System

Abstract

An object of a system according to an embodiment is to efficiently perform acquisition of information, analysis, and generation and notification of an optimal proposal.SOLUTION: A system includes an information acquisition unit, an analysis unit, a proposal unit, and a notification unit. The information acquisition unit acquires information. The analysis unit analyzes the information acquired by the information acquisition unit. The proposal unit generates an optimal answer, product, and progress information on the basis of the result analyzed by the analysis unit. The notification unit notifies the information generated by the proposal unit.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] Conventional technologies do not efficiently perform the process from acquiring information to analyzing it, generating optimal suggestions, and notifying users, and there is room for improvement.

[0005] The system according to the embodiment aims to efficiently perform processes from information acquisition and analysis to the generation and notification of optimal proposals. [Means for solving the problem]

[0006] The system according to the embodiment includes an information acquisition unit, an analysis unit, a proposal unit, and a notification unit. The information acquisition unit acquires information. The analysis unit analyzes the information acquired by the information acquisition unit. The proposal unit generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit. The notification unit notifies the user of the information generated by the proposal unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently perform processes from information acquisition and analysis to the generation and notification of optimal proposals. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The SB version of the generative AI system according to an embodiment of the present invention is a system that promotes communication within a company and between different companies, and aims to improve the efficiency and optimization of various business processes. This system utilizes generative AI to check information, present optimal products, calculate appropriate products from attribute information, share construction and development information, and act as an information sharing tool. As a result, the SB version of the generative AI system can efficiently check internal rules and systems, present optimal products, calculate appropriate products from customer attribute information, share construction and development information, and share information between business processes.

[0029] The SB version of the generation AI system according to the embodiment includes an information acquisition unit, an analysis unit, a proposal unit, and a notification unit. The information acquisition unit acquires internal company rules and systems, company information, customer information, construction progress information, and the like. For example, the information acquisition unit acquires document data on internal company rules and systems. The information acquisition unit can also acquire a company's transaction history and customer attribute information. The information acquisition unit can also acquire construction and development progress information. The analysis unit analyzes the information acquired by the information acquisition unit. For example, the analysis unit analyzes the document data on internal company rules and systems to generate an appropriate answer. The analysis unit can also analyze a company's transaction history and customer attribute information to propose optimal products. The analysis unit can also analyze construction and development progress information and provide the latest information. The proposal unit generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit. For example, the proposal unit generates appropriate answers to questions about internal company rules and systems. The proposal unit can also propose optimal products based on a company's transaction history and customer attribute information. Furthermore, the proposal unit can generate the latest information based on the progress of construction and development. The notification unit notifies the information generated by the proposal unit. For example, the notification unit notifies employees of answers regarding company rules and systems. The notification unit can also notify salesmen and store visitors of optimal products. The notification unit can also notify engineers of the progress of construction and development. As a result, the SB version of the generation AI system according to the embodiment can efficiently acquire, analyze, propose, and notify company rules and systems, company information, store visitor information, construction progress information, etc.

[0030] The information acquisition unit can analyze employees' past question history and provide customized answers that are optimal for each employee. For example, the information acquisition unit can analyze the question history that employees have previously input into the generation AI, and when a similar question is input again, it can provide the optimal answer based on the past answers. For example, if an employee who previously asked about how to take paid leave asks the same question again, it can provide a customized answer based on the previous answer. The information acquisition unit can also analyze employees' question history and provide customized answers based on each employee's job content and position. For example, it can provide information for managers to provide information for managers, and information for general employees to provide information for general employees. The information acquisition unit can also predict frequently asked questions based on employees' question history and provide information proactively. For example, if it is predicted that many employees will ask about how to take paid leave at the end of the fiscal year, it can provide that information in advance. This enables efficient information provision by providing optimal answers based on employees' past question history.

[0031] The information acquisition unit tracks the change history of internal rules and systems, allowing it to constantly provide the latest information. For example, the information acquisition unit stores the change history of internal rules and systems in a database, and the generation AI provides the latest information based on that data. For example, if the method for taking paid leave is changed, the system provides the latest information reflecting the changes. The information acquisition unit also tracks the change history of internal rules and systems in real time and builds a system that immediately notifies employees of any changes. For example, if an internal employee benefit system is changed, the system can immediately notify employees of the changes. The information acquisition unit also analyzes the change history of internal rules and systems and provides information that draws particular attention to items that are frequently changed. For example, for a personnel evaluation system that is changed every year, the system provides a detailed explanation of the changes. In this way, by tracking the change history of internal rules and systems and providing the latest information, employees can always obtain the latest information.

