System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting internal data of an enterprise; means for inputting the collected internal data to a generating AI; means for receiving a query from an employee; means for transmitting the received query to the generating AI; means for generating an optimal answer based on the query by the generating AI; means for providing the generated answer to the employee; means for inputting employee information to the generating AI; and means for proactively providing necessary information in a push-notification format using the employee information.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] When an employee in a company inquires about a problem, conventional systems rely on a consultation desk or person in charge, and responses often take a long time. Furthermore, even infrequent inquiries require a lot of man-hours. This problem occurs regardless of the size of the company, and there is a need for fast and efficient information provision. Furthermore, when providing information tailored to each employee, employees must search for the information themselves, which presents a challenge as it reduces work efficiency. The aim of this system is to solve these problems. [Means for solving the problem]

[0005] The present invention includes a means for collecting data within a company and inputting the collected data into a generation AI, and a means for accepting inquiries from employees and sending the accepted inquiries to the generation AI. The generation AI generates an optimal answer based on the inquiry and provides the generated answer to the employee. The system also includes a means for inputting employee information into the generation AI and using the employee information to proactively provide necessary information in the form of push notifications, thereby eliminating the need for employees to search for information themselves and enabling fast and efficient information provision.

[0006] "Internal corporate data" refers to all information held by a company, including internal regulations, business manuals, legal documents, and employee profile information.

[0007] "Generative AI" refers to an artificial intelligence system that performs natural language processing based on given data to generate optimal answers and information.

[0008] "Means for accepting inquiries" refers to an interface that accepts questions or requests from employees in input format, and is usually realized by a chatbot or form-filling system.

[0009] "Means for generating optimal answers" refers to the process by which the generative AI generates the optimal answer for employees based on the input inquiry.

[0010] "Means for providing answers" refers to the output interface for displaying the generated answers to employees, typically through the chatbot's screen or notification system.

[0011] "Employee information" refers to information about a company's employees, including, specifically, the employee's name, job title, department, work history, skill set, etc.

[0012] "Push notification format" refers to a mechanism that automatically sends specific information from the system to the user and notifies them.

[0013] "Necessary information" refers to information that employees need to carry out their work, and typically includes company regulations, work manuals, legal documents, and other related materials. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[0036] Server processing

[0037] The server accesses the company's internal database and collects the necessary information, including company regulations, business manuals, and legal documents. The server converts this information into structured data (e.g., JSON or XML format) and inputs it into the generation AI.

[0038] The generation AI is trained based on the data it receives, and gains the ability to understand and process that information. Next, the server has the function of accepting inquiries from employees and sending the received inquiries to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer back to the terminal to provide it to the employee.

[0039] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0040] Processing by the terminal

[0041] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, which are then sent to the server. When the server returns a response, the device displays it in the chat interface. Additionally, push notifications sent from the server are also displayed on the device for employees to review.

[0042] User operations

[0043] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they type a question like "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Employees can check this notification and take the necessary action.

[0044] Specific examples

[0045] Answers to employee questions

[0046] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0047] 2. Terminal: The entered question is sent to the server as text data.

[0048] 3. Server: Sends the received text data to the generation AI.

[0049] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0050] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0051] 6. Server: Receives the generated answer and sends it to the device.

[0052] 7. Terminal: Display the response in the chat interface and notify the user.

[0053] Providing information via push notifications

[0054] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0055] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0056] 3. Generation AI: Sends the generated notification content back to the server.

[0057] 4. Server: Sends the notification content received from the generation AI to the device.

[0058] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0059] 6. User: Check the push notification that appears on their device.

[0060] By implementing this system, information can be provided quickly and efficiently within the company, and employees can receive support to carry out their work smoothly.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[0064] Step 2:

[0065] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[0066] Step 3:

[0067] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[0068] Step 4:

[0069] Terminal: The entered question is sent to the server as text data.

[0070] Step 5:

[0071] Server: Sends the received query content to the generation AI.

[0072] Step 6:

[0073] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[0074] Step 7:

[0075] Generation AI: Sends the generated answer text back to the server.

[0076] Step 8:

[0077] Server: Sends the answer text received from the generation AI to the device.

[0078] Step 9:

[0079] Terminal: Display the reply text in the user's chat interface.

[0080] Step 10:

[0081] User: Review the answer provided (e.g., "The new vacation policy allows you to take 10 more vacation days per year") and get the information you need.

[0082] Step 11:

[0083] Server: Regularly reviews employee information and inputs it into the generation AI, such as employee title, department, and work history.

[0084] Step 12:

[0085] Generative AI: Generates push notification content based on employee and related information, tailored to specific times and events.

[0086] Step 13:

[0087] Generation AI: Sends the generated push notification content back to the server.

[0088] Step 14:

[0089] Server: Sends the push notification content received from the generation AI to the device.

[0090] Step 15:

[0091] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0092] Step 16:

[0093] User: Check the push notification displayed on their device and take appropriate action.

[0094] Example 1

[0095] 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."

[0096] In companies, a large amount of information is generated every day, making it difficult for employees to quickly obtain the information they need. Also, delayed responses to employee inquiries can lead to reduced work efficiency. Furthermore, if information is not provided appropriately at specific times or for specific events, there is a risk that important tasks or information will be overlooked. These problems need to be solved.

[0097] 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.

[0098] In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI in a structured data format, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate an optimal answer based on the inquiry, means for providing the generated answer to employees, means for inputting employee information to the generation AI, and means for proactively providing necessary information in the form of push notifications using the employee information. This enables employees to quickly obtain the information they need, provides prompt answers to their inquiries, and makes it possible to provide appropriate information according to specific timing or events.

[0099] "Methods of collecting data within an enterprise" are the processes and techniques used to obtain information stored in the enterprise's databases.

[0100] "Means for inputting collected data into generative AI in structured data format" refers to the processes and technologies for converting collected data into structured data such as JSON or XML format and inputting it into generative AI.

[0101] "Means for accepting inquiries from employees" refers to the interface or technology that allows employees to input questions or concerns into the system.

[0102] "Means for sending received inquiries to the generation AI" refers to the process or technology for sending the inquiry data received from employees to the generation AI.

[0103] "Means by which generative AI generates optimal answers based on inquiries" refers to the process or technology by which generative AI analyzes the inquiries it receives and generates optimal answers in response to them.

[0104] "Means of providing the generated answers to employees" refers to the process or technology used to communicate the answers returned by the generating AI to employees.

[0105] "Means for inputting employee information into the generative AI" refers to the processes and technologies for inputting information about employees into the generative AI so that the information can be analyzed and used.

[0106] "Means of proactively providing necessary information in the form of push notifications using employee information" refers to the process and technology that allows AI generated based on employee information to provide information in the form of push notifications according to specific times or events.

[0107] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[0108] Server processing

[0109] The server accesses the company's internal database and collects the necessary information (e.g., internal regulations, business manuals, and legal documents). This data collection is done using a database management system such as MySQL or PostgreSQL. After obtaining the data, the server uses a Python program to convert the collected data into JSON or XML format. The converted data is then input into the generative AI.

[0110] The generative AI is trained based on the data it receives using OpenAI's GPT model, for example. Through training, the generative AI improves its ability to understand and process data. The server then receives inquiries from employees and sends them to the generative AI. The generative AI analyzes the inquiry, generates the optimal answer, and sends it back to the server. The server then sends this answer back to the employee's device to provide it to them again.

[0111] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0112] Processing by the terminal

[0113] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. When the server returns a response, the device displays the response in the chat interface. Push notifications from the server are also displayed on the device for employees to review.

[0114] User operations

[0115] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is then displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Users can check this notification and take the necessary action.

[0116] Specific examples

[0117] Answers to employee questions

[0118] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0119] 2. Terminal: The entered question is sent to the server as text data.

[0120] 3. Server: Sends the received text data to the generation AI.

[0121] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0122] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0123] 6. Server: Receives the generated answer and sends it to the device.

[0124] 7. Terminal: Display the response in the chat interface and notify the user.

[0125] Providing information via push notifications

[0126] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0127] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0128] 3. Generation AI: Sends the generated notification content back to the server.

[0129] 4. Server: Sends the notification content received from the generation AI to the device.

[0130] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0131] 6. User: Check the push notification that appears on their device.

[0132] Example prompts for generative AI models

[0133] "Tell me about the new vacation policy."

[0134] "What are the updates regarding the operations manual this month?"

[0135] "Please show me the latest legal documents."

[0136] The above is an embodiment of this system. This system enables quick and efficient information provision within a company, and employees can receive support to smoothly carry out their work.

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1:

[0139] Server: Connects to a corporate database.

[0140] Input: Database connection information (e.g. hostname, port number, username, password)

[0141] What it does: Establishes a connection with a database management system (e.g. MySQL, PostgreSQL).

[0142] Output: Database connection object

[0143] Step 2:

[0144] Server: Obtains necessary information (e.g., company regulations, business manuals, legal documents).

[0145] Input: Database query (e.g. SQL statement)

[0146] What it does: It uses the connection object to execute SQL queries and retrieve the required data.

[0147] Output: Result set (e.g., vacation system, work manual)

[0148] Step 3:

[0149] Server: Converts the retrieved information into a structured data format (JSON or XML).

[0150] Input: Retrieve result set

[0151] What it does: Uses a Python program to convert data into JSON and XML formats.

[0152] Output: Structured data (e.g., vacation policy information in JSON format)

[0153] Step 4:

[0154] Server: Inputs structured data into the generative AI.

[0155] Input: Structured data

[0156] How it works: Sends data to a generative AI model (e.g., a GPT model) using an HTTP request.

[0157] Output: Stored as training data for the generative AI

[0158] Step 5:

[0159] User: Type a question into the chat interface on the device.

[0160] Input: Text data entered into the chat interface (e.g., "Tell me about the new vacation policy.")

[0161] How it works: The chat interface sends data to the server via JavaScript.

[0162] Output: Query data is sent to the server

[0163] Step 6:

[0164] Terminal: Sends the entered question to the server.

[0165] Input: Text data

[0166] What it does: Sends the form data to the server as an HTTP request.

[0167] Output: Received by the server

[0168] Step 7:

[0169] Server: Sends the received questions to the generation AI.

[0170] Input: Received text data

[0171] Action: Sends text data to the generating AI, requesting it to process the query.

[0172] Output: Generative AI receives the question

[0173] Step 8:

[0174] Generative AI: Generates the best answer based on the inquiry.

[0175] Input: Received text data

[0176] How it works: The AI ​​model analyzes the data and generates the best answer.

[0177] Output: Generated answer (e.g. "The new vacation policy allows you to take 10 more vacation days per year.")

[0178] Step 9:

[0179] Generation AI: Sends the generated answer back to the server.

[0180] Input: Generated answer

[0181] What it does: Sends the output of the AI ​​model to a server.

[0182] Output: The server receives the generated answer

[0183] Step 10:

[0184] Server: Sends the generated answer to the device.

[0185] Input: Generated answer

[0186] Behavior: Sends response data to the device using an HTTP response.

[0187] Output: The answer is sent to the terminal

[0188] Step 11:

[0189] Terminal: Display the response in the chat interface and notify the user.

[0190] Input: Generated answer data

[0191] What it does: Displays the reply in the chat interface via JavaScript.

[0192] Output: The answer is displayed to the user

[0193] Step 12:

[0194] Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0195] Input: Employee information (e.g., profile data) and timing information

[0196] Behavior: Sends a notification request to the generating AI.

[0197] Output: Notification content generated by the generation AI

[0198] Step 13:

[0199] Generative AI: Creates appropriate notifications to send based on employee information and related information.

[0200] Input: Employee information and timing information

[0201] How it works: AI models generate optimal notification content.

[0202] Output: Notification content is generated

[0203] Step 14:

[0204] Generation AI: Sends the generated notification content back to the server.

[0205] Input: Generated notification content

[0206] What it does: Sends the output of the AI ​​model to a server.

[0207] Output: The server receives the generated notification

[0208] Step 15:

[0209] Server: Sends the notification content received from the generation AI to the device.

[0210] Input: Generated notification content

[0211] Behavior: Sends notification data to the device using an HTTP response.

[0212] Output: A notification is sent to the device

[0213] Step 16:

[0214] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0215] Input: Notification data

[0216] What it does: Displays a push notification popup via JavaScript.

[0217] Output: A notification is displayed to the user

[0218] (Application example 1)

[0219] 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."

[0220] In order to raise security awareness among employees in a company, it is important to effectively provide the latest security information and training content. However, with conventional methods, it is difficult to provide information customized to the needs of each employee, which means that security education is not as effective as it could be.

[0221] 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.

[0222] In this invention, the server includes means for collecting data within the company, means for inputting the collected data into the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information into the generation AI, means for proactively providing necessary information in the form of push notifications using the employee information, and means for customizing and providing security information and training content to individual employees based on the generation AI. This makes it possible to provide the latest security information and training content to individual employees in a timely manner and according to their needs.

[0223] "Internal corporate data" encompasses all information generated and collected internally by a company, including internal regulations, business manuals, and legal documents.

[0224] "Generative AI" is a system that uses artificial intelligence technology to generate optimal answers and information from input data.

[0225] "Employee inquiries" are questions asked by employees to obtain work-related information or to clarify business-related questions.

[0226] "Means of sending inquiries to the generation AI" refers to the process of forwarding questions from employees to the generation AI, which then generates the optimal answer to that question.

[0227] The "optimal answer" refers to the accurate and effective information that the generative AI outputs in response to an employee inquiry.

[0228] "Means of providing to employees" refers to the method by which the answers and information output by the generative AI are delivered to employees.

[0229] "Employee Information" refers to data specific to each employee, such as profile information and work history about that employee.

[0230] "Push notification format" is a method of automatically sending important information and notifications to devices in real time.

[0231] "Security information" refers to data and knowledge about safety measures to protect companies and individuals.

[0232] "Training content" refers to educational programs and specific teaching materials that enable employees to continuously learn and improve their skills.

[0233] overview

[0234] This invention is a system that collects and processes data within a company and uses a generative AI model to provide optimal answers to inquiries from employees. It also has the function of providing necessary information based on employee information in the form of push notifications.

[0235] Server Processing

[0236] The server accesses the company's database and collects information such as internal regulations, business manuals, legal documents, security information, and training content. The collected information is converted into structured data (e.g., JSON or XML format). This is then input into the generative AI. The generative AI is trained based on the data and gains the ability to understand and process information.

[0237] Specific steps

[0238] 1. The server collects data within the company and inputs it into the generative AI as structured data.

[0239] 2. The server accepts inquiries from employees and sends the received inquiry data to the generation AI.

[0240] 3. The generation AI generates the optimal answer based on the input query and sends the answer back to the server.

[0241] 4. The server receives the generated response and notifies the employee's terminal.

[0242] 5. The server periodically reviews employee information and inputs it into the generation AI, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0243] Terminal handling

[0244] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. Responses from the server are sent back to the device and displayed in the chat interface. Push notifications sent from the server are also displayed on the device for employees to review.

[0245] Hardware / Software used

[0246] Server: Uses Flask (a lightweight Python framework).

[0247] Data structuring: Use data in JSON or XML format.

[0248] Generative AI model: A custom-made generative AI (natural language processing model) in the AIModel class.

[0249] Device: Smartphone application (implemented using JavaScript).

[0250] Specific examples

[0251] Answers to employee questions

[0252] An employee types a question into a smartphone app: "What are the current security risks?" The server receives this question and sends it to the generation AI. The generation AI generates a specific answer, such as "The current major security risks are phishing attacks and ransomware," and sends it back to the server. The server then resends the answer to the device and displays it to the employee.

[0253] Providing information via push notifications

[0254] The server requests notification content from the generation AI at a specific time based on employee information. The generation AI generates a notification such as "Employee A is scheduled for new security training on 2023-01-15." The server sends this notification to the terminal and displays it to the employee.

[0255] Push notification prompt examples

[0256] "Please provide the latest security training content. Employee A was last trained as an engineer on 2022-12-01."

[0257] This system enables quick and efficient information provision within the company, providing support to employees to ensure the smooth running of their work.

[0258] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0259] Step 1:

[0260] The server accesses the company's internal database and collects the necessary information (e.g., company regulations, business manuals, legal documents, security information, training content, etc.). The collected information is converted into JSON or XML format and input into the generating AI. This allows the generating AI to absorb the company's internal information as training data and gain the ability to understand and process it. The input is the company's internal database, and the output is structured data (JSON or XML format).

[0261] Step 2:

[0262] The user uses the chat interface on the device to input a question or inquiry. For example, a question might be, "What are the current security risks?" This input data is sent to the server. The input is the user's question, and the output is the text data sent to the server.

[0263] Step 3:

[0264] The server sends the received question data to the generation AI, which generates the optimal answer from the company's internal data based on the received question. At this time, the generation AI uses database information previously input to create an accurate and effective answer. The input is the user's question, and the output is the generation AI's answer.

[0265] Step 4:

[0266] The answer generated by the generation AI is sent back to the server. The server receives this answer data, sends it back to the device, and provides it to the user. This allows the user to obtain accurate information quickly. The input is the answer from the generation AI, and the output is the answer displayed on the user's device.

