's performance in using the generated AI tool based on the usage data and determines the user's reward based on the evaluation results.

[1646] For example, users who provide efficient maintenance procedures may be given high marks.

[1647] 8. Hosting a Contest

[1648] The server will host a contest on its web platform to recognize creative efforts using generative AI tools.

[1649] Users compete with other users with their proposals and solutions and are evaluated based on their results.

[1650] As a concrete example, if a user wants to learn the maintenance procedures for a robot in a factory, they input the prompt, "Please tell me the routine maintenance procedures for the robot." The generative AI tool generates procedures such as "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation," and returns them to the user. The operation logs are recorded on the device and sent to a central server for analysis and evaluation.

[1651] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1652] Step 1:

[1653] A user logs in to the generative AI tool and enters a prompt to obtain information and procedures. The input is the user's prompt (e.g., "Please tell me the routine maintenance procedures for the robot"), and the generative AI tool generates the necessary information based on this. The output is the generated content (e.g., "1. Stop the robot and perform a safety check. 2. Change the oil. 3. Inspect the sensors and check their operation.").

[1654] Step 2:

[1655] The device records a log of user operations. The input includes the prompt text entered by the user and the content generated by the generative AI tool. The device records this information as a log and saves it along with metadata. The output is the recorded operation log.

[1656] Step 3:

[1657] The terminal periodically sends the collected log data to the server. The input is the operation log recorded on the terminal, which is sent to the server using an encrypted communication protocol (e.g., HTTPS). The output is the log data sent to the server.

[1658] Step 4:

[1659] The server stores the received log data in secure storage. The input is encrypted log data, which is decrypted and stored in secure storage. The output is the data stored in secure storage.

[1660] Step 5:

[1661] The server analyzes the stored log data and classifies the prompt content by category. The input is the log data stored in secure storage, and natural language processing technology is used to analyze and classify the prompts by category. The output is the data classified by category.

[1662] Step 6:

[1663] The server visualizes the organized data on a web platform. The input is data classified by category, which is converted into a format that can be displayed on the web platform. The output is data visualized on the web platform in a format that can be viewed by users.

[1664] Step 7:

[1665] The server evaluates the user's usage performance of the generated AI tool based on usage data. The input is data visualized on the web platform, and the evaluation algorithm quantifies the user's usage performance. The output is an evaluation score for each user.

[1666] Step 8:

[1667] The server determines the reward based on the user's rating score. The input is the rating score, and the reward amount and content are determined using a reward determination algorithm. The output is the user's reward information.

[1668] Step 9:

[1669] The server hosts a contest on a web platform to promote the use of generative AI tools. The input is user submission data, and the server evaluates the user's submission based on the contest's evaluation criteria. The output is the contest results and the user's evaluation.

[1670] Step 10:

[1671] The server publishes users' contest results on a web platform and provides prizes or additional rewards as needed. The input is the evaluated contest results, which are published appropriately and notified to users. The output is the published contest results and a notification to users.

[1672] 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.

[1673] This invention is a system for promoting the use of generative AI tools in business processes across the entire company, and also combines it with an emotion engine that recognizes user emotions. This allows for the collection of user emotion data, improving work efficiency and user motivation. The system of this invention consists of the following main components:

[1674] Generative AI Tools

[1675] User terminal

[1676] Central Server

[1677] Web Platform

[1678] Secure Storage

[1679] Emotion Engine

[1680] System Overview

[1681] This system collects, analyzes, and classifies usage data of generative AI tools, evaluates users' usage performance, and determines rewards based on that. It also collects users' emotional data and reflects it in the evaluation to provide a comprehensive evaluation. The system aims to promote the use of generative AI tools and improve user motivation.

[1682] Program processing

[1683] 1. Collecting usage data of generative AI tools

[1684] The user logs in to the generative AI tool, completes the prompts, and begins using it.

[1685] A generative AI tool processes the input prompts and returns generated content to the user.