[0032] The information acquisition unit can enable confirmation of internal company rules and systems through voice input or a chatbot. For example, the information acquisition unit builds a system that enables confirmation of internal company rules and systems through voice input. For example, employees can voice-input questions using the microphone on their smartphone or PC, and the generation AI provides answers using voice recognition technology. The information acquisition unit also introduces a chatbot to enable employees to confirm internal company rules and systems in text chat format. For example, if an employee types "How do I take paid leave?" into the chatbot, the generation AI can provide an appropriate answer. The information acquisition unit also builds a hybrid system that combines voice input and a chatbot, enabling employees to confirm internal company rules and systems through both voice input and text chat. For example, they can ask questions via voice input and receive detailed answers from the chatbot. This improves employee convenience by enabling confirmation of internal company rules and systems through voice input or a chatbot.

[0033] The information acquisition unit can provide the results of the confirmation of internal rules and systems as visual notes or infographics. The information acquisition unit, for example, builds a system that provides the results of the confirmation of internal rules and systems in visual note format. For example, it visually explains how to take paid leave using diagrams and illustrations. The information acquisition unit also visually displays the results of the confirmation of internal rules and systems using infographics. For example, it can clearly explain the overview of an employee benefit system using graphs and icons. The information acquisition unit also develops tools that automatically generate visual notes and infographics, allowing employees to easily visually understand the results of the confirmation of internal rules and systems. For example, it provides a function that automatically visualizes answers to questions. As a result, the results of the confirmation of internal rules and systems can be provided as visual notes or infographics, making it easier for employees to visually understand the information.

[0034] The information acquisition unit can analyze past sales performance data and propose sales strategies with a high probability of success. The information acquisition unit, for example, analyzes past sales performance data and builds a system that proposes sales strategies with a high probability of success. For example, it proposes sales methods that are effective for specific industries and company sizes. The information acquisition unit also extracts commonalities between successful sales deals based on sales performance data and proposes new sales strategies based on this knowledge. For example, it can analyze the sales process and proposal content of successful deals and derive the optimal strategy. The information acquisition unit also develops a system that analyzes past sales performance data in real time and reflects this in current sales activities. For example, it can make optimal proposals to companies that salespeople visit based on past success cases. This makes it possible to improve the efficiency of sales activities by proposing sales strategies with a high probability of success based on past sales performance data.

[0035] The information acquisition unit can analyze a company's financial data and market trends in real time and propose optimal products. The information acquisition unit, for example, builds a system that analyzes a company's financial data and market trends in real time and proposes optimal products. For example, it selects optimal products based on the company's financial situation and market trends. The information acquisition unit also makes customized product proposals based on the company's needs based on the financial data and market trends. For example, it can propose expansion support products to growing companies and efficiency products to companies in a stable phase. The information acquisition unit also develops a system that analyzes the financial data and market trends collected in real time and proposes optimal products to companies visited by salespeople. For example, it can make proposals that reflect the latest market trends. This makes it possible to analyze a company's financial data and market trends in real time and propose optimal products, thereby increasing the effectiveness of sales activities.

[0036] The information acquisition unit can analyze the internal culture and values ​​of companies that salespeople visit and make proposals that match them. The information acquisition unit, for example, builds a system that analyzes the internal culture and values ​​of companies that salespeople visit and makes proposals that match them. For example, it makes product proposals that match the company's mission and vision. The information acquisition unit also customizes the content of presentations that salespeople make when they visit based on the company's internal culture and values. For example, it can make proposals that include stories that resonate with the company's values. The information acquisition unit also analyzes the internal culture and values ​​and develops a system that makes customized product proposals that match the company's needs. For example, it can propose products and services that match the company's values. This makes it possible to analyze a company's internal culture and values ​​and make proposals that match them, thereby increasing the effectiveness of sales activities.

[0037] The information acquisition unit works in conjunction with the salesperson's schedule management to propose optimal visiting routes. The information acquisition unit, for example, works in conjunction with the salesperson's schedule management to build a system that proposes optimal visiting routes. For example, it proposes optimal routes based on geographic information and traffic conditions of the destinations to be visited. The information acquisition unit also analyzes the salesperson's schedule and automatically generates efficient visiting routes. For example, it can optimize the order of destinations to be visited and minimize travel time. The information acquisition unit also works in conjunction with a schedule management system to propose optimal visiting routes in real time. For example, it can provide routes that take traffic congestion and weather information into consideration. This makes it possible to improve the efficiency of sales activities by working in conjunction with the salesperson's schedule management to propose optimal visiting routes.

[0038] The information acquisition unit can analyze the purchase history of store visitors in detail and make suggestions to encourage repeat purchases. The information acquisition unit, for example, builds a system that analyzes the purchase history of store visitors in detail and makes suggestions to encourage repeat purchases. For example, it proposes new products related to products previously purchased. The information acquisition unit also analyzes the preferences and purchasing patterns of store visitors based on the purchase history and makes customized suggestions to encourage repeat purchases. For example, it can prioritize suggestions for products of a specific brand or category. The information acquisition unit also develops a system that analyzes the purchase history of store visitors in real time and automatically generates promotions and coupons to encourage repeat purchases. For example, it can provide a discount coupon for the next purchase to a store visitor who purchases a specific product. In this way, customer satisfaction can be improved by analyzing the purchase history of store visitors in detail and making suggestions to encourage repeat purchases.