[0267] Step 5:

[0268] The server periodically reviews employee information and inputs it into the Generator AI. This process allows the Generator AI to understand each employee's information and create notifications based on specific timing and events. The input is regularly updated employee information, and the output is new training data for the Generator AI.

[0269] Step 6:

[0270] The server requests notification content based on a specific timing or event (e.g., the date of a new security training session) from the generation AI. The generation AI creates the appropriate notification content to send based on employee information and related information. The input is the notification request from the server, and the output is the notification content created by the generation AI.

[0271] Step 7:

[0272] The notification content generated by the generation AI is sent back to the server. The server then sends this notification content to the device and provides the information to the user as a push notification. This allows the user to catch important information without missing it. The input is the notification content of the generation AI, and the output is the push notification that is displayed on the user's device.

[0273] 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.

[0274] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[0275] Server processing

[0276] The server accesses the company's database and collects the necessary information (company regulations, business manuals, legal documents, employee profile information). The collected information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained based on this data and gains the ability to understand and process the information.

[0277] Next, the server has the function of accepting inquiries from employees and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the employee's device and provides it to the employee. The server also periodically reviews employee information and inputs that information into the generation AI. This allows the generation AI to provide useful information to employees in the form of push notifications based on specific timing or events.

[0278] Processing by the terminal

[0279] The device provides a chat interface for employees to enter inquiries. Employees use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that employees can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[0280] Emotion engine processing

[0281] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[0282] User operations

[0283] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[0284] Specific examples

[0285] Answers to employee questions

[0286] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0287] 2. Terminal: The entered question is sent to the server as text data.

[0288] 3. Server: Sends the received query to the generation AI.

[0289] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0290] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0291] 6. Server: Receives the generated answer and sends it to the device.

[0292] 7. Terminal: Display the response in the chat interface and notify the user.

[0293] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[0294] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[0295] Providing information via push notifications

[0296] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0297] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0298] 3. Generation AI: Sends the generated notification content back to the server.

[0299] 4. Server: Sends the push notification content received from the generation AI to the device.

[0300] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0301] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[0302] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[0303] 8. User: Check the push notification displayed on the device and take appropriate action.

[0304] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0305] The processing flow will be explained below.

[0306] Step 1:

[0307] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[0308] Step 2:

[0309] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[0310] Step 3:

[0311] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[0312] Step 4:

[0313] Terminal: The entered question is sent to the server as text data.

[0314] Step 5:

[0315] Server: Sends the received query content to the generation AI.

[0316] Step 6:

[0317] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[0318] Step 7:

[0319] Generation AI: Sends the generated answer text back to the server.

[0320] Step 8:

[0321] Server: Sends the answer text received from the generation AI to the device.

[0322] Step 9:

[0323] Terminal: Display the reply text in the user's chat interface.

[0324] Step 10:

[0325] Emotion engine: Analyzes the user's facial expressions and voice via the chat interface to determine the user's emotional state.

[0326] Step 11:

[0327] Emotion engine: Sends information to the generative AI based on the user's emotional state (e.g., if the user is feeling stressed, send that information).

[0328] Step 12:

[0329] Generative AI: Based on information from the emotion engine, it adjusts the content and wording of responses appropriately (e.g., responding in a gentler tone).

[0330] Step 13:

[0331] Terminal: Updates the adjusted response and displays it in the chat interface.

[0332] Step 14:

[0333] Server: Regularly reviews employee information and inputs it into the generation AI. For example, it collects and updates information such as employee title, department, and work history.

[0334] Step 15:

[0335] Generative AI: Generates push notification content based on employee information according to specific times and events.

[0336] Step 16:

[0337] Generation AI: Sends the generated push notification content back to the server.

[0338] Step 17:

[0339] Server: Sends the push notification content received from the generation AI to the device.

[0340] Step 18:

[0341] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0342] Step 19:

[0343] Emotion engine: Analyzes the user's emotions when a push notification is displayed and sends that information to the generation AI as needed.

[0344] Step 20:

[0345] Generative AI: Tailors notification content and follow-up methods based on information from the emotion engine.

[0346] Step 21:

[0347] User: Check the push notification displayed on their device and take appropriate action.

[0348] Example 2

[0349] 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."

[0350] There is a growing need for systems that efficiently collect, provide, and respond to inquiries within companies. However, conventional systems have the problem of being difficult to provide personalized information that meets the needs of specific users or to respond to users' emotions. In particular, large organizations require information provision that takes into account the situation and emotions of each employee. The present invention aims to solve these problems and realize more efficient and personalized information provision and inquiry response within companies.

[0351] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for collecting data within the company, a means for inputting the collected data to the generation AI, and a means for accepting inquiries from users. This enables the generation AI to generate appropriate answers based on the collected data and provide them to the user. The server also includes a means for inputting user information to the generation AI, a means for using the user information to proactively provide necessary information in the form of push notifications, and an emotion engine for analyzing the user's emotions. This enables personalized information to be provided based on specific timing or events, and also enables responses that take the user's emotions into consideration.

[0352] "Means of collecting data within a company" refers to methods and devices for aggregating various documents and information managed within a company.

[0353] "Means for inputting collected data into generative AI" refers to methods or devices for providing collected data to generative AI, allowing it to learn and make it usable.

[0354] "Means for accepting queries from users" refers to a method or device that allows users to input questions or requests to the system.

[0355] "Means for sending received inquiries to the generation AI" refers to a method or device for sending inquiry data received from a user to the generation AI for analysis and response generation.

[0356] "Means by which a generation AI generates an optimal answer based on an inquiry" refers to a method or device by which a generation AI generates the most appropriate answer to a user's inquiry.

[0357] "Means for providing the generated answer to the user" refers to a method or device for providing the answer generated by the generation AI to the user.

[0358] "Means for inputting user information into the generation AI" refers to a method or device for providing information about the user to the generation AI, allowing it to learn and make it usable.

[0359] The term "means for proactively providing necessary information in the form of a push notification using user information" refers to a method or device for automatically providing information related to a user in the form of a push notification.

[0360] An "emotion engine that analyzes user emotions" refers to a device or software that analyzes a user's facial expressions, voice, etc. to determine their current emotional state.

[0361] "Means for requesting user information from a generation AI based on specific timing or events" refers to a method or device for requesting user information from a generation AI and processing it based on predetermined timing or events.

[0362] "Internal regulations" refers to documents that describe the business procedures and rules that apply within a company.

[0363] "Business procedures" refer to documents that describe the steps or methods to be followed to perform a particular task.

[0364] "Legal documents" refer to documents that contain information about laws and regulations that a company must comply with.

[0365] MODE FOR CARRYING OUT THE INVENTION

[0366] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to user inquiries. Furthermore, by inputting user information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[0367] Server processing

[0368] The server accesses the company's database and collects the necessary information (internal regulations, business procedures, legal documents, user profile information). This information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained on this data and gains the ability to understand and process the information.

[0369] Next, the server has the function of accepting inquiries from users and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the device and provides it to the user. The server also periodically reviews user information and inputs that information into the generation AI. This allows the generation AI to provide useful information to users in the form of push notifications based on specific timing or events.

[0370] Processing by the terminal

[0371] The device provides a chat interface for users to enter inquiries. Users use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that the user can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[0372] Emotion engine processing

[0373] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[0374] User operations

[0375] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they input a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing the user to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, the server automatically sends a push notification, which is displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[0376] Specific examples

[0377] Answers to employee questions

[0378] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0379] 2. Terminal: The entered question is sent to the server as text data.

[0380] 3. Server: Sends the received query to the generation AI.

[0381] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0382] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0383] 6. Server: Receives the generated answer and sends it to the device.

[0384] 7. Terminal: Display the response in the chat interface and notify the user.

[0385] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[0386] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[0387] Providing information via push notifications

[0388] 1. Server: Based on user information, the server requests push notification content from the generation AI according to specific timing or events.

[0389] 2. Generative AI: Creates appropriate notification content to send based on user information and related information.

[0390] 3. Generation AI: Sends the generated notification content back to the server.

[0391] 4. Server: Sends the push notification content received from the generation AI to the device.

[0392] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0393] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[0394] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[0395] 8. User: Check the push notification displayed on the device and take appropriate action.

[0396] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0397] Prompt Sentence Examples

[0398] 1. "Tell me about the new vacation policy."

[0399] 2. "Show me a list of my important tasks for this week."

[0400] 3. "Please provide information on the latest legal changes."

[0401] 4. "What are some of the important events at your company this month?"

[0402] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0403] Explaining the program's processing in detail

[0404] Divide the process flow into steps

[0405] Step 1:

[0406] The server accesses the company's internal database and collects the necessary data. The collected data includes internal regulations, business procedures, legal documents, and user (employee) profile information. This data is converted into structured data (e.g., JSON format, XML format). The input is database information, and the output is structured data.

[0407] Step 2:

[0408] The server inputs structured data into the generative AI, which then trains itself based on the data it receives, allowing it to understand and process information. The input is structured data, and the output is training data for the generative AI.

[0409] Step 3:

[0410] The user inputs a query into the chat interface on the device. For example, if the user inputs "Tell me about the new vacation system," text data is generated. The input is the user's query, and the output is text data.

[0411] Step 4:

[0412] The terminal sends the text data entered by the user to the server. The server then sends the received query to the generation AI. The input is text data, and the output is query data for the generation AI.

[0413] Step 5:

[0414] Generative AI generates optimal answers based on the inquiries it receives. It uses training data to analyze the inquiry content and generate optimal answers. The input is inquiry data, and the output is answer data.

[0415] Step 6:

[0416] The generation AI sends the generated answer back to the server. The server then sends the received answer to the terminal and provides it to the user. The input is the answer data from the generation AI, and the output is the answer sent to the user.

[0417] Step 7:

[0418] The terminal displays the response sent from the server in the chat interface, and the user can check the response. The input is the response data from the server, and the output is the display content of the chat interface.

[0419] Step 8:

[0420] The server periodically reviews user information and inputs it into the generation AI. This allows the generation AI to proactively provide necessary information to users in the form of push notifications. The input is user information, and the output is the generation AI's input data.

[0421] Step 9:

[0422] The server requests push notification content from the generation AI based on specific timing or events. The generation AI analyzes user information and related information and generates appropriate notification content. The input is the push notification request, and the output is the notification content.

[0423] Step 10:

[0424] The server sends the notification content obtained from the generation AI to the device, which displays it to the user as a push notification. The input is the notification content from the generation AI, and the output is the push notification on the device.

[0425] Step 11:

[0426] The emotion engine installed in the device analyzes emotions from the user's facial expressions and voice and inputs the results into the generative AI. The input is the user's facial expressions and voice data, and the output is the analyzed emotional data.

[0427] Step 12:

[0428] The generative AI adjusts the content of responses and push notifications based on the emotional data obtained from the emotion engine. The input is emotional data, and the output is the adjusted response or notification content.

[0429] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0430] (Application example 2)

[0431] 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."

[0432] Within a company, employees need to obtain information quickly and accurately, but conventional systems make it difficult to easily obtain the necessary information. In factories, there is also a need to quickly share information such as operational status and malfunction information, but existing methods are insufficient for providing information in real time. Furthermore, there is a demand for personalized responses that take user emotions into account, but the technology to achieve this is lacking.

[0433] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information to the generation AI, means for using the employee information to proactively provide necessary information in the form of push notifications, means for collecting data within the factory and responding to inquiries from workers using the generation AI, and means for providing push notifications to factory robots and analyzing their emotions. This not only enables employees to quickly and accurately obtain the information they need, but also enables real-time information sharing within the factory and personalized responses that take user emotions into consideration.

[0434] "Internal corporate data" refers to all information related to the operation of a company, including, for example, internal regulations, business manuals, and legal documents.

[0435] "Generative AI" refers to a system that uses artificial intelligence technology to generate optimal answers or information from input data.

[0436] "Employee information" refers to individual information about individual employees, such as profile information and work history.

[0437] "Push Notification" means a notification that is sent automatically by the system without the user explicitly requesting it.

[0438] "Factory data" refers to information related to factory operations and production, including operational status, machine status, and quality control data.

[0439] An "inquiry" refers to a question or request for information made by a user (employee or worker) to the system.

[0440] "Emotion analysis" refers to the technology of analyzing a user's emotions from their facial expressions, voice, etc.

[0441] A specific embodiment for carrying out the present invention will be described.

[0442] First, a database management system (e.g., MySQL or PostgreSQL) is used to collect data within the company. Data is automatically collected from each system within the company and stored in the database. The collected data includes internal regulations, business manuals, legal documents, employee profile information, operation status, machine status, quality control data, etc.

[0443] The server converts the collected data into structured data in JSON or XML format and inputs it into a generative AI (for example, OpenAI's GPT model). The generative AI is trained based on this data and gains the ability to generate optimal answers to inquiries. The server also requests employee information from the generative AI based on specific timing or events and provides the required information in the form of push notifications.

[0444] Users (employees and workers) input inquiries using the chat interface installed on their devices. The inquiries are sent as text data to the server and processed by the generation AI. For example, if a user inputs "Tell me about the new vacation system," the generation AI searches for relevant information in the company's database and generates the most appropriate answer. The generated answer is sent to the device via the server and displayed on the chat interface.

[0445] Data from within the factory is also collected and input into the generative AI. The factory robot responds to inquiries from workers and provides real-time machine status and fault information. For example, if a worker inputs, "Machine 102 has broken down. Please tell me how to fix it," the generative AI will provide a response procedure.

[0446] This system is equipped with an emotion engine (such as Affectiva or Microsoft Azure Emotion API) that analyzes emotions from the user's facial expressions and voice. The analyzed emotion data is fed back to the AI ​​generator, which then personalizes the responses and notifications.

[0447] For example, if a user types "What is the status of Line 3?" into the chat interface on their device, the generated AI will respond with "Line 3 is currently running, the set temperature is 75 degrees, and it has been running for two hours. The next maintenance is scheduled for 2:00 PM." Similarly, if a worker types "Machine 102 has broken down. What should I do?", the generated AI will respond with "There are three possible causes for Machine 102's failure: 1) excessive temperature, 2) worn parts, and 3) overload. To resolve the issue, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload."

[0448] In this way, it is possible to provide information quickly and accurately within a company or factory, and it is also possible to provide personalized responses that take into account the user's feelings.

[0449] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0450] Step 1:

[0451] The server automatically collects data from various systems within the company and factory (e.g., operation control systems, quality control systems, user information systems). This data includes company regulations, work manuals, legal documents, operation status, machine status, quality control data, etc. The collected data is stored in a database.

[0452] Step 2:

[0453] The server converts the collected data into structured data in JSON or XML format, which is then fed into a generative AI (such as OpenAI's GPT model), which trains itself on the input data to improve its ability to generate optimal answers to queries.

[0454] Step 3:

[0455] Users (employees and workers) use the chat interface on their devices to input inquiries. For example, they might type, "Tell me about the new vacation system." The input inquiry is sent to the server as text data.

[0456] Step 4:

[0457] The server sends the text data received from the user to the generation AI, which analyzes the inquiry and searches for relevant information in the company's and factory's databases. Based on the search results, the AI ​​generates the optimal answer.

[0458] Step 5:

[0459] The AI ​​then sends the generated answer back to the server, which then sends the answer back to the device and displays it in the chat interface. For example, a specific answer such as "Under the new vacation system, you can now take 10 more days of vacation per fiscal year" is displayed.

[0460] Step 6:

[0461] The server requests employee information from the generation AI based on specific timing or events, and provides the necessary information in the form of a push notification, such as "New security training is scheduled soon."

[0462] Step 7:

[0463] The device displays the push notification to the user, who then checks and responds to the displayed notification. For example, a user who receives a notification about security training checks the training details.

[0464] Step 8:

[0465] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The analysis results are sent to a server, and the generation AI uses that information to adjust the content of responses and push notifications. For example, if the user expresses negative emotions, the generation AI will provide softer language and encouraging messages.

[0466] Step 9:

[0467] When a user types, "Machine 102 has broken down. Please tell me how to deal with this," the generated AI will respond, "There are three possible causes for the breakdown of Machine 102: 1) excessive temperature, 2) worn parts, and 3) overload. To deal with this, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload." In this way, quick and accurate information provision within the factory is achieved.

[0468] 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.

[0469] 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.

[0470] 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.

[0471] [Second embodiment]

[0472] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0473] 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.

[0474] 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).

[0475] 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.

[0476] 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.

[0477] 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).

[0478] 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.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] 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."

[0484] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[0485] Server processing

[0486] The server accesses the company's internal database and collects the necessary information, including company regulations, business manuals, and legal documents. The server converts this information into structured data (e.g., JSON or XML format) and inputs it into the generation AI.

[0487] The generation AI is trained based on the data it receives, and gains the ability to understand and process that information. Next, the server has the function of accepting inquiries from employees and sending the received inquiries to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer back to the terminal to provide it to the employee.

[0488] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0489] Processing by the terminal

[0490] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, which are then sent to the server. When the server returns a response, the device displays it in the chat interface. Additionally, push notifications sent from the server are also displayed on the device for employees to review.