[1686] The device will record a log of this operation, including the prompt, the generated result, the usage time, and the user ID.

[1687] 2. Collecting Emotional Data

[1688] When a user uses the generative AI tool, emotional data is collected in real time using the built-in camera and microphone.

[1689] The emotion engine analyzes the user's facial expressions and tone of voice to detect their emotional state (e.g., stress, joy, excitement, etc.).

[1690] The device records the emotional data along with usage data of the generated AI tool.

[1691] 3. Transmission and storage of log data and emotional data

[1692] The terminal periodically transmits the collected log data and emotion data to the server.

[1693] The server stores the received data in secure storage.

[1694] 4. Data Analysis and Classification

[1695] The server analyzes the stored log data and emotion data.

[1696] The server uses natural language processing technology to automatically categorize the prompt content and associate it with emotional data.

[1697] It also simultaneously removes duplicate data and optimizes data.

[1698] 5. Data Visualization

[1699] The server then visualizes the organized data on a web platform.

[1700] It allows users to log in to a web platform and view and search other users' prompts, generation results, and sentiment data.

[1701] 6. Evaluation of usage history and emotional data

[1702] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[1703] The server calculates a score for each user based on the evaluation criteria, and also reflects emotional data in the overall evaluation.

[1704] 7. Determination of Remuneration

[1705] The server determines the user's reward or bonus based on the evaluation score calculated.

[1706] The server notifies the evaluation score and reward determination on the web platform.

[1707] 8. Hosting a Contest

[1708] The server announces the use case contest on the web platform.

[1709] Users submit their work to the contest.

[1710] The server evaluates the submitted practical applications and also refers to emotional data to determine the winners.

[1711] Specific examples

[1712] Specific examples are shown below.

[1713] 1. Use of generative AI tools

[1714] A user in the marketing department uses a generative AI tool to create taglines for a new product.

[1715] The prompt is "Create a catchphrase for our new product," and the generated result is "An innovative product that will open up the future."

[1716] The device will log this operation.

[1717] 2. Collecting Emotional Data

[1718] While the user is using the generative AI tool, the emotion engine collects the user's facial expression data and detects the emotion of joy.

[1719] The device records this emotion data together with the log data.

[1720] 3. Transmission and storage of log data and emotional data

[1721] The device periodically sends log data and emotion data to the server.

[1722] The server receives the data and stores it in storage.

[1723] 4. Data Analysis and Classification

[1724] The server categorizes the prompt into a "marketing" category, associates sentiment data with it, and reflects it in a database.

[1725] 5. Visualization and Evaluation

[1726] Users can access the web platform to view other marketing-related prompts, their generated results, and sentiment data.

[1727] The server evaluates the user's activity and determines the reward for the next year, taking into account their emotional data.

[1728] As described above, the system of the present invention promotes the use of generative AI tools throughout the company, and by taking emotional data into account, it performs more comprehensive evaluations, thereby improving motivation and work efficiency.

[1729] The processing flow will be explained below.

[1730] Step 1: Use generative AI tools

[1731] A user logs in to the generative AI tool.

[1732] A user enters a prompt into a generative AI tool (e.g., "Please create a tagline for our new product").

[1733] A generative AI tool processes the input prompt and returns generated content (e.g., "Innovative products that open up the future") to the user.

[1734] The device logs the prompt and metadata such as the generated content, timestamp, and user ID.

[1735] Step 2: Collecting emotion data

[1736] While you are using the generative AI tool, it uses your camera and microphone to analyze your facial expressions and tone of voice.

[1737] The emotion engine recognizes the user's facial expressions and voice to detect their emotional state (e.g., joy, excitement, stress).

[1738] The device records the detected emotion data as a log.

[1739] Step 3: Sending log data and emotion data

[1740] The device periodically sends the collected log data and emotion data to a server. The data is sent in encrypted form using a secure communication protocol (e.g., HTTPS).