[0039] The information acquisition unit can analyze the behavioral patterns of store visitors and propose optimal product placement and promotions. The information acquisition unit, for example, builds a system that analyzes the behavioral patterns of store visitors and proposes optimal product placement and promotions. For example, popular products are placed along routes that store visitors frequently take. The information acquisition unit also customizes product placement and promotions that attract customers' interest based on the behavioral patterns. For example, if there are many customers in a specific area, products related to that area can be placed. The information acquisition unit also develops a system that analyzes the behavioral patterns of store visitors in real time and dynamically adjusts optimal product placement and promotions. For example, it can change displays and promotion content according to the movements of store visitors. This makes it possible to promote sales by analyzing the behavioral patterns of store visitors and proposing optimal product placement and promotions.

[0040] The information acquisition unit can provide personalized coupons and special offers based on the attribute information of store visitors. The information acquisition unit, for example, builds a system for providing personalized coupons and special offers based on the attribute information of store visitors. For example, special offers based on age and gender are provided. The information acquisition unit also automatically generates customized coupons based on the attribute information and the store visitor's preferences and purchasing history. For example, coupons related to products previously purchased can be provided. The information acquisition unit also analyzes the attribute information of store visitors in real time and develops a system for dynamically providing personalized special offers. For example, the content of the special offers can be changed according to the attributes of the store visitor. This makes it possible to improve customer satisfaction by providing personalized coupons and special offers based on the attribute information of store visitors.

[0041] The information acquisition unit works in conjunction with the customer's purchase history to prepare the most suitable products in advance for the customer's next visit. The information acquisition unit, for example, builds a system that prepares the most suitable products in advance for the customer's next visit based on the customer's purchase history. For example, new products related to products previously purchased are prepared in advance. The information acquisition unit also analyzes the customer's preferences and purchasing patterns based on the purchase history to customize and prepare the most suitable products for the customer's next visit. For example, products from a specific brand or category can be prepared preferentially. The information acquisition unit also develops a system that analyzes the customer's purchase history in real time and dynamically prepares the most suitable products for the customer's next visit. For example, products can be arranged in advance according to the customer's movements. This makes it possible to improve customer satisfaction by working in conjunction with the customer's purchase history to prepare the most suitable products in advance for the customer's next visit.

[0042] The information acquisition unit can analyze construction and development progress data in real time, predict delay risks, and propose countermeasures. The information acquisition unit, for example, builds a system that analyzes construction and development progress data in real time, predicts delay risks, and proposes countermeasures. For example, for projects that are behind schedule, it proposes adding resources or adjusting the schedule. The information acquisition unit also identifies processes with a high risk of delay based on the progress data and proposes specific countermeasures to reduce that risk. For example, it can allocate additional resources to specific processes. The information acquisition unit also develops a system that monitors construction and development progress data in real time and immediately proposes countermeasures when a risk of delay occurs. For example, if progress is behind schedule, it can propose resource reallocation or schedule readjustment. In this way, by analyzing construction and development progress data in real time, predicting delay risks, and proposing countermeasures, it is possible to smooth the progress of projects.

[0043] The information acquisition unit can analyze past project data and propose optimal resource allocation. The information acquisition unit, for example, analyzes past project data and builds a system that proposes optimal resource allocation. For example, the resource allocation of past successful projects is used as reference for a new project. The information acquisition unit also identifies resource surpluses and shortages based on project data and proposes optimal resource allocation. For example, additional resources can be allocated to specific processes. The information acquisition unit also analyzes past project data in real time and develops a system that proposes optimal resource allocation for current projects. For example, resources can be dynamically adjusted according to progress. This makes it possible to improve project efficiency by analyzing past project data and proposing optimal resource allocation.

[0044] The information acquisition unit can visualize the progress of construction and development using AR technology. The information acquisition unit, for example, builds a system that visualizes the progress of construction and development using AR technology. For example, the progress at the site is displayed in real time using a smartphone or tablet. The information acquisition unit also uses AR technology to visualize the progress of construction and development as a 3D model. For example, the progress at a construction site can be displayed as a 3D model, allowing the site situation to be intuitively grasped. The information acquisition unit also uses AR technology to visualize the progress of construction and development in real time and develop a system that monitors the progress of a project. For example, the site situation can be displayed using AR based on progress data. As a result, the progress of construction and development can be visualized using AR technology, allowing the project progress to be intuitively grasped.