[0491] User operations

[0492] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they type a question like "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Employees can check this notification and take the necessary action.

[0493] Specific examples

[0494] Answers to employee questions

[0495] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0496] 2. Terminal: The entered question is sent to the server as text data.

[0497] 3. Server: Sends the received text data to the generation AI.

[0498] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0499] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0500] 6. Server: Receives the generated answer and sends it to the device.

[0501] 7. Terminal: Display the response in the chat interface and notify the user.

[0502] Providing information via push notifications

[0503] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0504] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0505] 3. Generation AI: Sends the generated notification content back to the server.

[0506] 4. Server: Sends the notification content received from the generation AI to the device.

[0507] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0508] 6. User: Check the push notification that appears on their device.

[0509] By implementing this system, information can be provided quickly and efficiently within the company, and employees can receive support to carry out their work smoothly.

[0510] The processing flow will be explained below.

[0511] Step 1:

[0512] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[0513] Step 2:

[0514] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[0515] Step 3:

[0516] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[0517] Step 4:

[0518] Terminal: The entered question is sent to the server as text data.

[0519] Step 5:

[0520] Server: Sends the received query content to the generation AI.

[0521] Step 6:

[0522] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[0523] Step 7:

[0524] Generation AI: Sends the generated answer text back to the server.

[0525] Step 8:

[0526] Server: Sends the answer text received from the generation AI to the device.

[0527] Step 9:

[0528] Terminal: Display the reply text in the user's chat interface.

[0529] Step 10:

[0530] User: Review the answer provided (e.g., "The new vacation policy allows you to take 10 more vacation days per year") and get the information you need.

[0531] Step 11:

[0532] Server: Regularly reviews employee information and inputs it into the generation AI, such as employee title, department, and work history.

[0533] Step 12:

[0534] Generative AI: Generates push notification content based on employee and related information, tailored to specific times and events.

[0535] Step 13:

[0536] Generation AI: Sends the generated push notification content back to the server.

[0537] Step 14:

[0538] Server: Sends the push notification content received from the generation AI to the device.

[0539] Step 15:

[0540] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0541] Step 16:

[0542] User: Check the push notification displayed on their device and take appropriate action.

[0543] Example 1

[0544] 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."

[0545] In companies, a large amount of information is generated every day, making it difficult for employees to quickly obtain the information they need. Also, delayed responses to employee inquiries can lead to reduced work efficiency. Furthermore, if information is not provided appropriately at specific times or for specific events, there is a risk that important tasks or information will be overlooked. These problems need to be solved.

[0546] 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.

[0547] In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI in a structured data format, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate an optimal answer based on the inquiry, means for providing the generated answer to employees, means for inputting employee information to the generation AI, and means for proactively providing necessary information in the form of push notifications using the employee information. This enables employees to quickly obtain the information they need, provides prompt answers to their inquiries, and makes it possible to provide appropriate information according to specific timing or events.

[0548] "Methods of collecting data within an enterprise" are the processes and techniques used to obtain information stored in the enterprise's databases.

[0549] "Means for inputting collected data into generative AI in structured data format" refers to the processes and technologies for converting collected data into structured data such as JSON or XML format and inputting it into generative AI.

[0550] "Means for accepting inquiries from employees" refers to the interface or technology that allows employees to input questions or concerns into the system.

[0551] "Means for sending received inquiries to the generation AI" refers to the process or technology for sending the inquiry data received from employees to the generation AI.

[0552] "Means by which generative AI generates optimal answers based on inquiries" refers to the process or technology by which generative AI analyzes the inquiries it receives and generates optimal answers in response to them.

[0553] "Means of providing the generated answers to employees" refers to the process or technology used to communicate the answers returned by the generating AI to employees.

[0554] "Means for inputting employee information into the generative AI" refers to the processes and technologies for inputting information about employees into the generative AI so that the information can be analyzed and used.

[0555] "Means of proactively providing necessary information in the form of push notifications using employee information" refers to the process and technology that allows AI generated based on employee information to provide information in the form of push notifications according to specific times or events.

[0556] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[0557] Server processing

[0558] The server accesses the company's internal database and collects the necessary information (e.g., internal regulations, business manuals, and legal documents). This data collection is done using a database management system such as MySQL or PostgreSQL. After obtaining the data, the server uses a Python program to convert the collected data into JSON or XML format. The converted data is then input into the generative AI.

[0559] The generative AI is trained based on the data it receives using OpenAI's GPT model, for example. Through training, the generative AI improves its ability to understand and process data. The server then receives inquiries from employees and sends them to the generative AI. The generative AI analyzes the inquiry, generates the optimal answer, and sends it back to the server. The server then sends this answer back to the employee's device to provide it to them again.

[0560] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0561] Processing by the terminal

[0562] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. When the server returns a response, the device displays the response in the chat interface. Push notifications from the server are also displayed on the device for employees to review.

[0563] User operations

[0564] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is then displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Users can check this notification and take the necessary action.

[0565] Specific examples

[0566] Answers to employee questions

[0567] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0568] 2. Terminal: The entered question is sent to the server as text data.

[0569] 3. Server: Sends the received text data to the generation AI.

[0570] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0571] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0572] 6. Server: Receives the generated answer and sends it to the device.

[0573] 7. Terminal: Display the response in the chat interface and notify the user.

[0574] Providing information via push notifications

[0575] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0576] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0577] 3. Generation AI: Sends the generated notification content back to the server.

[0578] 4. Server: Sends the notification content received from the generation AI to the device.

[0579] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0580] 6. User: Check the push notification that appears on their device.

[0581] Example prompts for generative AI models

[0582] "Tell me about the new vacation policy."

[0583] "What are the updates regarding the operations manual this month?"

[0584] "Please show me the latest legal documents."

[0585] The above is an embodiment of this system. This system enables quick and efficient information provision within a company, and employees can receive support to smoothly carry out their work.

[0586] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0587] Step 1:

[0588] Server: Connects to a corporate database.

[0589] Input: Database connection information (e.g. hostname, port number, username, password)

[0590] What it does: Establishes a connection with a database management system (e.g. MySQL, PostgreSQL).

[0591] Output: Database connection object

[0592] Step 2:

[0593] Server: Obtains necessary information (e.g., company regulations, business manuals, legal documents).

[0594] Input: Database query (e.g. SQL statement)

[0595] What it does: It uses the connection object to execute SQL queries and retrieve the required data.

[0596] Output: Result set (e.g., vacation system, work manual)

[0597] Step 3:

[0598] Server: Converts the retrieved information into a structured data format (JSON or XML).

[0599] Input: Retrieve result set

[0600] What it does: Uses a Python program to convert data into JSON and XML formats.

[0601] Output: Structured data (e.g., vacation policy information in JSON format)

[0602] Step 4:

[0603] Server: Inputs structured data into the generative AI.

[0604] Input: Structured data

[0605] How it works: Sends data to a generative AI model (e.g., a GPT model) using an HTTP request.

[0606] Output: Stored as training data for the generative AI

[0607] Step 5:

[0608] User: Type a question into the chat interface on the device.

[0609] Input: Text data entered into the chat interface (e.g., "Tell me about the new vacation policy.")

[0610] How it works: The chat interface sends data to the server via JavaScript.

[0611] Output: Query data is sent to the server

[0612] Step 6:

[0613] Terminal: Sends the entered question to the server.

[0614] Input: Text data

[0615] What it does: Sends the form data to the server as an HTTP request.

[0616] Output: Received by the server

[0617] Step 7:

[0618] Server: Sends the received questions to the generation AI.

[0619] Input: Received text data

[0620] Action: Sends text data to the generating AI, requesting it to process the query.

[0621] Output: Generative AI receives the question

[0622] Step 8:

[0623] Generative AI: Generates the best answer based on the inquiry.

[0624] Input: Received text data

[0625] How it works: The AI ​​model analyzes the data and generates the best answer.

[0626] Output: Generated answer (e.g. "The new vacation policy allows you to take 10 more vacation days per year.")

[0627] Step 9:

[0628] Generation AI: Sends the generated answer back to the server.

[0629] Input: Generated answer

[0630] What it does: Sends the output of the AI ​​model to a server.

[0631] Output: The server receives the generated answer

[0632] Step 10:

[0633] Server: Sends the generated answer to the device.

[0634] Input: Generated answer

[0635] Behavior: Sends response data to the device using an HTTP response.

[0636] Output: The answer is sent to the terminal

[0637] Step 11:

[0638] Terminal: Display the response in the chat interface and notify the user.

[0639] Input: Generated answer data

[0640] What it does: Displays the reply in the chat interface via JavaScript.

[0641] Output: The answer is displayed to the user

[0642] Step 12:

[0643] Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0644] Input: Employee information (e.g., profile data) and timing information

[0645] Behavior: Sends a notification request to the generating AI.

[0646] Output: Notification content generated by the generation AI

[0647] Step 13:

[0648] Generative AI: Creates appropriate notifications to send based on employee information and related information.

[0649] Input: Employee information and timing information

[0650] How it works: AI models generate optimal notification content.

[0651] Output: Notification content is generated

[0652] Step 14:

[0653] Generation AI: Sends the generated notification content back to the server.

[0654] Input: Generated notification content

[0655] What it does: Sends the output of the AI ​​model to a server.

[0656] Output: The server receives the generated notification

[0657] Step 15:

[0658] Server: Sends the notification content received from the generation AI to the device.

[0659] Input: Generated notification content

[0660] Behavior: Sends notification data to the device using an HTTP response.

[0661] Output: A notification is sent to the device

[0662] Step 16:

[0663] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0664] Input: Notification data

[0665] What it does: Displays a push notification popup via JavaScript.

[0666] Output: A notification is displayed to the user

[0667] (Application example 1)

[0668] 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."

[0669] In order to raise security awareness among employees in a company, it is important to effectively provide the latest security information and training content. However, with conventional methods, it is difficult to provide information customized to the needs of each employee, which means that security education is not as effective as it could be.

[0670] 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.

[0671] In this invention, the server includes means for collecting data within the company, means for inputting the collected data into the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information into the generation AI, means for proactively providing necessary information in the form of push notifications using the employee information, and means for customizing and providing security information and training content to individual employees based on the generation AI. This makes it possible to provide the latest security information and training content to individual employees in a timely manner and according to their needs.

[0672] "Internal corporate data" encompasses all information generated and collected internally by a company, including internal regulations, business manuals, and legal documents.

[0673] "Generative AI" is a system that uses artificial intelligence technology to generate optimal answers and information from input data.

[0674] "Employee inquiries" are questions asked by employees to obtain work-related information or to clarify business-related questions.

[0675] "Means of sending inquiries to the generation AI" refers to the process of forwarding questions from employees to the generation AI, which then generates the optimal answer to that question.

[0676] The "optimal answer" refers to the accurate and effective information that the generative AI outputs in response to an employee inquiry.

[0677] "Means of providing to employees" refers to the method by which the answers and information output by the generative AI are delivered to employees.

[0678] "Employee Information" refers to data specific to each employee, such as profile information and work history about that employee.

[0679] "Push notification format" is a method of automatically sending important information and notifications to devices in real time.

[0680] "Security information" refers to data and knowledge about safety measures to protect companies and individuals.

[0681] "Training content" refers to educational programs and specific teaching materials that enable employees to continuously learn and improve their skills.

[0682] overview

[0683] This invention is a system that collects and processes data within a company and uses a generative AI model to provide optimal answers to inquiries from employees. It also has the function of providing necessary information based on employee information in the form of push notifications.

[0684] Server Processing

[0685] The server accesses the company's database and collects information such as internal regulations, business manuals, legal documents, security information, and training content. The collected information is converted into structured data (e.g., JSON or XML format). This is then input into the generative AI. The generative AI is trained based on the data and gains the ability to understand and process information.

[0686] Specific steps

[0687] 1. The server collects data within the company and inputs it into the generative AI as structured data.

[0688] 2. The server accepts inquiries from employees and sends the received inquiry data to the generation AI.

[0689] 3. The generation AI generates the optimal answer based on the input query and sends the answer back to the server.

[0690] 4. The server receives the generated response and notifies the employee's terminal.

[0691] 5. The server periodically reviews employee information and inputs it into the generation AI, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0692] Terminal handling

[0693] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. Responses from the server are sent back to the device and displayed in the chat interface. Push notifications sent from the server are also displayed on the device for employees to review.

[0694] Hardware / Software used

[0695] Server: Uses Flask (a lightweight Python framework).

[0696] Data structuring: Use data in JSON or XML format.

[0697] Generative AI model: A custom-made generative AI (natural language processing model) in the AIModel class.

[0698] Device: Smartphone application (implemented using JavaScript).

[0699] Specific examples

[0700] Answers to employee questions

[0701] An employee types a question into a smartphone app: "What are the current security risks?" The server receives this question and sends it to the generation AI. The generation AI generates a specific answer, such as "The current major security risks are phishing attacks and ransomware," and sends it back to the server. The server then resends the answer to the device and displays it to the employee.

[0702] Providing information via push notifications

[0703] The server requests notification content from the generation AI at a specific time based on employee information. The generation AI generates a notification such as "Employee A is scheduled for new security training on 2023-01-15." The server sends this notification to the terminal and displays it to the employee.

[0704] Push notification prompt examples

[0705] "Please provide the latest security training content. Employee A was last trained as an engineer on 2022-12-01."

[0706] This system enables quick and efficient information provision within the company, providing support to employees to ensure the smooth running of their work.

[0707] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0708] Step 1:

[0709] The server accesses the company's internal database and collects the necessary information (e.g., company regulations, business manuals, legal documents, security information, training content, etc.). The collected information is converted into JSON or XML format and input into the generating AI. This allows the generating AI to absorb the company's internal information as training data and gain the ability to understand and process it. The input is the company's internal database, and the output is structured data (JSON or XML format).

[0710] Step 2:

[0711] The user uses the chat interface on the device to input a question or inquiry. For example, a question might be, "What are the current security risks?" This input data is sent to the server. The input is the user's question, and the output is the text data sent to the server.

[0712] Step 3:

[0713] The server sends the received question data to the generation AI, which generates the optimal answer from the company's internal data based on the received question. At this time, the generation AI uses database information previously input to create an accurate and effective answer. The input is the user's question, and the output is the generation AI's answer.

[0714] Step 4:

[0715] The answer generated by the generation AI is sent back to the server. The server receives this answer data, sends it back to the device, and provides it to the user. This allows the user to obtain accurate information quickly. The input is the answer from the generation AI, and the output is the answer displayed on the user's device.

[0716] Step 5:

[0717] The server periodically reviews employee information and inputs it into the Generator AI. This process allows the Generator AI to understand each employee's information and create notifications based on specific timing and events. The input is regularly updated employee information, and the output is new training data for the Generator AI.

[0718] Step 6:

[0719] The server requests notification content based on a specific timing or event (e.g., the date of a new security training session) from the generation AI. The generation AI creates the appropriate notification content to send based on employee information and related information. The input is the notification request from the server, and the output is the notification content created by the generation AI.

[0720] Step 7:

[0721] The notification content generated by the generation AI is sent back to the server. The server then sends this notification content to the device and provides the information to the user as a push notification. This allows the user to catch important information without missing it. The input is the notification content of the generation AI, and the output is the push notification that is displayed on the user's device.

[0722] 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.

[0723] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[0724] Server processing

[0725] The server accesses the company's database and collects the necessary information (company regulations, business manuals, legal documents, employee profile information). The collected information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained based on this data and gains the ability to understand and process the information.

[0726] Next, the server has the function of accepting inquiries from employees and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the employee's device and provides it to the employee. The server also periodically reviews employee information and inputs that information into the generation AI. This allows the generation AI to provide useful information to employees in the form of push notifications based on specific timing or events.

[0727] Processing by the terminal

[0728] The device provides a chat interface for employees to enter inquiries. Employees use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that employees can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[0729] Emotion engine processing

[0730] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[0731] User operations

[0732] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[0733] Specific examples

[0734] Answers to employee questions

[0735] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0736] 2. Terminal: The entered question is sent to the server as text data.

[0737] 3. Server: Sends the received query to the generation AI.

[0738] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0739] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0740] 6. Server: Receives the generated answer and sends it to the device.

[0741] 7. Terminal: Display the response in the chat interface and notify the user.

[0742] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[0743] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[0744] Providing information via push notifications

[0745] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0746] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0747] 3. Generation AI: Sends the generated notification content back to the server.

[0748] 4. Server: Sends the push notification content received from the generation AI to the device.

[0749] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0750] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[0751] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[0752] 8. User: Check the push notification displayed on the device and take appropriate action.

[0753] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0754] The processing flow will be explained below.

[0755] Step 1:

[0756] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[0757] Step 2:

[0758] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[0759] Step 3:

[0760] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[0761] Step 4:

[0762] Terminal: The entered question is sent to the server as text data.

[0763] Step 5:

[0764] Server: Sends the received query content to the generation AI.

[0765] Step 6:

[0766] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[0767] Step 7:

[0768] Generation AI: Sends the generated answer text back to the server.

[0769] Step 8:

[0770] Server: Sends the answer text received from the generation AI to the device.

[0771] Step 9:

[0772] Terminal: Display the reply text in the user's chat interface.