[1741] Step 4: Receiving and storing data

[1742] The server receives the log data and emotion data sent from the terminal.

[1743] The server decompresses the received log data and emotion data and stores them in secure storage.

[1744] The server creates indexes to eliminate data redundancy and enable efficient searching.

[1745] Step 5: Analyze and classify the data

[1746] The server analyzes the stored log data and emotion data.

[1747] The server uses natural language processing technology to automatically categorize the prompt content (e.g., "Marketing," "Technical Documentation," etc.).

[1748] The server associates the emotional data with the prompt and generated content.

[1749] Duplicate data is also detected and removed at the same time.

[1750] Step 6: Visualize the data

[1751] The server organizes and classifies the log data and emotion data, which are then visualized on a web platform.

[1752] Users can log in to the platform and view and search other users' prompts, generated results, and sentiment data.

[1753] Step 7: Evaluate usage and sentiment data

[1754] The server evaluates the user's usage performance of the generated AI tool based on usage data and emotion data.

[1755] The server calculates a score for each user based on evaluation criteria (efficiency, contribution to business performance, emotional control, etc.).

[1756] Step 8: Determine the reward

[1757] The server determines the user's rewards and bonuses based on the evaluation score.

[1758] The server notifies the user of the evaluation results and reward details through the web platform.

[1759] Step 9: Host a Contest

[1760] The server announces the use case contest on the web platform.

[1761] Users submit their efforts to the contest, which includes performance and emotion data generated by the generative AI tool.

[1762] The server evaluates the submitted practical applications and also refers to the emotional data to determine the winners.

[1763] As described above, the system of the present invention promotes the use of generative AI tools in business operations throughout the company, performs comprehensive evaluations by taking into account user emotional data, and aims to improve business efficiency and user motivation.

[1764] Example 2

[1765] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1766] Conventional systems for collecting usage data on generative AI tools evaluate users based on their frequency of use and the results of their generation, but do not take into account the user's emotional state. This has resulted in problems such as insufficient reflection of the user's actual satisfaction and motivation. Furthermore, it is difficult to determine rewards based on the evaluation results or provide appropriate feedback to promote usage, resulting in limitations on improving work efficiency and user motivation.

[1767] 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.

[1768] In this invention, the server includes means for collecting usage data of the generation AI tool, means for transmitting the collected usage data to the server, means for storing the transmitted usage data in storage, means for collecting user emotional data, means for analyzing the collected emotional data to detect the emotional state, means for analyzing the stored usage data and emotional data and classifying them by category, means for visualizing the classified usage data and emotional data on a web platform, means for evaluating the user's usage performance of the generation AI tool based on the usage data and emotional data, means for determining the user's reward based on the evaluation, and means for holding contests to promote usage performance. This enables comprehensive evaluation that takes the user's emotional state into consideration, thereby improving work efficiency and user motivation.

[1769] A "generative AI tool" is an artificial intelligence system that analyzes prompts entered by users and generates specific content.

[1770] "Usage data" refers to information about the use of the generative AI tool, specifically metadata including prompt text, generated results, usage time, usage date and time, user ID, etc.

[1771] "Emotion data" is data that represents the user's emotional state, and is analyzed from the user's facial expressions and tone of voice collected using a camera or microphone.

[1772] A "server" is a central computer system that receives, stores, and analyzes data sent from the terminals.

[1773] "Storage" refers to a data storage device for safely storing usage data and emotion data collected by the server.

[1774] A "web platform" is an online system that users can access via the Internet and that provides data visualization and search functions.

[1775] An "emotion engine" is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state.

[1776] The "evaluation score" is the user's overall evaluation value calculated based on the usage data and emotional data of the generation AI tool.

[1777] "Rewards" are monetary or other incentives awarded to users based on their rating scores.

[1778] A "contest" is a competition or awards event held based on users' performance in using the AI ​​generation tool.