[0045] The information acquisition department can share construction and development information between different projects and introduce best practices. For example, the information acquisition department builds a system for sharing construction and development information between different projects and introducing best practices. For example, the methods and technologies of successful projects can be applied to other projects. The information acquisition department also shares information between different projects and introduces best practices to solve common issues and problems. For example, methods that were effective in past projects can be applied to other projects. The information acquisition department also develops a system for sharing construction and development information in real time and introducing best practices between different projects. For example, progress and problems can be shared and solutions from other projects can be applied. In this way, by sharing construction and development information between different projects and introducing best practices, the efficiency and quality of projects can be improved.

[0046] The information acquisition unit can analyze business content in detail and propose optimal business processes. The information acquisition unit, for example, builds a system that analyzes business content in detail and proposes optimal business processes. For example, it analyzes business flows and proposes improvements for efficiency. The information acquisition unit also identifies bottlenecks in business processes based on business data and proposes solutions to those bottlenecks. For example, it can propose resource reallocation or process automation for specific processes. The information acquisition unit also develops a system that analyzes business content in real time and dynamically proposes optimal business processes. For example, it can propose process adjustments and improvements according to the progress of the business. As a result, business efficiency can be improved by analyzing business content in detail and proposing optimal business processes.

[0047] The information acquisition department can introduce an automatic notification system to promote information sharing between different business operations. The information acquisition department, for example, builds an automatic notification system to promote information sharing between different business operations. For example, when a specific task is completed, a notification is automatically sent to the relevant department. The information acquisition department also develops a system that monitors the progress of tasks in real time and automatically shares information between different tasks. For example, it can automatically notify the relevant departments of progress and important changes. The information acquisition department also uses the automatic notification system to facilitate communication between different tasks. For example, when a specific task is delayed, it can automatically notify the relevant departments and urge them to take measures. In this way, by introducing an automatic notification system to promote information sharing between different tasks, collaboration between tasks can be strengthened.

[0048] The information acquisition unit can visualize the content of work so that it can be understood intuitively. The information acquisition unit, for example, builds a system that visualizes the content of work so that it can be understood intuitively. For example, the information acquisition unit visually displays the work flow using diagrams and illustrations. The information acquisition unit also uses visualization tools to display the content of work in graphs and charts so that it can be understood intuitively. For example, the progress of work can be displayed in graphs. The information acquisition unit also develops a system that visualizes the content of work in real time so that it can be understood intuitively. For example, the progress of work can be updated in real time and visually displayed. In this way, the efficiency and understanding of work can be improved by visualizing the content of work so that it can be understood intuitively.

[0049] The information acquisition unit can periodically hold workshops to promote collaboration between different business functions. For example, the information acquisition unit periodically holds workshops to promote collaboration between different business functions and collects ideas that arise there. For example, the information acquisition unit provides a forum for the technical department and the sales department to jointly exchange ideas. The information acquisition unit also records the content of discussions at the workshops and saves them as audio data. After that, it can perform audio analysis to extract important ideas and opinions and store them in a database. The information acquisition unit also collects materials and presentation data used in the workshops and saves them in a database as background information for the ideas. This makes it possible to clarify the origin and basis of ideas. As a result, by periodically holding workshops to promote collaboration between different business functions, it is possible to improve business collaboration and creativity.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The information acquisition unit can automatically generate and share minutes of internal conferences and meetings. For example, it can convert statements made during a meeting into text in real time and automatically generate minutes after the meeting ends. The information acquisition unit can also automatically organize the minutes and highlight important points and action items. Furthermore, the information acquisition unit can automatically upload the minutes to an internal shared folder or cloud storage and notify relevant parties. This allows for efficient recording and sharing of meeting content, facilitating the smooth transmission of information and follow-up.

[0052] The information acquisition department can manage employee skills and qualifications and assign them to appropriate projects and tasks. For example, by registering employee skill sets and qualifications in a database, the department can automatically select the most suitable personnel based on project requirements. The information acquisition department can also track the update status of employees' skills and qualifications and notify them of the timing of necessary training or qualification renewal. Furthermore, the information acquisition department can suggest career paths and growth plans based on employees' skills and qualifications. This allows the department to effectively manage employee skills and qualifications and assign them to appropriate projects and tasks, thereby supporting work efficiency and employee growth.

[0053] The information acquisition department can integrate and centrally manage internal communication tools. For example, different communication tools such as email, chat, and video conferencing can be integrated into a single platform, making them easily accessible to employees. The information acquisition department can also automatically organize communication history and provide a search function, allowing employees to quickly refer to past interactions. Furthermore, the information acquisition department can analyze the usage of communication tools and suggest efficient communication methods. This allows for centralized management of internal communication and promotes efficient information sharing and collaboration.