[0773] Step 10:

[0774] Emotion engine: Analyzes the user's facial expressions and voice via the chat interface to determine the user's emotional state.

[0775] Step 11:

[0776] Emotion engine: Sends information to the generative AI based on the user's emotional state (e.g., if the user is feeling stressed, send that information).

[0777] Step 12:

[0778] Generative AI: Based on information from the emotion engine, it adjusts the content and wording of responses appropriately (e.g., responding in a gentler tone).

[0779] Step 13:

[0780] Terminal: Updates the adjusted response and displays it in the chat interface.

[0781] Step 14:

[0782] Server: Regularly reviews employee information and inputs it into the generation AI. For example, it collects and updates information such as employee title, department, and work history.

[0783] Step 15:

[0784] Generative AI: Generates push notification content based on employee information according to specific times and events.

[0785] Step 16:

[0786] Generation AI: Sends the generated push notification content back to the server.

[0787] Step 17:

[0788] Server: Sends the push notification content received from the generation AI to the device.

[0789] Step 18:

[0790] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0791] Step 19:

[0792] Emotion engine: Analyzes the user's emotions when a push notification is displayed and sends that information to the generation AI as needed.

[0793] Step 20:

[0794] Generative AI: Tailors notification content and follow-up methods based on information from the emotion engine.

[0795] Step 21:

[0796] User: Check the push notification displayed on their device and take appropriate action.

[0797] Example 2

[0798] 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."

[0799] There is a growing need for systems that efficiently collect, provide, and respond to inquiries within companies. However, conventional systems have the problem of being difficult to provide personalized information that meets the needs of specific users or to respond to users' emotions. In particular, large organizations require information provision that takes into account the situation and emotions of each employee. The present invention aims to solve these problems and realize more efficient and personalized information provision and inquiry response within companies.

[0800] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for collecting data within the company, a means for inputting the collected data to the generation AI, and a means for accepting inquiries from users. This enables the generation AI to generate appropriate answers based on the collected data and provide them to the user. The server also includes a means for inputting user information to the generation AI, a means for using the user information to proactively provide necessary information in the form of push notifications, and an emotion engine for analyzing the user's emotions. This enables personalized information to be provided based on specific timing or events, and also enables responses that take the user's emotions into consideration.

[0801] "Means of collecting data within a company" refers to methods and devices for aggregating various documents and information managed within a company.

[0802] "Means for inputting collected data into generative AI" refers to methods or devices for providing collected data to generative AI, allowing it to learn and make it usable.

[0803] "Means for accepting queries from users" refers to a method or device that allows users to input questions or requests to the system.

[0804] "Means for sending received inquiries to the generation AI" refers to a method or device for sending inquiry data received from a user to the generation AI for analysis and response generation.

[0805] "Means by which a generation AI generates an optimal answer based on an inquiry" refers to a method or device by which a generation AI generates the most appropriate answer to a user's inquiry.

[0806] "Means for providing the generated answer to the user" refers to a method or device for providing the answer generated by the generation AI to the user.

[0807] "Means for inputting user information into the generation AI" refers to a method or device for providing information about the user to the generation AI, allowing it to learn and make it usable.

[0808] The term "means for proactively providing necessary information in the form of a push notification using user information" refers to a method or device for automatically providing information related to a user in the form of a push notification.

[0809] An "emotion engine that analyzes user emotions" refers to a device or software that analyzes a user's facial expressions, voice, etc. to determine their current emotional state.

[0810] "Means for requesting user information from a generation AI based on specific timing or events" refers to a method or device for requesting user information from a generation AI and processing it based on predetermined timing or events.

[0811] "Internal regulations" refers to documents that describe the business procedures and rules that apply within a company.

[0812] "Business procedures" refer to documents that describe the steps or methods to be followed to perform a particular task.

[0813] "Legal documents" refer to documents that contain information about laws and regulations that a company must comply with.

[0814] MODE FOR CARRYING OUT THE INVENTION

[0815] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to user inquiries. Furthermore, by inputting user information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[0816] Server processing

[0817] The server accesses the company's database and collects the necessary information (internal regulations, business procedures, legal documents, user profile information). This information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained on this data and gains the ability to understand and process the information.

[0818] Next, the server has the function of accepting inquiries from users and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the device and provides it to the user. The server also periodically reviews user information and inputs that information into the generation AI. This allows the generation AI to provide useful information to users in the form of push notifications based on specific timing or events.

[0819] Processing by the terminal

[0820] The device provides a chat interface for users to enter inquiries. Users use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that the user can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[0821] Emotion engine processing

[0822] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[0823] User operations

[0824] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they input a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing the user to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, the server automatically sends a push notification, which is displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[0825] Specific examples

[0826] Answers to employee questions

[0827] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0828] 2. Terminal: The entered question is sent to the server as text data.

[0829] 3. Server: Sends the received query to the generation AI.

[0830] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0831] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0832] 6. Server: Receives the generated answer and sends it to the device.

[0833] 7. Terminal: Display the response in the chat interface and notify the user.

[0834] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[0835] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[0836] Providing information via push notifications

[0837] 1. Server: Based on user information, the server requests push notification content from the generation AI according to specific timing or events.

[0838] 2. Generative AI: Creates appropriate notification content to send based on user information and related information.

[0839] 3. Generation AI: Sends the generated notification content back to the server.

[0840] 4. Server: Sends the push notification content received from the generation AI to the device.

[0841] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0842] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[0843] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[0844] 8. User: Check the push notification displayed on the device and take appropriate action.

[0845] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0846] Prompt Sentence Examples

[0847] 1. "Tell me about the new vacation policy."

[0848] 2. "Show me a list of my important tasks for this week."

[0849] 3. "Please provide information on the latest legal changes."

[0850] 4. "What are some of the important events at your company this month?"

[0851] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0852] Explaining the program's processing in detail

[0853] Divide the process flow into steps

[0854] Step 1:

[0855] The server accesses the company's internal database and collects the necessary data. The collected data includes internal regulations, business procedures, legal documents, and user (employee) profile information. This data is converted into structured data (e.g., JSON format, XML format). The input is database information, and the output is structured data.

[0856] Step 2:

[0857] The server inputs structured data into the generative AI, which then trains itself based on the data it receives, allowing it to understand and process information. The input is structured data, and the output is training data for the generative AI.

[0858] Step 3:

[0859] The user inputs a query into the chat interface on the device. For example, if the user inputs "Tell me about the new vacation system," text data is generated. The input is the user's query, and the output is text data.

[0860] Step 4:

[0861] The terminal sends the text data entered by the user to the server. The server then sends the received query to the generation AI. The input is text data, and the output is query data for the generation AI.

[0862] Step 5:

[0863] Generative AI generates optimal answers based on the inquiries it receives. It uses training data to analyze the inquiry content and generate optimal answers. The input is inquiry data, and the output is answer data.

[0864] Step 6:

[0865] The generation AI sends the generated answer back to the server. The server then sends the received answer to the terminal and provides it to the user. The input is the answer data from the generation AI, and the output is the answer sent to the user.

[0866] Step 7:

[0867] The terminal displays the response sent from the server in the chat interface, and the user can check the response. The input is the response data from the server, and the output is the display content of the chat interface.

[0868] Step 8:

[0869] The server periodically reviews user information and inputs it into the generation AI. This allows the generation AI to proactively provide necessary information to users in the form of push notifications. The input is user information, and the output is the generation AI's input data.

[0870] Step 9:

[0871] The server requests push notification content from the generation AI based on specific timing or events. The generation AI analyzes user information and related information and generates appropriate notification content. The input is the push notification request, and the output is the notification content.

[0872] Step 10:

[0873] The server sends the notification content obtained from the generation AI to the device, which displays it to the user as a push notification. The input is the notification content from the generation AI, and the output is the push notification on the device.

[0874] Step 11:

[0875] The emotion engine installed in the device analyzes emotions from the user's facial expressions and voice and inputs the results into the generative AI. The input is the user's facial expressions and voice data, and the output is the analyzed emotional data.

[0876] Step 12:

[0877] The generative AI adjusts the content of responses and push notifications based on the emotional data obtained from the emotion engine. The input is emotional data, and the output is the adjusted response or notification content.

[0878] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[0879] (Application example 2)

[0880] 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."

[0881] Within a company, employees need to obtain information quickly and accurately, but conventional systems make it difficult to easily obtain the necessary information. In factories, there is also a need to quickly share information such as operational status and malfunction information, but existing methods are insufficient for providing information in real time. Furthermore, there is a demand for personalized responses that take user emotions into account, but the technology to achieve this is lacking.

[0882] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information to the generation AI, means for using the employee information to proactively provide necessary information in the form of push notifications, means for collecting data within the factory and responding to inquiries from workers using the generation AI, and means for providing push notifications to factory robots and analyzing their emotions. This not only enables employees to quickly and accurately obtain the information they need, but also enables real-time information sharing within the factory and personalized responses that take user emotions into consideration.

[0883] "Internal corporate data" refers to all information related to the operation of a company, including, for example, internal regulations, business manuals, and legal documents.

[0884] "Generative AI" refers to a system that uses artificial intelligence technology to generate optimal answers or information from input data.

[0885] "Employee information" refers to individual information about individual employees, such as profile information and work history.

[0886] "Push Notification" means a notification that is sent automatically by the system without the user explicitly requesting it.

[0887] "Factory data" refers to information related to factory operations and production, including operational status, machine status, and quality control data.

[0888] An "inquiry" refers to a question or request for information made by a user (employee or worker) to the system.

[0889] "Emotion analysis" refers to the technology of analyzing a user's emotions from their facial expressions, voice, etc.

[0890] A specific embodiment for carrying out the present invention will be described.

[0891] First, a database management system (e.g., MySQL or PostgreSQL) is used to collect data within the company. Data is automatically collected from each system within the company and stored in the database. The collected data includes internal regulations, business manuals, legal documents, employee profile information, operation status, machine status, quality control data, etc.

[0892] The server converts the collected data into structured data in JSON or XML format and inputs it into a generative AI (for example, OpenAI's GPT model). The generative AI is trained based on this data and gains the ability to generate optimal answers to inquiries. The server also requests employee information from the generative AI based on specific timing or events and provides the required information in the form of push notifications.

[0893] Users (employees and workers) input inquiries using the chat interface installed on their devices. The inquiries are sent as text data to the server and processed by the generation AI. For example, if a user inputs "Tell me about the new vacation system," the generation AI searches for relevant information in the company's database and generates the most appropriate answer. The generated answer is sent to the device via the server and displayed on the chat interface.

[0894] Data from within the factory is also collected and input into the generative AI. The factory robot responds to inquiries from workers and provides real-time machine status and fault information. For example, if a worker inputs, "Machine 102 has broken down. Please tell me how to fix it," the generative AI will provide a response procedure.

[0895] This system is equipped with an emotion engine (such as Affectiva or Microsoft Azure Emotion API) that analyzes emotions from the user's facial expressions and voice. The analyzed emotion data is fed back to the AI ​​generator, which then personalizes the responses and notifications.

[0896] For example, if a user types "What is the status of Line 3?" into the chat interface on their device, the generated AI will respond with "Line 3 is currently running, the set temperature is 75 degrees, and it has been running for two hours. The next maintenance is scheduled for 2:00 PM." Similarly, if a worker types "Machine 102 has broken down. What should I do?", the generated AI will respond with "There are three possible causes for Machine 102's failure: 1) excessive temperature, 2) worn parts, and 3) overload. To resolve the issue, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload."

[0897] In this way, it is possible to provide information quickly and accurately within a company or factory, and it is also possible to provide personalized responses that take into account the user's feelings.

[0898] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0899] Step 1:

[0900] The server automatically collects data from various systems within the company and factory (e.g., operation control systems, quality control systems, user information systems). This data includes company regulations, work manuals, legal documents, operation status, machine status, quality control data, etc. The collected data is stored in a database.

[0901] Step 2:

[0902] The server converts the collected data into structured data in JSON or XML format, which is then fed into a generative AI (such as OpenAI's GPT model), which trains itself on the input data to improve its ability to generate optimal answers to queries.

[0903] Step 3:

[0904] Users (employees and workers) use the chat interface on their devices to input inquiries. For example, they might type, "Tell me about the new vacation system." The input inquiry is sent to the server as text data.

[0905] Step 4:

[0906] The server sends the text data received from the user to the generation AI, which analyzes the inquiry and searches for relevant information in the company's and factory's databases. Based on the search results, the AI ​​generates the optimal answer.

[0907] Step 5:

[0908] The AI ​​then sends the generated answer back to the server, which then sends the answer back to the device and displays it in the chat interface. For example, a specific answer such as "Under the new vacation system, you can now take 10 more days of vacation per fiscal year" is displayed.

[0909] Step 6:

[0910] The server requests employee information from the generation AI based on specific timing or events, and provides the necessary information in the form of a push notification, such as "New security training is scheduled soon."

[0911] Step 7:

[0912] The device displays the push notification to the user, who then checks and responds to the displayed notification. For example, a user who receives a notification about security training checks the training details.

[0913] Step 8:

[0914] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The analysis results are sent to a server, and the generation AI uses that information to adjust the content of responses and push notifications. For example, if the user expresses negative emotions, the generation AI will provide softer language and encouraging messages.

[0915] Step 9:

[0916] When a user types, "Machine 102 has broken down. Please tell me how to deal with this," the generated AI will respond, "There are three possible causes for the breakdown of Machine 102: 1) excessive temperature, 2) worn parts, and 3) overload. To deal with this, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload." In this way, quick and accurate information provision within the factory is achieved.

[0917] 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.

[0918] 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.

[0919] 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.

[0920] [Third embodiment]

[0921] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0922] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0923] 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).

[0924] 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.

[0925] 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.

[0926] 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).

[0927] 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.

[0928] 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.

[0929] 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.

[0930] 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.

[0931] 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.

[0932] 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."

[0933] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[0934] Server processing

[0935] The server accesses the company's internal database and collects the necessary information, including company regulations, business manuals, and legal documents. The server converts this information into structured data (e.g., JSON or XML format) and inputs it into the generation AI.

[0936] The generation AI is trained based on the data it receives, and gains the ability to understand and process that information. Next, the server has the function of accepting inquiries from employees and sending the received inquiries to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer back to the terminal to provide it to the employee.

[0937] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[0938] Processing by the terminal

[0939] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, which are then sent to the server. When the server returns a response, the device displays it in the chat interface. Additionally, push notifications sent from the server are also displayed on the device for employees to review.

[0940] User operations

[0941] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they type a question like "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Employees can check this notification and take the necessary action.

[0942] Specific examples

[0943] Answers to employee questions

[0944] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[0945] 2. Terminal: The entered question is sent to the server as text data.

[0946] 3. Server: Sends the received text data to the generation AI.

[0947] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[0948] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[0949] 6. Server: Receives the generated answer and sends it to the device.

[0950] 7. Terminal: Display the response in the chat interface and notify the user.

[0951] Providing information via push notifications

[0952] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[0953] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[0954] 3. Generation AI: Sends the generated notification content back to the server.

[0955] 4. Server: Sends the notification content received from the generation AI to the device.

[0956] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[0957] 6. User: Check the push notification that appears on their device.

[0958] By implementing this system, information can be provided quickly and efficiently within the company, and employees can receive support to carry out their work smoothly.

[0959] The processing flow will be explained below.

[0960] Step 1:

[0961] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[0962] Step 2:

[0963] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[0964] Step 3:

[0965] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[0966] Step 4:

[0967] Terminal: The entered question is sent to the server as text data.

[0968] Step 5:

[0969] Server: Sends the received query content to the generation AI.

[0970] Step 6:

[0971] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[0972] Step 7:

[0973] Generation AI: Sends the generated answer text back to the server.

[0974] Step 8:

[0975] Server: Sends the answer text received from the generation AI to the device.

[0976] Step 9:

[0977] Terminal: Display the reply text in the user's chat interface.

[0978] Step 10:

[0979] User: Review the answer provided (e.g., "The new vacation policy allows you to take 10 more vacation days per year") and get the information you need.

[0980] Step 11:

[0981] Server: Regularly reviews employee information and inputs it into the generation AI, such as employee title, department, and work history.

[0982] Step 12:

[0983] Generative AI: Generates push notification content based on employee and related information, tailored to specific times and events.

[0984] Step 13:

[0985] Generation AI: Sends the generated push notification content back to the server.

[0986] Step 14:

[0987] Server: Sends the push notification content received from the generation AI to the device.

[0988] Step 15:

[0989] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[0990] Step 16:

[0991] User: Check the push notification displayed on their device and take appropriate action.

[0992] Example 1

[0993] 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."

[0994] In companies, a large amount of information is generated every day, making it difficult for employees to quickly obtain the information they need. Also, delayed responses to employee inquiries can lead to reduced work efficiency. Furthermore, if information is not provided appropriately at specific times or for specific events, there is a risk that important tasks or information will be overlooked. These problems need to be solved.

[0995] 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.