[1779] This invention is a system that promotes the use of generative AI tools in business processes across the entire company. By combining it with an emotion engine that recognizes users' emotions, it collects user emotion data and improves work efficiency and user motivation. The system of this invention consists of the following main components:

[1780] Generative AI Tools

[1781] User terminal

[1782] Central Server

[1783] Web Platform

[1784] Secure Storage

[1785] Emotion Engine

[1786] This system collects, analyzes, and classifies usage data and emotional data from the generative AI tool to comprehensively evaluate users' usage performance and determine rewards and bonuses based on that data. Contests will also be held to promote usage performance. Specific implementation methods are described in detail below.

[1787] Hardware and Software Configuration

[1788] User terminal

[1789] This is a device that allows users to access and use generative AI tools. The device has a built-in camera and microphone, and is equipped with hardware for collecting emotional data.

[1790] Generative AI Tools

[1791] A generative AI tool is an artificial intelligence system that analyzes prompts entered by users and generates specific content. As a specific example of its use, if the prompt is "Please create a catchphrase for a new product," the generated result will be "An innovative product that opens up the future."

[1792] Central Server

[1793] The server is a computer system that receives, analyzes, and stores usage data and emotion data sent from the devices. The server is equipped with an analysis system that uses natural language processing technology to classify and evaluate the data.

[1794] Secure Storage

[1795] The storage is a data storage device for safely storing the usage data and emotion data received by the server, and is equipped with security measures such as access control and encryption.

[1796] Web Platform

[1797] The web platform is an online system that users can access via the Internet and use data visualization and search functions. On this platform, users can view other users' prompts, generated results, and emotion data.

[1798] Emotion Engine

[1799] An emotion engine is a software or hardware component that analyzes a user's facial expressions and tone of voice to detect their emotional state. It detects emotional states such as stress, joy, and excitement in real time and collects them as data on the device.

[1800] Specific examples

[1801] Use of generative AI tools

[1802] A user uses a generative AI tool to create a catchphrase for a new product in the marketing department. The user enters "Please create a catchphrase for our new product" as the prompt, and the generated result is "An innovative product that will open up the future." The device records a log of this operation and saves details such as the user ID, prompt, generated result, usage time, and usage date and time.

[1803] Collecting Emotional Data

[1804] While the user is using the generative AI tool, the built-in camera captures the user's facial expressions and the microphone records the tone of voice. The emotion engine analyzes this data in real time to detect emotions such as joy. The device records this emotion data along with the log data.

[1805] Data transmission and storage

[1806] The device periodically collects log data and emotional data and sends it to a server, which then stores the received data in secure storage and applies access control and encryption.

[1807] Data analysis and classification

[1808] The server analyzes the stored log data and sentiment data, and uses natural language processing technology to categorize prompts and associate sentiment data with them, such as marketing, technical support, and product development.

[1809] Data Visualization

[1810] The server displays the organized data on a web platform dashboard, where users can log in and view prompts, results, and sentiment data in the "Marketing" category, filtering for the information they need.

[1811] Evaluation of usage history and emotional data

[1812] The server analyzes the data of all users and calculates an evaluation score based on the frequency of use, the quality of the generated results, the positivity of the emotional data, etc. Based on this score, the server notifies each user of the evaluation result.

[1813] Determining compensation

[1814] The server determines the amount of rewards and bonuses for each user based on the evaluation score, and notifies the user of the details of the determined rewards and bonuses on the web platform dashboard.

[1815] Hosting a contest

[1816] The server announces the "Practical Case Contest" on the web platform. Users enter the necessary information into the application form and submit it with their own efforts attached. The server evaluates all applications, incorporating emotional data into the evaluation criteria, and determines the winners. The results are announced on the web platform, and the winners are notified.

[1817] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1818] Step 1:

[1819] The user logs into the generative AI tool and enters a prompt.

[1820] Input: User ID, prompt

[1821] Specific operation: The user enters their ID and password to log in to the generation AI tool. The prompt text is "Please create a catchphrase for our new product."