[0054] The information acquisition department can enable employees to check company rules and systems through voice input or a chatbot. For example, employees can use the microphone on their smartphone or PC to voice-input questions, and the generation AI can provide answers using voice recognition technology. The information acquisition department can also introduce a chatbot to enable employees to check company rules and systems in text chat format. For example, if an employee types "How do I take paid leave?" into the chatbot, the generation AI can provide an appropriate answer. The information acquisition department can also build a hybrid system that combines voice input and a chatbot, allowing employees to check company rules and systems through both voice input and text chat. For example, they can ask questions via voice input and receive detailed answers from the chatbot. This improves employee convenience by allowing employees to check company rules and systems through voice input or a chatbot.

[0055] The information acquisition department can build an internal knowledge sharing platform that employees can easily access. For example, it can centrally manage internal documents, manuals, and FAQs and provide a search function. The information acquisition department can also introduce posting and commenting functions so that employees can share their knowledge and experience. Furthermore, the information acquisition department can provide project management functions through the knowledge sharing platform to promote collaboration between employees. This allows for efficient sharing of internal knowledge, improving employee skills and streamlining work.

[0056] The information acquisition department can analyze past sales performance data and propose sales strategies with a high probability of success. For example, it can propose sales methods that are effective for specific industries or company sizes. The information acquisition department can also extract commonalities between successful sales deals based on sales performance data and propose new sales strategies based on that knowledge. For example, it can analyze the sales process and proposal content of successful deals to derive the optimal strategy. The information acquisition department can also develop a system that analyzes past sales performance data in real time and reflects this in current sales activities. For example, it can make optimal proposals to companies that salespeople visit based on past success stories. This makes it possible to improve the efficiency of sales activities by proposing sales strategies with a high probability of success based on past sales performance data.

[0057] The information acquisition department can analyze a company's financial data and market trends in real time and propose optimal products. For example, it selects optimal products based on the company's financial situation and market trends. The information acquisition department also makes customized product proposals based on the company's needs based on financial data and market trends. For example, it can propose expansion support products to growing companies and efficiency products to companies in a stable phase. The information acquisition department can also develop a system that analyzes financial data and market trends collected in real time and proposes optimal products to companies visited by salespeople. For example, it can make proposals that reflect the latest market trends. This makes it possible to analyze a company's financial data and market trends in real time and propose optimal products, thereby increasing the effectiveness of sales activities.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The information acquisition unit acquires information such as internal company rules and systems, company information, visitor information, and construction progress information. For example, the information acquisition unit acquires document data on internal company rules and systems, and can also acquire the company's transaction history and visitor attribute information. It can also acquire the progress status of construction and development. Step 2: The analysis unit analyzes the information acquired by the information acquisition unit. For example, the analysis unit analyzes document data on internal company rules and systems to generate appropriate responses. It can also analyze a company's transaction history and customer attributes to suggest optimal products. It can also analyze the progress of construction and development projects and provide the latest information. Step 3: The proposal unit generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit. For example, the proposal unit generates appropriate answers to questions about internal rules and systems. It can also propose optimal products based on the company's transaction history and customer attributes. It can also generate the latest information based on the progress of construction and development. Step 4: The notification department notifies the information generated by the proposal department. For example, the notification department notifies employees of answers regarding company rules and systems. It can also notify salesmen and store visitors of optimal products. It can also notify engineers of the progress of construction and development projects.

[0060] (Example 2) The SB version of the generative AI system according to an embodiment of the present invention is a system that promotes communication within a company and between different companies, and aims to improve the efficiency and optimization of various business processes. This system utilizes generative AI to check information, present optimal products, calculate appropriate products from attribute information, share construction and development information, and act as an information sharing tool. As a result, the SB version of the generative AI system can efficiently check internal rules and systems, present optimal products, calculate appropriate products from customer attribute information, share construction and development information, and share information between business processes.

[0061] The SB version of the generation AI system according to the embodiment includes an information acquisition unit, an analysis unit, a proposal unit, and a notification unit. The information acquisition unit acquires internal company rules and systems, company information, customer information, construction progress information, and the like. For example, the information acquisition unit acquires document data on internal company rules and systems. The information acquisition unit can also acquire a company's transaction history and customer attribute information. The information acquisition unit can also acquire construction and development progress information. The analysis unit analyzes the information acquired by the information acquisition unit. For example, the analysis unit analyzes the document data on internal company rules and systems to generate an appropriate answer. The analysis unit can also analyze a company's transaction history and customer attribute information to propose optimal products. The analysis unit can also analyze construction and development progress information and provide the latest information. The proposal unit generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit. For example, the proposal unit generates appropriate answers to questions about internal company rules and systems. The proposal unit can also propose optimal products based on a company's transaction history and customer attribute information. Furthermore, the proposal unit can generate the latest information based on the progress of construction and development. The notification unit notifies the information generated by the proposal unit. For example, the notification unit notifies employees of answers regarding company rules and systems. The notification unit can also notify salesmen and store visitors of optimal products. The notification unit can also notify engineers of the progress of construction and development. As a result, the SB version of the generation AI system according to the embodiment can efficiently acquire, analyze, propose, and notify company rules and systems, company information, store visitor information, construction progress information, etc.