[0996] In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI in a structured data format, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate an optimal answer based on the inquiry, means for providing the generated answer to employees, means for inputting employee information to the generation AI, and means for proactively providing necessary information in the form of push notifications using the employee information. This enables employees to quickly obtain the information they need, provides prompt answers to their inquiries, and makes it possible to provide appropriate information according to specific timing or events.

[0997] "Methods of collecting data within an enterprise" are the processes and techniques used to obtain information stored in the enterprise's databases.

[0998] "Means for inputting collected data into generative AI in structured data format" refers to the processes and technologies for converting collected data into structured data such as JSON or XML format and inputting it into generative AI.

[0999] "Means for accepting inquiries from employees" refers to the interface or technology that allows employees to input questions or concerns into the system.

[1000] "Means for sending received inquiries to the generation AI" refers to the process or technology for sending the inquiry data received from employees to the generation AI.

[1001] "Means by which generative AI generates optimal answers based on inquiries" refers to the process or technology by which generative AI analyzes the inquiries it receives and generates optimal answers in response to them.

[1002] "Means of providing the generated answers to employees" refers to the process or technology used to communicate the answers returned by the generating AI to employees.

[1003] "Means for inputting employee information into the generative AI" refers to the processes and technologies for inputting information about employees into the generative AI so that the information can be analyzed and used.

[1004] "Means of proactively providing necessary information in the form of push notifications using employee information" refers to the process and technology that allows AI generated based on employee information to provide information in the form of push notifications according to specific times or events.

[1005] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[1006] Server processing

[1007] The server accesses the company's internal database and collects the necessary information (e.g., internal regulations, business manuals, and legal documents). This data collection is done using a database management system such as MySQL or PostgreSQL. After obtaining the data, the server uses a Python program to convert the collected data into JSON or XML format. The converted data is then input into the generative AI.

[1008] The generative AI is trained based on the data it receives using OpenAI's GPT model, for example. Through training, the generative AI improves its ability to understand and process data. The server then receives inquiries from employees and sends them to the generative AI. The generative AI analyzes the inquiry, generates the optimal answer, and sends it back to the server. The server then sends this answer back to the employee's device to provide it to them again.

[1009] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[1010] Processing by the terminal

[1011] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. When the server returns a response, the device displays the response in the chat interface. Push notifications from the server are also displayed on the device for employees to review.

[1012] User operations

[1013] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is then displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Users can check this notification and take the necessary action.

[1014] Specific examples

[1015] Answers to employee questions

[1016] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1017] 2. Terminal: The entered question is sent to the server as text data.

[1018] 3. Server: Sends the received text data to the generation AI.

[1019] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1020] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1021] 6. Server: Receives the generated answer and sends it to the device.

[1022] 7. Terminal: Display the response in the chat interface and notify the user.

[1023] Providing information via push notifications

[1024] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1025] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[1026] 3. Generation AI: Sends the generated notification content back to the server.

[1027] 4. Server: Sends the notification content received from the generation AI to the device.

[1028] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1029] 6. User: Check the push notification that appears on their device.

[1030] Example prompts for generative AI models

[1031] "Tell me about the new vacation policy."

[1032] "What are the updates regarding the operations manual this month?"

[1033] "Please show me the latest legal documents."

[1034] The above is an embodiment of this system. This system enables quick and efficient information provision within a company, and employees can receive support to smoothly carry out their work.

[1035] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1036] Step 1:

[1037] Server: Connects to a corporate database.

[1038] Input: Database connection information (e.g. hostname, port number, username, password)

[1039] What it does: Establishes a connection with a database management system (e.g. MySQL, PostgreSQL).

[1040] Output: Database connection object

[1041] Step 2:

[1042] Server: Obtains necessary information (e.g., company regulations, business manuals, legal documents).

[1043] Input: Database query (e.g. SQL statement)

[1044] What it does: It uses the connection object to execute SQL queries and retrieve the required data.

[1045] Output: Result set (e.g., vacation system, work manual)

[1046] Step 3:

[1047] Server: Converts the retrieved information into a structured data format (JSON or XML).

[1048] Input: Retrieve result set

[1049] What it does: Uses a Python program to convert data into JSON and XML formats.

[1050] Output: Structured data (e.g., vacation policy information in JSON format)

[1051] Step 4:

[1052] Server: Inputs structured data into the generative AI.

[1053] Input: Structured data

[1054] How it works: Sends data to a generative AI model (e.g., a GPT model) using an HTTP request.

[1055] Output: Stored as training data for the generative AI

[1056] Step 5:

[1057] User: Type a question into the chat interface on the device.

[1058] Input: Text data entered into the chat interface (e.g., "Tell me about the new vacation policy.")

[1059] How it works: The chat interface sends data to the server via JavaScript.

[1060] Output: Query data is sent to the server

[1061] Step 6:

[1062] Terminal: Sends the entered question to the server.

[1063] Input: Text data

[1064] What it does: Sends the form data to the server as an HTTP request.

[1065] Output: Received by the server

[1066] Step 7:

[1067] Server: Sends the received questions to the generation AI.

[1068] Input: Received text data

[1069] Action: Sends text data to the generating AI, requesting it to process the query.

[1070] Output: Generative AI receives the question

[1071] Step 8:

[1072] Generative AI: Generates the best answer based on the inquiry.

[1073] Input: Received text data

[1074] How it works: The AI ​​model analyzes the data and generates the best answer.

[1075] Output: Generated answer (e.g. "The new vacation policy allows you to take 10 more vacation days per year.")

[1076] Step 9:

[1077] Generation AI: Sends the generated answer back to the server.

[1078] Input: Generated answer

[1079] What it does: Sends the output of the AI ​​model to a server.

[1080] Output: The server receives the generated answer

[1081] Step 10:

[1082] Server: Sends the generated answer to the device.

[1083] Input: Generated answer

[1084] Behavior: Sends response data to the device using an HTTP response.

[1085] Output: The answer is sent to the terminal

[1086] Step 11:

[1087] Terminal: Display the response in the chat interface and notify the user.

[1088] Input: Generated answer data

[1089] What it does: Displays the reply in the chat interface via JavaScript.

[1090] Output: The answer is displayed to the user

[1091] Step 12:

[1092] Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1093] Input: Employee information (e.g., profile data) and timing information

[1094] Behavior: Sends a notification request to the generating AI.

[1095] Output: Notification content generated by the generation AI

[1096] Step 13:

[1097] Generative AI: Creates appropriate notifications to send based on employee information and related information.

[1098] Input: Employee information and timing information

[1099] How it works: AI models generate optimal notification content.

[1100] Output: Notification content is generated

[1101] Step 14:

[1102] Generation AI: Sends the generated notification content back to the server.

[1103] Input: Generated notification content

[1104] What it does: Sends the output of the AI ​​model to a server.

[1105] Output: The server receives the generated notification

[1106] Step 15:

[1107] Server: Sends the notification content received from the generation AI to the device.

[1108] Input: Generated notification content

[1109] Behavior: Sends notification data to the device using an HTTP response.

[1110] Output: A notification is sent to the device

[1111] Step 16:

[1112] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[1113] Input: Notification data

[1114] What it does: Displays a push notification popup via JavaScript.

[1115] Output: A notification is displayed to the user

[1116] (Application example 1)

[1117] 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."

[1118] In order to raise security awareness among employees in a company, it is important to effectively provide the latest security information and training content. However, with conventional methods, it is difficult to provide information customized to the needs of each employee, which means that security education is not as effective as it could be.

[1119] 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.

[1120] In this invention, the server includes means for collecting data within the company, means for inputting the collected data into the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information into the generation AI, means for proactively providing necessary information in the form of push notifications using the employee information, and means for customizing and providing security information and training content to individual employees based on the generation AI. This makes it possible to provide the latest security information and training content to individual employees in a timely manner and according to their needs.

[1121] "Internal corporate data" encompasses all information generated and collected internally by a company, including internal regulations, business manuals, and legal documents.

[1122] "Generative AI" is a system that uses artificial intelligence technology to generate optimal answers and information from input data.

[1123] "Employee inquiries" are questions asked by employees to obtain work-related information or to clarify business-related questions.

[1124] "Means of sending inquiries to the generation AI" refers to the process of forwarding questions from employees to the generation AI, which then generates the optimal answer to that question.

[1125] The "optimal answer" refers to the accurate and effective information that the generative AI outputs in response to an employee inquiry.

[1126] "Means of providing to employees" refers to the method by which the answers and information output by the generative AI are delivered to employees.

[1127] "Employee Information" refers to data specific to each employee, such as profile information and work history about that employee.

[1128] "Push notification format" is a method of automatically sending important information and notifications to devices in real time.

[1129] "Security information" refers to data and knowledge about safety measures to protect companies and individuals.

[1130] "Training content" refers to educational programs and specific teaching materials that enable employees to continuously learn and improve their skills.

[1131] overview

[1132] This invention is a system that collects and processes data within a company and uses a generative AI model to provide optimal answers to inquiries from employees. It also has the function of providing necessary information based on employee information in the form of push notifications.

[1133] Server Processing

[1134] The server accesses the company's database and collects information such as internal regulations, business manuals, legal documents, security information, and training content. The collected information is converted into structured data (e.g., JSON or XML format). This is then input into the generative AI. The generative AI is trained based on the data and gains the ability to understand and process information.

[1135] Specific steps

[1136] 1. The server collects data within the company and inputs it into the generative AI as structured data.

[1137] 2. The server accepts inquiries from employees and sends the received inquiry data to the generation AI.

[1138] 3. The generation AI generates the optimal answer based on the input query and sends the answer back to the server.

[1139] 4. The server receives the generated response and notifies the employee's terminal.

[1140] 5. The server periodically reviews employee information and inputs it into the generation AI, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[1141] Terminal handling

[1142] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. Responses from the server are sent back to the device and displayed in the chat interface. Push notifications sent from the server are also displayed on the device for employees to review.

[1143] Hardware / Software used

[1144] Server: Uses Flask (a lightweight Python framework).

[1145] Data structuring: Use data in JSON or XML format.

[1146] Generative AI model: A custom-made generative AI (natural language processing model) in the AIModel class.

[1147] Device: Smartphone application (implemented using JavaScript).

[1148] Specific examples

[1149] Answers to employee questions

[1150] An employee types a question into a smartphone app: "What are the current security risks?" The server receives this question and sends it to the generation AI. The generation AI generates a specific answer, such as "The current major security risks are phishing attacks and ransomware," and sends it back to the server. The server then resends the answer to the device and displays it to the employee.

[1151] Providing information via push notifications

[1152] The server requests notification content from the generation AI at a specific time based on employee information. The generation AI generates a notification such as "Employee A is scheduled for new security training on 2023-01-15." The server sends this notification to the terminal and displays it to the employee.

[1153] Push notification prompt examples

[1154] "Please provide the latest security training content. Employee A was last trained as an engineer on 2022-12-01."

[1155] This system enables quick and efficient information provision within the company, providing support to employees to ensure the smooth running of their work.

[1156] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1157] Step 1:

[1158] The server accesses the company's internal database and collects the necessary information (e.g., company regulations, business manuals, legal documents, security information, training content, etc.). The collected information is converted into JSON or XML format and input into the generating AI. This allows the generating AI to absorb the company's internal information as training data and gain the ability to understand and process it. The input is the company's internal database, and the output is structured data (JSON or XML format).

[1159] Step 2:

[1160] The user uses the chat interface on the device to input a question or inquiry. For example, a question might be, "What are the current security risks?" This input data is sent to the server. The input is the user's question, and the output is the text data sent to the server.

[1161] Step 3:

[1162] The server sends the received question data to the generation AI, which generates the optimal answer from the company's internal data based on the received question. At this time, the generation AI uses database information previously input to create an accurate and effective answer. The input is the user's question, and the output is the generation AI's answer.

[1163] Step 4:

[1164] The answer generated by the generation AI is sent back to the server. The server receives this answer data, sends it back to the device, and provides it to the user. This allows the user to obtain accurate information quickly. The input is the answer from the generation AI, and the output is the answer displayed on the user's device.

[1165] Step 5:

[1166] The server periodically reviews employee information and inputs it into the Generator AI. This process allows the Generator AI to understand each employee's information and create notifications based on specific timing and events. The input is regularly updated employee information, and the output is new training data for the Generator AI.

[1167] Step 6:

[1168] The server requests notification content based on a specific timing or event (e.g., the date of a new security training session) from the generation AI. The generation AI creates the appropriate notification content to send based on employee information and related information. The input is the notification request from the server, and the output is the notification content created by the generation AI.

[1169] Step 7:

[1170] The notification content generated by the generation AI is sent back to the server. The server then sends this notification content to the device and provides the information to the user as a push notification. This allows the user to catch important information without missing it. The input is the notification content of the generation AI, and the output is the push notification that is displayed on the user's device.

[1171] 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.

[1172] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[1173] Server processing

[1174] The server accesses the company's database and collects the necessary information (company regulations, business manuals, legal documents, employee profile information). The collected information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained based on this data and gains the ability to understand and process the information.

[1175] Next, the server has the function of accepting inquiries from employees and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the employee's device and provides it to the employee. The server also periodically reviews employee information and inputs that information into the generation AI. This allows the generation AI to provide useful information to employees in the form of push notifications based on specific timing or events.

[1176] Processing by the terminal

[1177] The device provides a chat interface for employees to enter inquiries. Employees use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that employees can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[1178] Emotion engine processing

[1179] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[1180] User operations

[1181] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[1182] Specific examples

[1183] Answers to employee questions

[1184] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1185] 2. Terminal: The entered question is sent to the server as text data.

[1186] 3. Server: Sends the received query to the generation AI.

[1187] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1188] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1189] 6. Server: Receives the generated answer and sends it to the device.

[1190] 7. Terminal: Display the response in the chat interface and notify the user.

[1191] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[1192] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[1193] Providing information via push notifications

[1194] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1195] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[1196] 3. Generation AI: Sends the generated notification content back to the server.

[1197] 4. Server: Sends the push notification content received from the generation AI to the device.

[1198] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1199] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[1200] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[1201] 8. User: Check the push notification displayed on the device and take appropriate action.

[1202] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1203] The processing flow will be explained below.

[1204] Step 1:

[1205] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[1206] Step 2:

[1207] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[1208] Step 3:

[1209] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[1210] Step 4:

[1211] Terminal: The entered question is sent to the server as text data.

[1212] Step 5:

[1213] Server: Sends the received query content to the generation AI.

[1214] Step 6:

[1215] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[1216] Step 7:

[1217] Generation AI: Sends the generated answer text back to the server.

[1218] Step 8:

[1219] Server: Sends the answer text received from the generation AI to the device.

[1220] Step 9:

[1221] Terminal: Display the reply text in the user's chat interface.

[1222] Step 10:

[1223] Emotion engine: Analyzes the user's facial expressions and voice via the chat interface to determine the user's emotional state.

[1224] Step 11:

[1225] Emotion engine: Sends information to the generative AI based on the user's emotional state (e.g., if the user is feeling stressed, send that information).

[1226] Step 12:

[1227] Generative AI: Based on information from the emotion engine, it adjusts the content and wording of responses appropriately (e.g., responding in a gentler tone).

[1228] Step 13:

[1229] Terminal: Updates the adjusted response and displays it in the chat interface.

[1230] Step 14:

[1231] Server: Regularly reviews employee information and inputs it into the generation AI. For example, it collects and updates information such as employee title, department, and work history.

[1232] Step 15:

[1233] Generative AI: Generates push notification content based on employee information according to specific times and events.

[1234] Step 16:

[1235] Generation AI: Sends the generated push notification content back to the server.

[1236] Step 17:

[1237] Server: Sends the push notification content received from the generation AI to the device.

[1238] Step 18:

[1239] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[1240] Step 19:

[1241] Emotion engine: Analyzes the user's emotions when a push notification is displayed and sends that information to the generation AI as needed.

[1242] Step 20:

[1243] Generative AI: Tailors notification content and follow-up methods based on information from the emotion engine.

[1244] Step 21:

[1245] User: Check the push notification displayed on their device and take appropriate action.

[1246] Example 2

[1247] 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."

[1248] There is a growing need for systems that efficiently collect, provide, and respond to inquiries within companies. However, conventional systems have the problem of being difficult to provide personalized information that meets the needs of specific users or to respond to users' emotions. In particular, large organizations require information provision that takes into account the situation and emotions of each employee. The present invention aims to solve these problems and realize more efficient and personalized information provision and inquiry response within companies.

[1249] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for collecting data within the company, a means for inputting the collected data to the generation AI, and a means for accepting inquiries from users. This enables the generation AI to generate appropriate answers based on the collected data and provide them to the user. The server also includes a means for inputting user information to the generation AI, a means for using the user information to proactively provide necessary information in the form of push notifications, and an emotion engine for analyzing the user's emotions. This enables personalized information to be provided based on specific timing or events, and also enables responses that take the user's emotions into consideration.

[1250] "Means of collecting data within a company" refers to methods and devices for aggregating various documents and information managed within a company.

[1251] "Means for inputting collected data into generative AI" refers to methods or devices for providing collected data to generative AI, allowing it to learn and make it usable.

[1252] "Means for accepting queries from users" refers to a method or device that allows users to input questions or requests to the system.