[1822] Output: Logged in to the generation AI tool, and the prompt entered

[1823] Step 2:

[1824] The generative AI tool processes the input prompt sentence and produces a generated result.

[1825] Input: prompt statement

[1826] Specific operation: The generative AI tool analyzes the prompt sentence and generates the generated result, "An innovative product that opens up the future."

[1827] Output: Generated result

[1828] Step 3:

[1829] The device records usage data of the generated AI tool.

[1830] Input: User ID, prompt, generated result, usage time, usage date and time

[1831] Specific operation: The terminal records detailed logs such as the user ID, prompt text, generated results, usage time, and usage date and time.

[1832] Output: Recorded usage data

[1833] Step 4:

[1834] While the user is using the generative AI tool, the device's camera and microphone collect emotional data.

[1835] Input: User's facial expression, tone of voice

[1836] Specific operations: The camera captures the user's facial expressions and the microphone records the tone of voice.

[1837] Output: Collected emotion data

[1838] Step 5:

[1839] The emotion engine analyzes the collected emotion data to detect the emotional state.

[1840] Input: Emotion data

[1841] Specific operation: The emotion engine analyzes collected facial expression data and tone of voice to detect emotional states such as joy, stress, and excitement.

[1842] Output: Detected emotional state

[1843] Step 6:

[1844] The terminal transmits the log data and the emotion data to the server.

[1845] Input: Log data, emotion data

[1846] Specific operation: The terminal periodically sends the collected log data and emotion data to the server.

[1847] Output: Data sent to the server

[1848] Step 7:

[1849] The server stores the received data in secure storage.

[1850] Input: Log data, emotion data

[1851] Specific operation: The server stores the received log data and emotion data in storage. Access control and encryption are applied.

[1852] Output: Saved data

[1853] Step 8:

[1854] The server analyzes the stored data, categorizes the prompts, and associates them with emotion data.

[1855] Input: Saved log data, emotion data

[1856] How it works: The server uses natural language processing technology to analyze the prompt and classify it into categories such as marketing, technical support, product development, etc. It also associates sentiment data.

[1857] Output: Categorized and linked data

[1858] Step 9:

[1859] The server then visualizes the organized data on a web platform.

[1860] Input: Categorized and linked data

[1861] What it does: The server displays the data in a dashboard, allowing users to log in and search / view it.

[1862] Output: visualized data

[1863] Step 10:

[1864] The server analyzes the usage data and emotion data of all users and calculates an evaluation score.

[1865] Input: Categorized and linked data

[1866] Specific operation: Based on the data, the server evaluates the frequency of use, the quality of the generated results, the positivity of the emotional data, etc., and calculates a score.

[1867] Output: Evaluation score

[1868] Step 11:

[1869] The server determines and notifies the user of rewards and bonuses based on the evaluation score.

[1870] Input: Rating score

[1871] Specific operation: The server determines rewards and bonuses based on the evaluation score and notifies the user on the web platform.

[1872] Output: Reward and bonus notification

[1873] Step 12:

[1874] The server will announce the practical application case contest on the web platform, accept applications from users, and evaluate and notify the results.

[1875] Input: Application information from the user

[1876] Specific operation: The server announces the contest, accepts user applications, evaluates the applications, incorporates emotional data into the evaluation criteria, and determines the winners. The results are published on the web platform, and the winners are notified.

[1877] Output: Contest results

[1878] (Application example 2)

[1879] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1880] Conventional generative AI tool systems lacked a means to efficiently evaluate user usage performance, and the criteria for promoting usage and determining rewards were unclear. Furthermore, there was no means to incorporate emotional data to improve user motivation and service quality. Furthermore, when dealing with customers, it was difficult to grasp their emotions in real time and provide appropriate services accordingly.

[1881] 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.

[1882] In this invention, the server includes a means for collecting usage data of the generative AI tool, a means for collecting user emotion data using an emotion engine, and a means for analyzing the customer's emotional state in real time and using that information to propose appropriate services. By integrating both the usage data and the emotion data for evaluation, it becomes possible to more accurately reflect the user's usage performance of the generative AI tool and to determine rewards and propose response methods.