[0062] The information acquisition unit can analyze employees' past question history and provide customized answers that are optimal for each employee. For example, the information acquisition unit can analyze the question history that employees have previously input into the generation AI, and when a similar question is input again, it can provide the optimal answer based on the past answers. For example, if an employee who previously asked about how to take paid leave asks the same question again, it can provide a customized answer based on the previous answer. The information acquisition unit can also analyze employees' question history and provide customized answers based on each employee's job content and position. For example, it can provide information for managers to provide information for managers, and information for general employees to provide information for general employees. The information acquisition unit can also predict frequently asked questions based on employees' question history and provide information proactively. For example, if it is predicted that many employees will ask about how to take paid leave at the end of the fiscal year, it can provide that information in advance. This enables efficient information provision by providing optimal answers based on employees' past question history.

[0063] The information acquisition unit tracks the change history of internal rules and systems, allowing it to constantly provide the latest information. For example, the information acquisition unit stores the change history of internal rules and systems in a database, and the generation AI provides the latest information based on that data. For example, if the method for taking paid leave is changed, the system provides the latest information reflecting the changes. The information acquisition unit also tracks the change history of internal rules and systems in real time and builds a system that immediately notifies employees of any changes. For example, if an internal employee benefit system is changed, the system can immediately notify employees of the changes. The information acquisition unit also analyzes the change history of internal rules and systems and provides information that draws particular attention to items that are frequently changed. For example, for a personnel evaluation system that is changed every year, the system provides a detailed explanation of the changes. In this way, by tracking the change history of internal rules and systems and providing the latest information, employees can always obtain the latest information.

[0064] The information acquisition unit can use the emotion estimation function to analyze the emotions of employees when they ask questions and generate answers to reduce stress and anxiety. For example, the information acquisition unit can analyze the emotions of employees when they input questions in real time, and if stress or anxiety is high, generate answers that provide a sense of security. For example, it can provide answers that use kind language and include encouraging messages. The information acquisition unit can also use the emotion estimation function to analyze the emotional state of employees when they ask questions, and if negative emotions are strong, generate answers that elicit positive emotions. For example, it can provide answers that include success stories and positive feedback. The information acquisition unit can also suggest resources and support to reduce stress and anxiety based on the employee's emotional state. For example, it can provide answers that include information on mental health support and relaxation methods. In this way, by analyzing employees' emotions and providing answers to reduce stress and anxiety, it is possible to reduce the psychological burden on employees.

[0065] The information acquisition unit can enable confirmation of internal company rules and systems through voice input or a chatbot. For example, the information acquisition unit builds a system that enables confirmation of internal company rules and systems through voice input. For example, employees can voice-input questions using the microphone on their smartphone or PC, and the generation AI provides answers using voice recognition technology. The information acquisition unit also introduces a chatbot to enable employees to confirm internal company rules and systems in text chat format. For example, if an employee types "How do I take paid leave?" into the chatbot, the generation AI can provide an appropriate answer. The information acquisition unit also builds a hybrid system that combines voice input and a chatbot, enabling employees to confirm internal company rules and systems through both voice input and text chat. For example, they can ask questions via voice input and receive detailed answers from the chatbot. This improves employee convenience by enabling confirmation of internal company rules and systems through voice input or a chatbot.

[0066] The information acquisition unit can provide the results of the confirmation of internal rules and systems as visual notes or infographics. The information acquisition unit, for example, builds a system that provides the results of the confirmation of internal rules and systems in visual note format. For example, it visually explains how to take paid leave using diagrams and illustrations. The information acquisition unit also visually displays the results of the confirmation of internal rules and systems using infographics. For example, it can clearly explain the overview of an employee benefit system using graphs and icons. The information acquisition unit also develops tools that automatically generate visual notes and infographics, allowing employees to easily visually understand the results of the confirmation of internal rules and systems. For example, it provides a function that automatically visualizes answers to questions. As a result, the results of the confirmation of internal rules and systems can be provided as visual notes or infographics, making it easier for employees to visually understand the information.

[0067] The information acquisition unit can use the emotion estimation function to automatically suggest training programs based on the employee's emotions. For example, the information acquisition unit uses the emotion estimation function to analyze the employee's emotional state and automatically suggest the optimal training program based on the results. For example, it can suggest relaxation and mental health training to employees with high stress levels. The information acquisition unit also builds a system that customizes and suggests the optimal training program for each employee based on the employee's emotional data. For example, it can suggest leadership training to employees with strong positive emotions. The information acquisition unit also uses the emotion estimation function to monitor the employee's emotional state in real time and dynamically adjust the training program based on the results. For example, if stress increases during training, it can add a relaxation session. This makes it possible to support employee growth by automatically suggesting training programs based on the employee's emotions.