[1253] "Means for sending received inquiries to the generation AI" refers to a method or device for sending inquiry data received from a user to the generation AI for analysis and response generation.

[1254] "Means by which a generation AI generates an optimal answer based on an inquiry" refers to a method or device by which a generation AI generates the most appropriate answer to a user's inquiry.

[1255] "Means for providing the generated answer to the user" refers to a method or device for providing the answer generated by the generation AI to the user.

[1256] "Means for inputting user information into the generation AI" refers to a method or device for providing information about the user to the generation AI, allowing it to learn and make it usable.

[1257] The term "means for proactively providing necessary information in the form of a push notification using user information" refers to a method or device for automatically providing information related to a user in the form of a push notification.

[1258] An "emotion engine that analyzes user emotions" refers to a device or software that analyzes a user's facial expressions, voice, etc. to determine their current emotional state.

[1259] "Means for requesting user information from a generation AI based on specific timing or events" refers to a method or device for requesting user information from a generation AI and processing it based on predetermined timing or events.

[1260] "Internal regulations" refers to documents that describe the business procedures and rules that apply within a company.

[1261] "Business procedures" refer to documents that describe the steps or methods to be followed to perform a particular task.

[1262] "Legal documents" refer to documents that contain information about laws and regulations that a company must comply with.

[1263] MODE FOR CARRYING OUT THE INVENTION

[1264] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to user inquiries. Furthermore, by inputting user information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[1265] Server processing

[1266] The server accesses the company's database and collects the necessary information (internal regulations, business procedures, legal documents, user profile information). This information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained on this data and gains the ability to understand and process the information.

[1267] Next, the server has the function of accepting inquiries from users and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the device and provides it to the user. The server also periodically reviews user information and inputs that information into the generation AI. This allows the generation AI to provide useful information to users in the form of push notifications based on specific timing or events.

[1268] Processing by the terminal

[1269] The device provides a chat interface for users to enter inquiries. Users use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that the user can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[1270] Emotion engine processing

[1271] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[1272] User operations

[1273] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they input a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing the user to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, the server automatically sends a push notification, which is displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[1274] Specific examples

[1275] Answers to employee questions

[1276] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1277] 2. Terminal: The entered question is sent to the server as text data.

[1278] 3. Server: Sends the received query to the generation AI.

[1279] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1280] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1281] 6. Server: Receives the generated answer and sends it to the device.

[1282] 7. Terminal: Display the response in the chat interface and notify the user.

[1283] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[1284] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[1285] Providing information via push notifications

[1286] 1. Server: Based on user information, the server requests push notification content from the generation AI according to specific timing or events.

[1287] 2. Generative AI: Creates appropriate notification content to send based on user information and related information.

[1288] 3. Generation AI: Sends the generated notification content back to the server.

[1289] 4. Server: Sends the push notification content received from the generation AI to the device.

[1290] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1291] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[1292] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[1293] 8. User: Check the push notification displayed on the device and take appropriate action.

[1294] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1295] Prompt Sentence Examples

[1296] 1. "Tell me about the new vacation policy."

[1297] 2. "Show me a list of my important tasks for this week."

[1298] 3. "Please provide information on the latest legal changes."

[1299] 4. "What are some of the important events at your company this month?"

[1300] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1301] Explaining the program's processing in detail

[1302] Divide the process flow into steps

[1303] Step 1:

[1304] The server accesses the company's internal database and collects the necessary data. The collected data includes internal regulations, business procedures, legal documents, and user (employee) profile information. This data is converted into structured data (e.g., JSON format, XML format). The input is database information, and the output is structured data.

[1305] Step 2:

[1306] The server inputs structured data into the generative AI, which then trains itself based on the data it receives, allowing it to understand and process information. The input is structured data, and the output is training data for the generative AI.

[1307] Step 3:

[1308] The user inputs a query into the chat interface on the device. For example, if the user inputs "Tell me about the new vacation system," text data is generated. The input is the user's query, and the output is text data.

[1309] Step 4:

[1310] The terminal sends the text data entered by the user to the server. The server then sends the received query to the generation AI. The input is text data, and the output is query data for the generation AI.

[1311] Step 5:

[1312] Generative AI generates optimal answers based on the inquiries it receives. It uses training data to analyze the inquiry content and generate optimal answers. The input is inquiry data, and the output is answer data.

[1313] Step 6:

[1314] The generation AI sends the generated answer back to the server. The server then sends the received answer to the terminal and provides it to the user. The input is the answer data from the generation AI, and the output is the answer sent to the user.

[1315] Step 7:

[1316] The terminal displays the response sent from the server in the chat interface, and the user can check the response. The input is the response data from the server, and the output is the display content of the chat interface.

[1317] Step 8:

[1318] The server periodically reviews user information and inputs it into the generation AI. This allows the generation AI to proactively provide necessary information to users in the form of push notifications. The input is user information, and the output is the generation AI's input data.

[1319] Step 9:

[1320] The server requests push notification content from the generation AI based on specific timing or events. The generation AI analyzes user information and related information and generates appropriate notification content. The input is the push notification request, and the output is the notification content.

[1321] Step 10:

[1322] The server sends the notification content obtained from the generation AI to the device, which displays it to the user as a push notification. The input is the notification content from the generation AI, and the output is the push notification on the device.

[1323] Step 11:

[1324] The emotion engine installed in the device analyzes emotions from the user's facial expressions and voice and inputs the results into the generative AI. The input is the user's facial expressions and voice data, and the output is the analyzed emotional data.

[1325] Step 12:

[1326] The generative AI adjusts the content of responses and push notifications based on the emotional data obtained from the emotion engine. The input is emotional data, and the output is the adjusted response or notification content.

[1327] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1328] (Application example 2)

[1329] 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."

[1330] Within a company, employees need to obtain information quickly and accurately, but conventional systems make it difficult to easily obtain the necessary information. In factories, there is also a need to quickly share information such as operational status and malfunction information, but existing methods are insufficient for providing information in real time. Furthermore, there is a demand for personalized responses that take user emotions into account, but the technology to achieve this is lacking.

[1331] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information to the generation AI, means for using the employee information to proactively provide necessary information in the form of push notifications, means for collecting data within the factory and responding to inquiries from workers using the generation AI, and means for providing push notifications to factory robots and analyzing their emotions. This not only enables employees to quickly and accurately obtain the information they need, but also enables real-time information sharing within the factory and personalized responses that take user emotions into consideration.

[1332] "Internal corporate data" refers to all information related to the operation of a company, including, for example, internal regulations, business manuals, and legal documents.

[1333] "Generative AI" refers to a system that uses artificial intelligence technology to generate optimal answers or information from input data.

[1334] "Employee information" refers to individual information about individual employees, such as profile information and work history.

[1335] "Push Notification" means a notification that is sent automatically by the system without the user explicitly requesting it.

[1336] "Factory data" refers to information related to factory operations and production, including operational status, machine status, and quality control data.

[1337] An "inquiry" refers to a question or request for information made by a user (employee or worker) to the system.

[1338] "Emotion analysis" refers to the technology of analyzing a user's emotions from their facial expressions, voice, etc.

[1339] A specific embodiment for carrying out the present invention will be described.

[1340] First, a database management system (e.g., MySQL or PostgreSQL) is used to collect data within the company. Data is automatically collected from each system within the company and stored in the database. The collected data includes internal regulations, business manuals, legal documents, employee profile information, operation status, machine status, quality control data, etc.

[1341] The server converts the collected data into structured data in JSON or XML format and inputs it into a generative AI (for example, OpenAI's GPT model). The generative AI is trained based on this data and gains the ability to generate optimal answers to inquiries. The server also requests employee information from the generative AI based on specific timing or events and provides the required information in the form of push notifications.

[1342] Users (employees and workers) input inquiries using the chat interface installed on their devices. The inquiries are sent as text data to the server and processed by the generation AI. For example, if a user inputs "Tell me about the new vacation system," the generation AI searches for relevant information in the company's database and generates the most appropriate answer. The generated answer is sent to the device via the server and displayed on the chat interface.

[1343] Data from within the factory is also collected and input into the generative AI. The factory robot responds to inquiries from workers and provides real-time machine status and fault information. For example, if a worker inputs, "Machine 102 has broken down. Please tell me how to fix it," the generative AI will provide a response procedure.

[1344] This system is equipped with an emotion engine (such as Affectiva or Microsoft Azure Emotion API) that analyzes emotions from the user's facial expressions and voice. The analyzed emotion data is fed back to the AI ​​generator, which then personalizes the responses and notifications.

[1345] For example, if a user types "What is the status of Line 3?" into the chat interface on their device, the generated AI will respond with "Line 3 is currently running, the set temperature is 75 degrees, and it has been running for two hours. The next maintenance is scheduled for 2:00 PM." Similarly, if a worker types "Machine 102 has broken down. What should I do?", the generated AI will respond with "There are three possible causes for Machine 102's failure: 1) excessive temperature, 2) worn parts, and 3) overload. To resolve the issue, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload."

[1346] In this way, it is possible to provide information quickly and accurately within a company or factory, and it is also possible to provide personalized responses that take into account the user's feelings.

[1347] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1348] Step 1:

[1349] The server automatically collects data from various systems within the company and factory (e.g., operation control systems, quality control systems, user information systems). This data includes company regulations, work manuals, legal documents, operation status, machine status, quality control data, etc. The collected data is stored in a database.

[1350] Step 2:

[1351] The server converts the collected data into structured data in JSON or XML format, which is then fed into a generative AI (such as OpenAI's GPT model), which trains itself on the input data to improve its ability to generate optimal answers to queries.

[1352] Step 3:

[1353] Users (employees and workers) use the chat interface on their devices to input inquiries. For example, they might type, "Tell me about the new vacation system." The input inquiry is sent to the server as text data.

[1354] Step 4:

[1355] The server sends the text data received from the user to the generation AI, which analyzes the inquiry and searches for relevant information in the company's and factory's databases. Based on the search results, the AI ​​generates the optimal answer.

[1356] Step 5:

[1357] The AI ​​then sends the generated answer back to the server, which then sends the answer back to the device and displays it in the chat interface. For example, a specific answer such as "Under the new vacation system, you can now take 10 more days of vacation per fiscal year" is displayed.

[1358] Step 6:

[1359] The server requests employee information from the generation AI based on specific timing or events, and provides the necessary information in the form of a push notification, such as "New security training is scheduled soon."

[1360] Step 7:

[1361] The device displays the push notification to the user, who then checks and responds to the displayed notification. For example, a user who receives a notification about security training checks the training details.

[1362] Step 8:

[1363] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The analysis results are sent to a server, and the generation AI uses that information to adjust the content of responses and push notifications. For example, if the user expresses negative emotions, the generation AI will provide softer language and encouraging messages.

[1364] Step 9:

[1365] When a user types, "Machine 102 has broken down. Please tell me how to deal with this," the generated AI will respond, "There are three possible causes for the breakdown of Machine 102: 1) excessive temperature, 2) worn parts, and 3) overload. To deal with this, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload." In this way, quick and accurate information provision within the factory is achieved.

[1366] 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.

[1367] 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.

[1368] 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.

[1369] [Fourth embodiment]

[1370] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1371] 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.

[1372] 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).

[1373] 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.

[1374] 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.

[1375] 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).

[1376] 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.

[1377] 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.

[1378] 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.

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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."

[1383] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[1384] Server processing

[1385] The server accesses the company's internal database and collects the necessary information, including company regulations, business manuals, and legal documents. The server converts this information into structured data (e.g., JSON or XML format) and inputs it into the generation AI.

[1386] The generation AI is trained based on the data it receives, and gains the ability to understand and process that information. Next, the server has the function of accepting inquiries from employees and sending the received inquiries to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer back to the terminal to provide it to the employee.

[1387] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[1388] Processing by the terminal

[1389] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, which are then sent to the server. When the server returns a response, the device displays it in the chat interface. Additionally, push notifications sent from the server are also displayed on the device for employees to review.

[1390] User operations

[1391] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they type a question like "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Employees can check this notification and take the necessary action.

[1392] Specific examples

[1393] Answers to employee questions

[1394] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1395] 2. Terminal: The entered question is sent to the server as text data.

[1396] 3. Server: Sends the received text data to the generation AI.

[1397] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1398] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1399] 6. Server: Receives the generated answer and sends it to the device.

[1400] 7. Terminal: Display the response in the chat interface and notify the user.

[1401] Providing information via push notifications

[1402] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1403] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[1404] 3. Generation AI: Sends the generated notification content back to the server.

[1405] 4. Server: Sends the notification content received from the generation AI to the device.

[1406] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1407] 6. User: Check the push notification that appears on their device.

[1408] By implementing this system, information can be provided quickly and efficiently within the company, and employees can receive support to carry out their work smoothly.

[1409] The processing flow will be explained below.

[1410] Step 1:

[1411] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[1412] Step 2:

[1413] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[1414] Step 3:

[1415] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[1416] Step 4:

[1417] Terminal: The entered question is sent to the server as text data.

[1418] Step 5:

[1419] Server: Sends the received query content to the generation AI.

[1420] Step 6:

[1421] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[1422] Step 7:

[1423] Generation AI: Sends the generated answer text back to the server.

[1424] Step 8:

[1425] Server: Sends the answer text received from the generation AI to the device.

[1426] Step 9:

[1427] Terminal: Display the reply text in the user's chat interface.

[1428] Step 10:

[1429] User: Review the answer provided (e.g., "The new vacation policy allows you to take 10 more vacation days per year") and get the information you need.

[1430] Step 11:

[1431] Server: Regularly reviews employee information and inputs it into the generation AI, such as employee title, department, and work history.

[1432] Step 12:

[1433] Generative AI: Generates push notification content based on employee and related information, tailored to specific times and events.

[1434] Step 13:

[1435] Generation AI: Sends the generated push notification content back to the server.

[1436] Step 14:

[1437] Server: Sends the push notification content received from the generation AI to the device.

[1438] Step 15:

[1439] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[1440] Step 16:

[1441] User: Check the push notification displayed on their device and take appropriate action.

[1442] Example 1

[1443] 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."

[1444] In companies, a large amount of information is generated every day, making it difficult for employees to quickly obtain the information they need. Also, delayed responses to employee inquiries can lead to reduced work efficiency. Furthermore, if information is not provided appropriately at specific times or for specific events, there is a risk that important tasks or information will be overlooked. These problems need to be solved.

[1445] 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.

[1446] In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI in a structured data format, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate an optimal answer based on the inquiry, means for providing the generated answer to employees, means for inputting employee information to the generation AI, and means for proactively providing necessary information in the form of push notifications using the employee information. This enables employees to quickly obtain the information they need, provides prompt answers to their inquiries, and makes it possible to provide appropriate information according to specific timing or events.

[1447] "Methods of collecting data within an enterprise" are the processes and techniques used to obtain information stored in the enterprise's databases.

[1448] "Means for inputting collected data into generative AI in structured data format" refers to the processes and technologies for converting collected data into structured data such as JSON or XML format and inputting it into generative AI.

[1449] "Means for accepting inquiries from employees" refers to the interface or technology that allows employees to input questions or concerns into the system.

[1450] "Means for sending received inquiries to the generation AI" refers to the process or technology for sending the inquiry data received from employees to the generation AI.

[1451] "Means by which generative AI generates optimal answers based on inquiries" refers to the process or technology by which generative AI analyzes the inquiries it receives and generates optimal answers in response to them.

[1452] "Means of providing the generated answers to employees" refers to the process or technology used to communicate the answers returned by the generating AI to employees.

[1453] "Means for inputting employee information into the generative AI" refers to the processes and technologies for inputting information about employees into the generative AI so that the information can be analyzed and used.

[1454] "Means of proactively providing necessary information in the form of push notifications using employee information" refers to the process and technology that allows AI generated based on employee information to provide information in the form of push notifications according to specific times or events.

[1455] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it also has the function of providing necessary information in advance in the form of push notifications.

[1456] Server processing

[1457] The server accesses the company's internal database and collects the necessary information (e.g., internal regulations, business manuals, and legal documents). This data collection is done using a database management system such as MySQL or PostgreSQL. After obtaining the data, the server uses a Python program to convert the collected data into JSON or XML format. The converted data is then input into the generative AI.

[1458] The generative AI is trained based on the data it receives using OpenAI's GPT model, for example. Through training, the generative AI improves its ability to understand and process data. The server then receives inquiries from employees and sends them to the generative AI. The generative AI analyzes the inquiry, generates the optimal answer, and sends it back to the server. The server then sends this answer back to the employee's device to provide it to them again.

[1459] In addition, the server periodically reviews employee information and inputs it into the AI ​​generator, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[1460] Processing by the terminal

[1461] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. When the server returns a response, the device displays the response in the chat interface. Push notifications from the server are also displayed on the device for employees to review.

[1462] User operations

[1463] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generative AI generates the optimal answer, which is then displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Users can check this notification and take the necessary action.

[1464] Specific examples

[1465] Answers to employee questions

[1466] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1467] 2. Terminal: The entered question is sent to the server as text data.

[1468] 3. Server: Sends the received text data to the generation AI.

[1469] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1470] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1471] 6. Server: Receives the generated answer and sends it to the device.