[1883] A "generative AI tool" is an artificial intelligence system that automatically generates content or information based on text prompts entered by a user.

[1884] "Usage Data" means data about the usage of the Generative AI Tools, including prompts, generated content, duration of usage, user ID, and other metadata.

[1885] The "emotion engine" is a system that analyzes the user's facial expressions and voice to detect their emotional state in real time.

[1886] A "server" is a data processing system that analyzes and stores collected data and provides feedback to users.

[1887] "Storage" refers to a storage device used by a server to store data.

[1888] A "web platform" is an online system that users can access through a browser and view and manipulate information.

[1889] A "prompt" is text data used as input to a generative AI tool.

[1890] The "evaluation score" is a numerical value calculated based on collected data that evaluates a user's performance in using the generated AI tool.

[1891] A "reward" is a monetary or non-monetary incentive provided to a user based on their rating score.

[1892] "Real-time" means that the system processes and analyzes data and provides results almost immediately.

[1893] "Service proposal" is the act of providing information indicating the optimal response method to users and staff based on the analysis results.

[1894] The system of this invention collects usage data and emotion data from the generative AI tool, analyzes and evaluates them, and determines appropriate rewards. It also uses the emotion data to propose services to customers in real time. This system consists of the following main components: the generative AI tool, user terminal, server, web platform, storage, and emotion engine.

[1895] Overall structure

[1896] Generative AI tools: Artificial intelligence systems that generate content or information based on text prompts entered by the user.

[1897] User device: An interface for using generative AI tools and emotion engines on devices such as smartphones and PCs.

[1898] Server: The central system that analyzes and stores data.

[1899] Web platform: An online system that users access through a browser to view and manipulate data.

[1900] Storage: A storage device where a server stores data persistently.

[1901] Emotion engine: A system that analyzes the user's emotional state in real time.

[1902] Data collection and analysis

[1903] When a user device operates the AI ​​tool, usage data is automatically collected, including prompts, generated content, usage time, and user ID. This data is periodically sent to a server and stored in storage.

[1904] The emotion engine analyzes the user's facial expressions and voice to collect emotional data such as joy, sadness, and anger. For example, while the user is using the generative AI tool, the facial expressions and voice are collected via a camera and microphone, and then analyzed by the emotion engine. The analysis results are sent to the server along with the usage data and displayed on the portal.

[1905] Re-proposal and evaluation

[1906] The server uses natural language processing technology to categorize the received data, and then visualizes the categorized data on a web platform, allowing users and administrators to easily view and analyze usage history and sentiment data.

[1907] Service proposal and compensation determination

[1908] For example, a user device inputs a prompt to the generative AI tool, saying, "It has been detected that the customer is angry. Please suggest how to provide service." The generative AI tool generates an appropriate response in real time and displays a suggestion such as, "Apologize politely in a calm tone, and then make a specific suggestion to resolve the problem." This suggestion is presented to the user via the device.

[1909] The server calculates a fair and reliable evaluation score based on the entire data and determines the user's reward. The evaluation score includes usage data and emotion data, and more accurately reflects the user's experience using the AI ​​tool.

[1910] This system will promote the use of generative AI tools throughout the company, thereby increasing user motivation and improving work efficiency.

[1911] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1912] Step 1:

[1913] The device operates the generative AI tool. The user inputs a prompt (e.g., "It has been detected that the customer is angry. Please suggest how to provide service.") into the generative AI tool, which then receives the generated content. Based on the input text data (prompt), the generative AI tool performs natural language processing and generates an appropriate response. The output is the generated content, a suggestion sentence (e.g., "Please apologize politely in a calm tone, and then make a specific suggestion to resolve the problem.").