[0068] The information acquisition unit can analyze past sales performance data and propose sales strategies with a high probability of success. The information acquisition unit, for example, analyzes past sales performance data and builds a system that proposes sales strategies with a high probability of success. For example, it proposes sales methods that are effective for specific industries and company sizes. The information acquisition unit also extracts commonalities between successful sales deals based on sales performance data and proposes new sales strategies based on this knowledge. For example, it can analyze the sales process and proposal content of successful deals and derive the optimal strategy. The information acquisition unit also develops a system that analyzes past sales performance data in real time and reflects this in current sales activities. For example, it can make optimal proposals to companies that salespeople visit based on past success cases. This makes it possible to improve the efficiency of sales activities by proposing sales strategies with a high probability of success based on past sales performance data.

[0069] The information acquisition unit can analyze a company's financial data and market trends in real time and propose optimal products. The information acquisition unit, for example, builds a system that analyzes a company's financial data and market trends in real time and proposes optimal products. For example, it selects optimal products based on the company's financial situation and market trends. The information acquisition unit also makes customized product proposals based on the company's needs based on the financial data and market trends. For example, it can propose expansion support products to growing companies and efficiency products to companies in a stable phase. The information acquisition unit also develops a system that analyzes the financial data and market trends collected in real time and proposes optimal products to companies visited by salespeople. For example, it can make proposals that reflect the latest market trends. This makes it possible to analyze a company's financial data and market trends in real time and propose optimal products, thereby increasing the effectiveness of sales activities.

[0070] The information acquisition unit can use the emotion estimation function to analyze the emotional state of a salesperson and suggest optimal timing for sales activities. For example, the information acquisition unit can use the emotion estimation function to build a system that analyzes the emotional state of a salesperson in real time and suggests optimal timing for sales activities. For example, it can suggest important business negotiations when the salesperson is relaxed. Furthermore, based on the emotional data of the salesperson, the information acquisition unit can suggest refreshment time when stress is high and recommend active sales activities when positive emotions are strong. For example, it can adjust the schedule according to the emotional state. Furthermore, the information acquisition unit can monitor the emotional state of a salesperson using the emotion estimation function and suggest important sales activities to be carried out when emotions are stable. For example, it can determine the optimal timing for visiting based on the emotional data. As a result, the effectiveness of sales activities can be maximized by analyzing the emotional state of a salesperson and suggesting optimal timing for sales activities.

[0071] The information acquisition unit can analyze the internal culture and values ​​of companies that salespeople visit and make proposals that match them. The information acquisition unit, for example, builds a system that analyzes the internal culture and values ​​of companies that salespeople visit and makes proposals that match them. For example, it makes product proposals that match the company's mission and vision. The information acquisition unit also customizes the content of presentations that salespeople make when they visit based on the company's internal culture and values. For example, it can make proposals that include stories that resonate with the company's values. The information acquisition unit also analyzes the internal culture and values ​​and develops a system that makes customized product proposals that match the company's needs. For example, it can propose products and services that match the company's values. This makes it possible to analyze a company's internal culture and values ​​and make proposals that match them, thereby increasing the effectiveness of sales activities.

[0072] The information acquisition unit works in conjunction with the salesperson's schedule management to propose optimal visiting routes. The information acquisition unit, for example, works in conjunction with the salesperson's schedule management to build a system that proposes optimal visiting routes. For example, it proposes optimal routes based on geographic information and traffic conditions of the destinations to be visited. The information acquisition unit also analyzes the salesperson's schedule and automatically generates efficient visiting routes. For example, it can optimize the order of destinations to be visited and minimize travel time. The information acquisition unit also works in conjunction with a schedule management system to propose optimal visiting routes in real time. For example, it can provide routes that take traffic congestion and weather information into consideration. This makes it possible to improve the efficiency of sales activities by working in conjunction with the salesperson's schedule management to propose optimal visiting routes.

[0073] The information acquisition unit uses the emotion estimation function to analyze the emotional compatibility between a salesperson and a customer, and can assign the most suitable salesperson. For example, the information acquisition unit uses the emotion estimation function to analyze the emotional compatibility between a salesperson and a customer, and builds a system to assign the most suitable salesperson. For example, a salesperson with strong positive emotions is assigned to an important customer. The information acquisition unit also identifies a combination of salespersons with good compatibility based on emotional data of the salesperson and the customer, and assigns a salesperson based on the results. For example, a salesperson with good emotional compatibility can be assigned to a customer. The information acquisition unit also uses the emotion estimation function to develop a system that monitors the emotional compatibility between a salesperson and a customer in real time, and dynamically assigns the most suitable salesperson. For example, a salesperson can be adjusted based on the emotional data. This makes it possible to analyze the emotional compatibility between a salesperson and a customer, and assign the most suitable salesperson, thereby improving the effectiveness of sales activities.