[1472] 7. Terminal: Display the response in the chat interface and notify the user.

[1473] Providing information via push notifications

[1474] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1475] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[1476] 3. Generation AI: Sends the generated notification content back to the server.

[1477] 4. Server: Sends the notification content received from the generation AI to the device.

[1478] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1479] 6. User: Check the push notification that appears on their device.

[1480] Example prompts for generative AI models

[1481] "Tell me about the new vacation policy."

[1482] "What are the updates regarding the operations manual this month?"

[1483] "Please show me the latest legal documents."

[1484] The above is an embodiment of this system. This system enables quick and efficient information provision within a company, and employees can receive support to smoothly carry out their work.

[1485] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1486] Step 1:

[1487] Server: Connects to a corporate database.

[1488] Input: Database connection information (e.g. hostname, port number, username, password)

[1489] What it does: Establishes a connection with a database management system (e.g. MySQL, PostgreSQL).

[1490] Output: Database connection object

[1491] Step 2:

[1492] Server: Obtains necessary information (e.g., company regulations, business manuals, legal documents).

[1493] Input: Database query (e.g. SQL statement)

[1494] What it does: It uses the connection object to execute SQL queries and retrieve the required data.

[1495] Output: Result set (e.g., vacation system, work manual)

[1496] Step 3:

[1497] Server: Converts the retrieved information into a structured data format (JSON or XML).

[1498] Input: Retrieve result set

[1499] What it does: Uses a Python program to convert data into JSON and XML formats.

[1500] Output: Structured data (e.g., vacation policy information in JSON format)

[1501] Step 4:

[1502] Server: Inputs structured data into the generative AI.

[1503] Input: Structured data

[1504] How it works: Sends data to a generative AI model (e.g., a GPT model) using an HTTP request.

[1505] Output: Stored as training data for the generative AI

[1506] Step 5:

[1507] User: Type a question into the chat interface on the device.

[1508] Input: Text data entered into the chat interface (e.g., "Tell me about the new vacation policy.")

[1509] How it works: The chat interface sends data to the server via JavaScript.

[1510] Output: Query data is sent to the server

[1511] Step 6:

[1512] Terminal: Sends the entered question to the server.

[1513] Input: Text data

[1514] What it does: Sends the form data to the server as an HTTP request.

[1515] Output: Received by the server

[1516] Step 7:

[1517] Server: Sends the received questions to the generation AI.

[1518] Input: Received text data

[1519] Action: Sends text data to the generating AI, requesting it to process the query.

[1520] Output: Generative AI receives the question

[1521] Step 8:

[1522] Generative AI: Generates the best answer based on the inquiry.

[1523] Input: Received text data

[1524] How it works: The AI ​​model analyzes the data and generates the best answer.

[1525] Output: Generated answer (e.g. "The new vacation policy allows you to take 10 more vacation days per year.")

[1526] Step 9:

[1527] Generation AI: Sends the generated answer back to the server.

[1528] Input: Generated answer

[1529] What it does: Sends the output of the AI ​​model to a server.

[1530] Output: The server receives the generated answer

[1531] Step 10:

[1532] Server: Sends the generated answer to the device.

[1533] Input: Generated answer

[1534] Behavior: Sends response data to the device using an HTTP response.

[1535] Output: The answer is sent to the terminal

[1536] Step 11:

[1537] Terminal: Display the response in the chat interface and notify the user.

[1538] Input: Generated answer data

[1539] What it does: Displays the reply in the chat interface via JavaScript.

[1540] Output: The answer is displayed to the user

[1541] Step 12:

[1542] Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1543] Input: Employee information (e.g., profile data) and timing information

[1544] Behavior: Sends a notification request to the generating AI.

[1545] Output: Notification content generated by the generation AI

[1546] Step 13:

[1547] Generative AI: Creates appropriate notifications to send based on employee information and related information.

[1548] Input: Employee information and timing information

[1549] How it works: AI models generate optimal notification content.

[1550] Output: Notification content is generated

[1551] Step 14:

[1552] Generation AI: Sends the generated notification content back to the server.

[1553] Input: Generated notification content

[1554] What it does: Sends the output of the AI ​​model to a server.

[1555] Output: The server receives the generated notification

[1556] Step 15:

[1557] Server: Sends the notification content received from the generation AI to the device.

[1558] Input: Generated notification content

[1559] Behavior: Sends notification data to the device using an HTTP response.

[1560] Output: A notification is sent to the device

[1561] Step 16:

[1562] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[1563] Input: Notification data

[1564] What it does: Displays a push notification popup via JavaScript.

[1565] Output: A notification is displayed to the user

[1566] (Application example 1)

[1567] 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."

[1568] In order to raise security awareness among employees in a company, it is important to effectively provide the latest security information and training content. However, with conventional methods, it is difficult to provide information customized to the needs of each employee, which means that security education is not as effective as it could be.

[1569] 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.

[1570] In this invention, the server includes means for collecting data within the company, means for inputting the collected data into the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information into the generation AI, means for proactively providing necessary information in the form of push notifications using the employee information, and means for customizing and providing security information and training content to individual employees based on the generation AI. This makes it possible to provide the latest security information and training content to individual employees in a timely manner and according to their needs.

[1571] "Internal corporate data" encompasses all information generated and collected internally by a company, including internal regulations, business manuals, and legal documents.

[1572] "Generative AI" is a system that uses artificial intelligence technology to generate optimal answers and information from input data.

[1573] "Employee inquiries" are questions asked by employees to obtain work-related information or to clarify business-related questions.

[1574] "Means of sending inquiries to the generation AI" refers to the process of forwarding questions from employees to the generation AI, which then generates the optimal answer to that question.

[1575] The "optimal answer" refers to the accurate and effective information that the generative AI outputs in response to an employee inquiry.

[1576] "Means of providing to employees" refers to the method by which the answers and information output by the generative AI are delivered to employees.

[1577] "Employee Information" refers to data specific to each employee, such as profile information and work history about that employee.

[1578] "Push notification format" is a method of automatically sending important information and notifications to devices in real time.

[1579] "Security information" refers to data and knowledge about safety measures to protect companies and individuals.

[1580] "Training content" refers to educational programs and specific teaching materials that enable employees to continuously learn and improve their skills.

[1581] overview

[1582] This invention is a system that collects and processes data within a company and uses a generative AI model to provide optimal answers to inquiries from employees. It also has the function of providing necessary information based on employee information in the form of push notifications.

[1583] Server Processing

[1584] The server accesses the company's database and collects information such as internal regulations, business manuals, legal documents, security information, and training content. The collected information is converted into structured data (e.g., JSON or XML format). This is then input into the generative AI. The generative AI is trained based on the data and gains the ability to understand and process information.

[1585] Specific steps

[1586] 1. The server collects data within the company and inputs it into the generative AI as structured data.

[1587] 2. The server accepts inquiries from employees and sends the received inquiry data to the generation AI.

[1588] 3. The generation AI generates the optimal answer based on the input query and sends the answer back to the server.

[1589] 4. The server receives the generated response and notifies the employee's terminal.

[1590] 5. The server periodically reviews employee information and inputs it into the generation AI, which can then provide useful information to employees in the form of push notifications based on specific timing or events.

[1591] Terminal handling

[1592] The device provides a chat interface for employees to enter their inquiries. Employees use this interface to enter their questions, and the data is sent to the server. Responses from the server are sent back to the device and displayed in the chat interface. Push notifications sent from the server are also displayed on the device for employees to review.

[1593] Hardware / Software used

[1594] Server: Uses Flask (a lightweight Python framework).

[1595] Data structuring: Use data in JSON or XML format.

[1596] Generative AI model: A custom-made generative AI (natural language processing model) in the AIModel class.

[1597] Device: Smartphone application (implemented using JavaScript).

[1598] Specific examples

[1599] Answers to employee questions

[1600] An employee types a question into a smartphone app: "What are the current security risks?" The server receives this question and sends it to the generation AI. The generation AI generates a specific answer, such as "The current major security risks are phishing attacks and ransomware," and sends it back to the server. The server then resends the answer to the device and displays it to the employee.

[1601] Providing information via push notifications

[1602] The server requests notification content from the generation AI at a specific time based on employee information. The generation AI generates a notification such as "Employee A is scheduled for new security training on 2023-01-15." The server sends this notification to the terminal and displays it to the employee.

[1603] Push notification prompt examples

[1604] "Please provide the latest security training content. Employee A was last trained as an engineer on 2022-12-01."

[1605] This system enables quick and efficient information provision within the company, providing support to employees to ensure the smooth running of their work.

[1606] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1607] Step 1:

[1608] The server accesses the company's internal database and collects the necessary information (e.g., company regulations, business manuals, legal documents, security information, training content, etc.). The collected information is converted into JSON or XML format and input into the generating AI. This allows the generating AI to absorb the company's internal information as training data and gain the ability to understand and process it. The input is the company's internal database, and the output is structured data (JSON or XML format).

[1609] Step 2:

[1610] The user uses the chat interface on the device to input a question or inquiry. For example, a question might be, "What are the current security risks?" This input data is sent to the server. The input is the user's question, and the output is the text data sent to the server.

[1611] Step 3:

[1612] The server sends the received question data to the generation AI, which generates the optimal answer from the company's internal data based on the received question. At this time, the generation AI uses database information previously input to create an accurate and effective answer. The input is the user's question, and the output is the generation AI's answer.

[1613] Step 4:

[1614] The answer generated by the generation AI is sent back to the server. The server receives this answer data, sends it back to the device, and provides it to the user. This allows the user to obtain accurate information quickly. The input is the answer from the generation AI, and the output is the answer displayed on the user's device.

[1615] Step 5:

[1616] The server periodically reviews employee information and inputs it into the Generator AI. This process allows the Generator AI to understand each employee's information and create notifications based on specific timing and events. The input is regularly updated employee information, and the output is new training data for the Generator AI.

[1617] Step 6:

[1618] The server requests notification content based on a specific timing or event (e.g., the date of a new security training session) from the generation AI. The generation AI creates the appropriate notification content to send based on employee information and related information. The input is the notification request from the server, and the output is the notification content created by the generation AI.

[1619] Step 7:

[1620] The notification content generated by the generation AI is sent back to the server. The server then sends this notification content to the device and provides the information to the user as a push notification. This allows the user to catch important information without missing it. The input is the notification content of the generation AI, and the output is the push notification that is displayed on the user's device.

[1621] 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.

[1622] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to inquiries from employees. Furthermore, by inputting employee information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[1623] Server processing

[1624] The server accesses the company's database and collects the necessary information (company regulations, business manuals, legal documents, employee profile information). The collected information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained based on this data and gains the ability to understand and process the information.

[1625] Next, the server has the function of accepting inquiries from employees and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the employee's device and provides it to the employee. The server also periodically reviews employee information and inputs that information into the generation AI. This allows the generation AI to provide useful information to employees in the form of push notifications based on specific timing or events.

[1626] Processing by the terminal

[1627] The device provides a chat interface for employees to enter inquiries. Employees use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that employees can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[1628] Emotion engine processing

[1629] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[1630] User operations

[1631] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they enter a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing employees to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, a push notification is automatically sent from the server and displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[1632] Specific examples

[1633] Answers to employee questions

[1634] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1635] 2. Terminal: The entered question is sent to the server as text data.

[1636] 3. Server: Sends the received query to the generation AI.

[1637] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1638] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1639] 6. Server: Receives the generated answer and sends it to the device.

[1640] 7. Terminal: Display the response in the chat interface and notify the user.

[1641] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[1642] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[1643] Providing information via push notifications

[1644] 1. Server: Based on employee information, the server requests push notification content from the generation AI according to specific times and events.

[1645] 2. Generative AI: Creates appropriate notification content to send based on employee information and related information.

[1646] 3. Generation AI: Sends the generated notification content back to the server.

[1647] 4. Server: Sends the push notification content received from the generation AI to the device.

[1648] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1649] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[1650] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[1651] 8. User: Check the push notification displayed on the device and take appropriate action.

[1652] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1653] The processing flow will be explained below.

[1654] Step 1:

[1655] Server: Accesses the company's database and collects necessary information (company regulations, business manuals, legal documents, employee profile information).

[1656] Step 2:

[1657] Server: Converts the collected information into structured data (e.g., JSON or XML format) and inputs it into the generation AI, which uses this data as training data.

[1658] Step 3:

[1659] User: Type a question into the device's chat interface (e.g., "Tell me about the new vacation policy").

[1660] Step 4:

[1661] Terminal: The entered question is sent to the server as text data.

[1662] Step 5:

[1663] Server: Sends the received query content to the generation AI.

[1664] Step 6:

[1665] Generative AI: Processes the questions sent to it and generates the best answer from the information collected.

[1666] Step 7:

[1667] Generation AI: Sends the generated answer text back to the server.

[1668] Step 8:

[1669] Server: Sends the answer text received from the generation AI to the device.

[1670] Step 9:

[1671] Terminal: Display the reply text in the user's chat interface.

[1672] Step 10:

[1673] Emotion engine: Analyzes the user's facial expressions and voice via the chat interface to determine the user's emotional state.

[1674] Step 11:

[1675] Emotion engine: Sends information to the generative AI based on the user's emotional state (e.g., if the user is feeling stressed, send that information).

[1676] Step 12:

[1677] Generative AI: Based on information from the emotion engine, it adjusts the content and wording of responses appropriately (e.g., responding in a gentler tone).

[1678] Step 13:

[1679] Terminal: Updates the adjusted response and displays it in the chat interface.

[1680] Step 14:

[1681] Server: Regularly reviews employee information and inputs it into the generation AI. For example, it collects and updates information such as employee title, department, and work history.

[1682] Step 15:

[1683] Generative AI: Generates push notification content based on employee information according to specific times and events.

[1684] Step 16:

[1685] Generation AI: Sends the generated push notification content back to the server.

[1686] Step 17:

[1687] Server: Sends the push notification content received from the generation AI to the device.

[1688] Step 18:

[1689] On the device: Displayed to the user as a push notification (e.g., "New security training coming soon.").

[1690] Step 19:

[1691] Emotion engine: Analyzes the user's emotions when a push notification is displayed and sends that information to the generation AI as needed.

[1692] Step 20:

[1693] Generative AI: Tailors notification content and follow-up methods based on information from the emotion engine.

[1694] Step 21:

[1695] User: Check the push notification displayed on their device and take appropriate action.

[1696] Example 2

[1697] 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."

[1698] There is a growing need for systems that efficiently collect, provide, and respond to inquiries within companies. However, conventional systems have the problem of being difficult to provide personalized information that meets the needs of specific users or to respond to users' emotions. In particular, large organizations require information provision that takes into account the situation and emotions of each employee. The present invention aims to solve these problems and realize more efficient and personalized information provision and inquiry response within companies.

[1699] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for collecting data within the company, a means for inputting the collected data to the generation AI, and a means for accepting inquiries from users. This enables the generation AI to generate appropriate answers based on the collected data and provide them to the user. The server also includes a means for inputting user information to the generation AI, a means for using the user information to proactively provide necessary information in the form of push notifications, and an emotion engine for analyzing the user's emotions. This enables personalized information to be provided based on specific timing or events, and also enables responses that take the user's emotions into consideration.

[1700] "Means of collecting data within a company" refers to methods and devices for aggregating various documents and information managed within a company.

[1701] "Means for inputting collected data into generative AI" refers to methods or devices for providing collected data to generative AI, allowing it to learn and make it usable.

[1702] "Means for accepting queries from users" refers to a method or device that allows users to input questions or requests to the system.

[1703] "Means for sending received inquiries to the generation AI" refers to a method or device for sending inquiry data received from a user to the generation AI for analysis and response generation.

[1704] "Means by which a generation AI generates an optimal answer based on an inquiry" refers to a method or device by which a generation AI generates the most appropriate answer to a user's inquiry.

[1705] "Means for providing the generated answer to the user" refers to a method or device for providing the answer generated by the generation AI to the user.

[1706] "Means for inputting user information into the generation AI" refers to a method or device for providing information about the user to the generation AI, allowing it to learn and make it usable.

[1707] The term "means for proactively providing necessary information in the form of a push notification using user information" refers to a method or device for automatically providing information related to a user in the form of a push notification.

[1708] An "emotion engine that analyzes user emotions" refers to a device or software that analyzes a user's facial expressions, voice, etc. to determine their current emotional state.

[1709] "Means for requesting user information from a generation AI based on specific timing or events" refers to a method or device for requesting user information from a generation AI and processing it based on predetermined timing or events.

[1710] "Internal regulations" refers to documents that describe the business procedures and rules that apply within a company.

[1711] "Business procedures" refer to documents that describe the steps or methods to be followed to perform a particular task.

[1712] "Legal documents" refer to documents that contain information about laws and regulations that a company must comply with.

[1713] MODE FOR CARRYING OUT THE INVENTION

[1714] This invention is a system that collects data within a company, inputs the collected data into a generation AI, and provides optimal answers to user inquiries. Furthermore, by inputting user information into the generation AI, it is possible to provide necessary information in advance in the form of push notifications, and by combining this with an emotion engine that recognizes user emotions, it is possible to provide more personalized information.