[1914] Step 2:

[1915] The device collects usage data of the generated AI tool. The collected data includes prompts, generated content, usage time, user ID, etc. This data is temporarily stored on the device and later sent to a server for processing. The input is the data generated by the user's operations, and the output is the stored usage data.

[1916] Step 3:

[1917] The device collects the user's emotional data. The emotion engine analyzes the user's facial expressions and voice in real time using the device's built-in camera and microphone to detect their emotional state (e.g., joy, sadness, anger, etc.). The input is the user's facial expression images and voice data, and the output is the analyzed emotional data.

[1918] Step 4:

[1919] The device periodically collects usage data and emotion data and sends it to the server. The data is securely transmitted over the network and reaches the server. The input is the usage data and emotion data stored on the device, and the output is the data sent to the server.

[1920] Step 5:

[1921] The server stores the received data in secure storage. It records usage data and emotion data in an appropriate format while ensuring data integrity and safety. The input is the data that arrives at the server, and the output is the stored data.

[1922] Step 6:

[1923] The server analyzes the stored data and classifies it into categories. It uses natural language processing technology to automatically classify prompts and associate them with emotional data. The input is the stored usage data and emotional data, and the output is the classified data.

[1924] Step 7:

[1925] The server visualizes the organized data on a web platform, allowing users to view and search the data through their browsers. The input is the classified data, and the output is a user-accessible data visualization.

[1926] Step 8:

[1927] The server evaluates the user's performance in using the AI ​​tool based on usage data and emotion data. This evaluation calculates a score for each user and determines a reward based on the evaluation criteria. The input is usage data and emotion data, and the output is an evaluation score and a reward based on that decision.

[1928] Step 9:

[1929] The server notifies the evaluation score and reward determination on the web platform. Users can check the evaluation results and reward details by logging in to the web platform. The input is the evaluation score and reward information, and the output is a web interface that notifies them.

[1930] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1931] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1932] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1933] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1934] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1935] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1936] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1937] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1938] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1939] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1940] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1941] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1942] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1943] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1944] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1945] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1946] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1947] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1948] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1949] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1950] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1951] The following is further disclosed regarding the above embodiment.

[1952] (Claim 1)

[1953] A means of collecting usage data for the generative AI tool; and

[1954] means for transmitting the collected usage data to a server;

[1955] a means for storing the transmitted usage data in storage;

[1956] means for analyzing and categorizing the stored usage data;

[1957] a means for visualizing the classified usage data on a web platform;

[1958] A means for evaluating a user's performance in using the generated AI tool based on usage data; and

[1959] means for determining a reward for the user based on the rating;

[1960] The system includes a means for holding contests to promote usage.

[1961] (Claim 2)

[1962] 2. The system of claim 1, further comprising means for recording metadata including prompts and generated content as usage data of the generative AI tool.

[1963] (Claim 3)

[1964] 2. The system according to claim 1, further comprising means for automatically categorizing prompts using natural language processing techniques in analyzing usage data.

[1965] "Example 1"

[1966] (Claim 1)

[1967] A means of collecting usage data for the generative AI model; and

[1968] means for transmitting the collected usage data to a server;

[1969] a means for storing the transmitted usage data in storage;

[1970] means for analyzing and categorizing the stored usage data;

[1971] a means for visualizing the classified usage data on a web platform;

[1972] A means for evaluating a user's performance in using the generated AI model based on usage data;

[1973] means for determining a reward for the user based on the rating;

[1974] a means of holding contests to promote usage;

[1975] means for encrypting collected usage data using a secure communications protocol;

[1976] means for recording the generated content and its prompts as metadata;

[1977] A means for automatically detecting and removing duplicate prompts;

[1978] A means to search and browse user-generated prompts and results;

[1979] A system including:

[1980] (Claim 2)

[1981] The system of claim 1, further comprising means for recording metadata including prompts and generated content as usage data of the generative AI model.

[1982] (Claim 3)

[1983] 2. The system according to claim 1, further comprising means for automatically categorizing prompts using natural language processing techniques in analyzing usage data.

[1984] "Application Example 1"

[1985] (Claim 1)

[1986] A means of collecting usage data for the generative AI tool; and

[1987] means for transmitting the collected usage data to a server;

[1988] a means for storing the transmitted usage data in storage;

[1989] means for analyzing and categorizing the stored usage data;

[1990] a means for visualizing the classified usage data on a web platform;

[1991] A means for evaluating a user's performance in using the generated AI tool based on usage data; and

[1992] means for determining a reward for the user based on the rating;

[1993] a means of holding contests to promote usage;

[1994] A system including a means for efficiently supporting the control and maintenance procedures of automated machines in a factory using generative AI tools.

[1995] (Claim 2)

[1996] a means for recording metadata including prompts and generated content as usage data of the generative AI tool;

[1997] 2. The system according to claim 1, further comprising means for collecting log data including operation and maintenance records of automated machines in a factory.

[1998] (Claim 3)

[1999] a means for automatically categorizing prompts using natural language processing techniques in analyzing usage data;

[2000] 2. The system according to claim 1, further comprising means for analyzing operation logs of automated machines in a factory and presenting optimal maintenance procedures.

[2001] "Example 2: Combining Emotion Engines"

[2002] (Claim 1)

[2003] A means of collecting usage data for the generative AI tool; and

[2004] means for transmitting the collected usage data to a server;

[2005] a means for storing the transmitted usage data in storage;

[2006] means for collecting user emotion data;

[2007] means for analyzing the collected emotion data to detect an emotional state;

[2008] means for analyzing and categorizing the stored usage data and emotion data;

[2009] a means for visualizing the classified usage data and sentiment data on a web platform;

[2010] a means for evaluating a user's performance in using the generated AI tool based on the usage data and the emotion data;

[2011] means for determining a reward for the user based on the rating;

[2012] The system includes a means for holding contests to promote usage.

[2013] (Claim 2)

[2014] 2. The system of claim 1, further comprising means for recording metadata including prompts and generated content as usage data of the generative AI tool.

[2015] (Claim 3)

[2016] 2. The system according to claim 1, further comprising means for automatically categorizing prompts using natural language processing techniques in analyzing usage data.

[2017] "Application example 2 when combining emotion engines"

[2018] (Claim 1)

[2019] A means of collecting usage data for the generative AI tool; and

[2020] means for transmitting the collected usage data to a server;

[2021] a means for storing the transmitted usage data in storage;

[2022] means for analyzing and categorizing the stored usage data;

[2023] a means for visualizing the classified usage data on a web platform;

[2024] A means for evaluating a user's performance in using the generated AI tool based on usage data; and

[2025] means for determining a reward for the user based on the rating;

[2026] a means of holding contests to promote usage;

[2027] means for collecting user emotion data using an emotion engine;

[2028] means for providing a user with a response method based on the emotion data;

[2029] A system that includes a means for analyzing a customer's emotional state in real time and using that information to suggest appropriate services.

[2030] (Claim 2)

[2031] 2. The system of claim 1, further comprising means for recording metadata including prompts and generated content as usage data of the generative AI tool.

[2032] (Claim 3)

[2033] 2. The system according to claim 1, further comprising means for automatically categorizing prompts using natural language processing techniques in analyzing usage data. [Explanation of symbols]

[2034] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting usage data for the generative AI tool; and means for transmitting the collected usage data to a server; a means for storing the transmitted usage data in storage; means for analyzing and categorizing the stored usage data; a means for visualizing the classified usage data on a web platform; A means for evaluating a user's performance in using the generated AI tool based on usage data; and means for determining a reward for the user based on the rating; The system includes a means for holding contests to promote usage.

2. The system of claim 1, further comprising means for recording metadata including prompts and generated content as usage data of the generation AI tool.

3. 10. The system of claim 1, further comprising means for automatically categorizing prompts using natural language processing techniques in analyzing usage data.

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