[1715] Server processing

[1716] The server accesses the company's database and collects the necessary information (internal regulations, business procedures, legal documents, user profile information). This information is converted into structured data (e.g., JSON or XML format) and input into the generating AI. The generating AI is trained on this data and gains the ability to understand and process the information.

[1717] Next, the server has the function of accepting inquiries from users and sending them to the generation AI. The generation AI generates the optimal answer based on the input inquiry and sends the generated answer back to the server. The server then sends the received answer to the device and provides it to the user. The server also periodically reviews user information and inputs that information into the generation AI. This allows the generation AI to provide useful information to users in the form of push notifications based on specific timing or events.

[1718] Processing by the terminal

[1719] The device provides a chat interface for users to enter inquiries. Users use this interface to enter questions, and the data is sent to the server. When a response is returned from the server, the device displays it in the chat interface. In addition, push notifications sent from the server are also displayed on the device so that the user can check them. The device is also equipped with an emotion engine that recognizes the user's emotions and analyzes them in real time.

[1720] Emotion engine processing

[1721] The emotion engine installed on the device analyzes the user's emotions from their facial expressions and voice and inputs the results into the generation AI, which can then adjust the content of responses and push notifications based on the user's current emotions.

[1722] User operations

[1723] Users (employees) can use their devices to ask work-related questions in chat format. For example, if they input a question such as "Tell me about the new vacation system," the data is sent to the server. The generation AI generates the optimal answer, which is displayed on the device, allowing the user to quickly obtain the information. In addition, if there is important information or a task that must not be forgotten, the server automatically sends a push notification, which is displayed on the device. Furthermore, if the user's emotions are negative, the generation AI uses that information to provide softer language and encouraging messages.

[1724] Specific examples

[1725] Answers to employee questions

[1726] 1. User: Type "Tell me about the new vacation policy" into the device's chat interface.

[1727] 2. Terminal: The entered question is sent to the server as text data.

[1728] 3. Server: Sends the received query to the generation AI.

[1729] 4. Generative AI: Searches for information about company leave policies and generates the best answer.

[1730] 5. Generative AI: Generates a specific answer such as, "Under the new vacation system, the number of vacation days that can be taken within the fiscal year has increased by 10 days," and sends it back to the server.

[1731] 6. Server: Receives the generated answer and sends it to the device.

[1732] 7. Terminal: Display the response in the chat interface and notify the user.

[1733] 8. Emotion Engine: Analyzes the user's emotions and if negative emotions are recognized, sends that information to the generative AI.

[1734] 9. Generative AI: Adjusts the content and expression of responses based on information from the emotion engine.

[1735] Providing information via push notifications

[1736] 1. Server: Based on user information, the server requests push notification content from the generation AI according to specific timing or events.

[1737] 2. Generative AI: Creates appropriate notification content to send based on user information and related information.

[1738] 3. Generation AI: Sends the generated notification content back to the server.

[1739] 4. Server: Sends the push notification content received from the generation AI to the device.

[1740] 5. On the device: Display this as a push notification to the user (e.g., "New security training coming soon.").

[1741] 6. Emotion Engine: Analyzes the user's emotions when the push notification is displayed and sends that information to the generation AI as needed.

[1742] 7. Generative AI: Tailor the content of notifications and follow-up methods based on information from the emotion engine.

[1743] 8. User: Check the push notification displayed on the device and take appropriate action.

[1744] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1745] Prompt Sentence Examples

[1746] 1. "Tell me about the new vacation policy."

[1747] 2. "Show me a list of my important tasks for this week."

[1748] 3. "Please provide information on the latest legal changes."

[1749] 4. "What are some of the important events at your company this month?"

[1750] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1751] Explaining the program's processing in detail

[1752] Divide the process flow into steps

[1753] Step 1:

[1754] The server accesses the company's internal database and collects the necessary data. The collected data includes internal regulations, business procedures, legal documents, and user (employee) profile information. This data is converted into structured data (e.g., JSON format, XML format). The input is database information, and the output is structured data.

[1755] Step 2:

[1756] The server inputs structured data into the generative AI, which then trains itself based on the data it receives, allowing it to understand and process information. The input is structured data, and the output is training data for the generative AI.

[1757] Step 3:

[1758] The user inputs a query into the chat interface on the device. For example, if the user inputs "Tell me about the new vacation system," text data is generated. The input is the user's query, and the output is text data.

[1759] Step 4:

[1760] The terminal sends the text data entered by the user to the server. The server then sends the received query to the generation AI. The input is text data, and the output is query data for the generation AI.

[1761] Step 5:

[1762] Generative AI generates optimal answers based on the inquiries it receives. It uses training data to analyze the inquiry content and generate optimal answers. The input is inquiry data, and the output is answer data.

[1763] Step 6:

[1764] The generation AI sends the generated answer back to the server. The server then sends the received answer to the terminal and provides it to the user. The input is the answer data from the generation AI, and the output is the answer sent to the user.

[1765] Step 7:

[1766] The terminal displays the response sent from the server in the chat interface, and the user can check the response. The input is the response data from the server, and the output is the display content of the chat interface.

[1767] Step 8:

[1768] The server periodically reviews user information and inputs it into the generation AI. This allows the generation AI to proactively provide necessary information to users in the form of push notifications. The input is user information, and the output is the generation AI's input data.

[1769] Step 9:

[1770] The server requests push notification content from the generation AI based on specific timing or events. The generation AI analyzes user information and related information and generates appropriate notification content. The input is the push notification request, and the output is the notification content.

[1771] Step 10:

[1772] The server sends the notification content obtained from the generation AI to the device, which displays it to the user as a push notification. The input is the notification content from the generation AI, and the output is the push notification on the device.

[1773] Step 11:

[1774] The emotion engine installed in the device analyzes emotions from the user's facial expressions and voice and inputs the results into the generative AI. The input is the user's facial expressions and voice data, and the output is the analyzed emotional data.

[1775] Step 12:

[1776] The generative AI adjusts the content of responses and push notifications based on the emotional data obtained from the emotion engine. The input is emotional data, and the output is the adjusted response or notification content.

[1777] This system enables quick and efficient information provision within a company and enables personalized responses that take into account the user's emotions.

[1778] (Application example 2)

[1779] 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."

[1780] Within a company, employees need to obtain information quickly and accurately, but conventional systems make it difficult to easily obtain the necessary information. In factories, there is also a need to quickly share information such as operational status and malfunction information, but existing methods are insufficient for providing information in real time. Furthermore, there is a demand for personalized responses that take user emotions into account, but the technology to achieve this is lacking.

[1781] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data within the company, means for inputting the collected data to the generation AI, means for accepting inquiries from employees, means for transmitting the accepted inquiries to the generation AI, means for the generation AI to generate optimal answers based on the inquiries, means for providing the generated answers to employees, means for inputting employee information to the generation AI, means for using the employee information to proactively provide necessary information in the form of push notifications, means for collecting data within the factory and responding to inquiries from workers using the generation AI, and means for providing push notifications to factory robots and analyzing their emotions. This not only enables employees to quickly and accurately obtain the information they need, but also enables real-time information sharing within the factory and personalized responses that take user emotions into consideration.

[1782] "Internal corporate data" refers to all information related to the operation of a company, including, for example, internal regulations, business manuals, and legal documents.

[1783] "Generative AI" refers to a system that uses artificial intelligence technology to generate optimal answers or information from input data.

[1784] "Employee information" refers to individual information about individual employees, such as profile information and work history.

[1785] "Push Notification" means a notification that is sent automatically by the system without the user explicitly requesting it.

[1786] "Factory data" refers to information related to factory operations and production, including operational status, machine status, and quality control data.

[1787] An "inquiry" refers to a question or request for information made by a user (employee or worker) to the system.

[1788] "Emotion analysis" refers to the technology of analyzing a user's emotions from their facial expressions, voice, etc.

[1789] A specific embodiment for carrying out the present invention will be described.

[1790] First, a database management system (e.g., MySQL or PostgreSQL) is used to collect data within the company. Data is automatically collected from each system within the company and stored in the database. The collected data includes internal regulations, business manuals, legal documents, employee profile information, operation status, machine status, quality control data, etc.

[1791] The server converts the collected data into structured data in JSON or XML format and inputs it into a generative AI (for example, OpenAI's GPT model). The generative AI is trained based on this data and gains the ability to generate optimal answers to inquiries. The server also requests employee information from the generative AI based on specific timing or events and provides the required information in the form of push notifications.

[1792] Users (employees and workers) input inquiries using the chat interface installed on their devices. The inquiries are sent as text data to the server and processed by the generation AI. For example, if a user inputs "Tell me about the new vacation system," the generation AI searches for relevant information in the company's database and generates the most appropriate answer. The generated answer is sent to the device via the server and displayed on the chat interface.

[1793] Data from within the factory is also collected and input into the generative AI. The factory robot responds to inquiries from workers and provides real-time machine status and fault information. For example, if a worker inputs, "Machine 102 has broken down. Please tell me how to fix it," the generative AI will provide a response procedure.

[1794] This system is equipped with an emotion engine (such as Affectiva or Microsoft Azure Emotion API) that analyzes emotions from the user's facial expressions and voice. The analyzed emotion data is fed back to the AI ​​generator, which then personalizes the responses and notifications.

[1795] For example, if a user types "What is the status of Line 3?" into the chat interface on their device, the generated AI will respond with "Line 3 is currently running, the set temperature is 75 degrees, and it has been running for two hours. The next maintenance is scheduled for 2:00 PM." Similarly, if a worker types "Machine 102 has broken down. What should I do?", the generated AI will respond with "There are three possible causes for Machine 102's failure: 1) excessive temperature, 2) worn parts, and 3) overload. To resolve the issue, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload."

[1796] In this way, it is possible to provide information quickly and accurately within a company or factory, and it is also possible to provide personalized responses that take into account the user's feelings.

[1797] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1798] Step 1:

[1799] The server automatically collects data from various systems within the company and factory (e.g., operation control systems, quality control systems, user information systems). This data includes company regulations, work manuals, legal documents, operation status, machine status, quality control data, etc. The collected data is stored in a database.

[1800] Step 2:

[1801] The server converts the collected data into structured data in JSON or XML format, which is then fed into a generative AI (such as OpenAI's GPT model), which trains itself on the input data to improve its ability to generate optimal answers to queries.

[1802] Step 3:

[1803] Users (employees and workers) use the chat interface on their devices to input inquiries. For example, they might type, "Tell me about the new vacation system." The input inquiry is sent to the server as text data.

[1804] Step 4:

[1805] The server sends the text data received from the user to the generation AI, which analyzes the inquiry and searches for relevant information in the company's and factory's databases. Based on the search results, the AI ​​generates the optimal answer.

[1806] Step 5:

[1807] The AI ​​then sends the generated answer back to the server, which then sends the answer back to the device and displays it in the chat interface. For example, a specific answer such as "Under the new vacation system, you can now take 10 more days of vacation per fiscal year" is displayed.

[1808] Step 6:

[1809] The server requests employee information from the generation AI based on specific timing or events, and provides the necessary information in the form of a push notification, such as "New security training is scheduled soon."

[1810] Step 7:

[1811] The device displays the push notification to the user, who then checks and responds to the displayed notification. For example, a user who receives a notification about security training checks the training details.

[1812] Step 8:

[1813] The device is equipped with an emotion engine that analyzes the user's emotions from their facial expressions and voice. The analysis results are sent to a server, and the generation AI uses that information to adjust the content of responses and push notifications. For example, if the user expresses negative emotions, the generation AI will provide softer language and encouraging messages.

[1814] Step 9:

[1815] When a user types, "Machine 102 has broken down. Please tell me how to deal with this," the generated AI will respond, "There are three possible causes for the breakdown of Machine 102: 1) excessive temperature, 2) worn parts, and 3) overload. To deal with this, first check the temperature and allow it to cool properly. Then, replace the parts or remove the overload." In this way, quick and accurate information provision within the factory is achieved.

[1816] 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.

[1817] 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] 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).

[1823] 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.

[1824] 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."

[1825] 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.

[1826] 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).

[1827] 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.

[1828] 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.

[1829] 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.

[1830] 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.

[1831] 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.

[1832] 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.

[1833] 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.

[1834] 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.

[1835] 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.

[1836] 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.

[1837] The following is further disclosed regarding the above embodiment.

[1838] (Claim 1)

[1839] A means of collecting data within the enterprise;

[1840] A means of inputting the collected data into the generative AI;

[1841] A means of receiving inquiries from employees,

[1842] A means for sending the received inquiry to the generation AI;

[1843] A means for the generative AI to generate optimal answers based on inquiries;

[1844] a means of providing the generated answers to employees;

[1845] A means of inputting employee information into the generation AI,

[1846] A system that includes a means for proactively providing necessary information in the form of push notifications using employee information.

[1847] (Claim 2)

[1848] The system of claim 1, further comprising means for requesting employee information from the generation AI based on a specific timing or event.

[1849] (Claim 3)

[1850] The system according to claim 1, wherein the information provided by the generation AI is company regulations, business manuals, and legal documents.

[1851] "Example 1"

[1852] (Claim 1)

[1853] A means of collecting data within the enterprise;

[1854] A means of inputting the collected data into the generative AI in a structured data format;

[1855] A means of receiving inquiries from employees,

[1856] A means for sending the received inquiry to the generation AI;

[1857] A means for the generative AI to generate optimal answers based on inquiries;

[1858] a means of providing the generated answers to employees;

[1859] A means of inputting employee information into the generation AI,

[1860] A system that includes a means for proactively providing necessary information in the form of push notifications using employee information.

[1861] (Claim 2)

[1862] The system of claim 1, further comprising means for requesting employee information from the generation AI based on a specific timing or event.

[1863] (Claim 3)

[1864] The system according to claim 1, wherein the information provided by the generation AI is company regulations, business manuals, and legal documents.

[1865] "Application Example 1"

[1866] (Claim 1)

[1867] A means of collecting data within the enterprise;

[1868] A means of inputting the collected data into the generative AI;

[1869] A means of receiving inquiries from employees,

[1870] A means for sending the received inquiry to the generation AI;

[1871] A means for the generative AI to generate optimal answers based on inquiries;

[1872] a means of providing the generated answers to employees;

[1873] A means of inputting employee information into the generation AI,

[1874] A means to proactively provide necessary information in the form of push notifications using employee information,

[1875] A system that includes a means to provide security information and training content customized to individual employees based on generative AI.

[1876] (Claim 2)

[1877] The system of claim 1, further comprising means for requesting employee information from the generation AI based on a specific timing or event.

[1878] (Claim 3)

[1879] The system according to claim 1, wherein the information provided by the generation AI is company regulations, business manuals, legal documents, and security training content.

[1880] "Example 2: Combining Emotion Engines"

[1881] (Claim 1)

[1882] A means of collecting data within the enterprise;

[1883] A means of inputting the collected data into the generative AI;

[1884] A means for accepting inquiries from users;

[1885] A means for sending the received inquiry to the generation AI;

[1886] A means for the generative AI to generate optimal answers based on inquiries;

[1887] means for providing the generated answer to the user;

[1888] A means of inputting user information into the generation AI;

[1889] A means of proactively providing necessary information in the form of push notifications using user information;

[1890] A system including an emotion engine that analyzes user emotions.

[1891] (Claim 2)

[1892] The system of claim 1, further comprising means for requesting user information from the generation AI based on a specific timing or event.

[1893] (Claim 3)

[1894] The system according to claim 1, wherein the information provided by the generation AI is internal regulations, business procedures, and legal documents.

[1895] "Application example 2 when combining emotion engines"

[1896] (Claim 1)

[1897] A means of collecting data within the enterprise;

[1898] A means of inputting the collected data into the generative AI;

[1899] A means of receiving inquiries from employees,

[1900] A means for sending the received inquiry to the generation AI;

[1901] A means for the generative AI to generate optimal answers based on inquiries;

[1902] a means of providing the generated answers to employees;

[1903] A means of inputting employee information into the generation AI,

[1904] A means to proactively provide necessary information in the form of push notifications using employee information,

[1905] A means of collecting data within the factory and using generative AI to respond to inquiries from workers,

[1906] A system that provides push notifications to factory robots and includes a means for analyzing their emotions.

[1907] (Claim 2)

[1908] The system of claim 1, further comprising means for requesting employee information and factory data from the generation AI based on a specific timing or event.

[1909] (Claim 3)

[1910] The system according to claim 1, wherein the information provided by the generation AI is company regulations, business manuals, legal documents, and factory operation status data. [Explanation of symbols]

[1911] 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 data within the enterprise; A means of inputting the collected data into the generative AI; A means of receiving inquiries from employees, A means for sending the received inquiry to the generation AI; A means for the generative AI to generate optimal answers based on inquiries; a means of providing the generated answers to employees; A means of inputting employee information into the generation AI, A system that includes a means for proactively providing necessary information in the form of push notifications using employee information.

2. The system according to claim 1 , further comprising means for requesting employee information from the generation AI based on a specific timing or event.

3. The system according to claim 1, wherein the information provided by the generation AI is company regulations, business manuals, and legal documents.

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