[0074] The information acquisition unit can analyze the purchase history of store visitors in detail and make suggestions to encourage repeat purchases. The information acquisition unit, for example, builds a system that analyzes the purchase history of store visitors in detail and makes suggestions to encourage repeat purchases. For example, it proposes new products related to products previously purchased. The information acquisition unit also analyzes the preferences and purchasing patterns of store visitors based on the purchase history and makes customized suggestions to encourage repeat purchases. For example, it can prioritize suggestions for products of a specific brand or category. The information acquisition unit also develops a system that analyzes the purchase history of store visitors in real time and automatically generates promotions and coupons to encourage repeat purchases. For example, it can provide a discount coupon for the next purchase to a store visitor who purchases a specific product. In this way, customer satisfaction can be improved by analyzing the purchase history of store visitors in detail and making suggestions to encourage repeat purchases.

[0075] The information acquisition unit can analyze the behavioral patterns of store visitors and propose optimal product placement and promotions. The information acquisition unit, for example, builds a system that analyzes the behavioral patterns of store visitors and proposes optimal product placement and promotions. For example, popular products are placed along routes that store visitors frequently take. The information acquisition unit also customizes product placement and promotions that attract customers' interest based on the behavioral patterns. For example, if there are many customers in a specific area, products related to that area can be placed. The information acquisition unit also develops a system that analyzes the behavioral patterns of store visitors in real time and dynamically adjusts optimal product placement and promotions. For example, it can change displays and promotion content according to the movements of store visitors. This makes it possible to promote sales by analyzing the behavioral patterns of store visitors and proposing optimal product placement and promotions.

[0076] The information acquisition unit can use the emotion estimation function to analyze the emotional state of customers and propose a service method appropriate to their emotions. For example, the information acquisition unit uses the emotion estimation function to build a system that analyzes the emotional state of customers in real time and proposes a service method appropriate to their emotions. For example, it can propose an active service approach to a relaxed customer and a more subdued service approach to a stressed customer. The information acquisition unit can also customize and propose the optimal service method for each customer based on the customer's emotional data. For example, it can prioritize introducing new products to customers with strong positive emotions and providing support to customers with strong negative emotions. The information acquisition unit can also use the emotion estimation function to develop a system that monitors the emotional state of customers and dynamically adjusts the service method appropriate to their emotions. For example, it can provide advice to customer service staff in real time based on the emotional data. This allows customer satisfaction to be improved by analyzing the customer's emotional state and proposing a service method appropriate to their emotions.

[0077] The information acquisition unit can provide personalized coupons and special offers based on the attribute information of store visitors. The information acquisition unit, for example, builds a system for providing personalized coupons and special offers based on the attribute information of store visitors. For example, special offers based on age and gender are provided. The information acquisition unit also automatically generates customized coupons based on the attribute information and the store visitor's preferences and purchasing history. For example, coupons related to products previously purchased can be provided. The information acquisition unit also analyzes the attribute information of store visitors in real time and develops a system for dynamically providing personalized special offers. For example, the content of the special offers can be changed according to the attributes of the store visitor. This makes it possible to improve customer satisfaction by providing personalized coupons and special offers based on the attribute information of store visitors.

[0078] The information acquisition unit works in conjunction with the customer's purchase history to prepare the most suitable products in advance for the customer's next visit. The information acquisition unit, for example, builds a system that prepares the most suitable products in advance for the customer's next visit based on the customer's purchase history. For example, new products related to products previously purchased are prepared in advance. The information acquisition unit also analyzes the customer's preferences and purchasing patterns based on the purchase history to customize and prepare the most suitable products for the customer's next visit. For example, products from a specific brand or category can be prepared preferentially. The information acquisition unit also develops a system that analyzes the customer's purchase history in real time and dynamically prepares the most suitable products for the customer's next visit. For example, products can be arranged in advance according to the customer's movements. This makes it possible to improve customer satisfaction by working in conjunction with the customer's purchase history to prepare the most suitable products in advance for the customer's next visit.

[0079] The information acquisition unit can use the emotion estimation function to automatically adjust background music and in-store displays according to the emotions of customers. For example, the information acquisition unit uses the emotion estimation function to analyze the emotional state of customers in real time and build a system that automatically adjusts background music and in-store displays according to their emotions. For example, calm background music can be played for relaxed customers, and lively background music for excited customers. The information acquisition unit also customizes and adjusts the in-store atmosphere based on the customers' emotional data. For example, a bright display can be set for customers with strong positive emotions, and a calm display can be set for customers with strong negative emotions. The information acquisition unit also uses the emotion estimation function to monitor the emotional state of customers and develop a system that dynamically adjusts background music and in-store displays according to their emotions. For example, the in-store atmosphere can be changed in real time based on the emotional data. This allows for automatic adjustment of background music and in-store displays according to customers' emotions, thereby improving customer satisfaction.

[0080] The information acquisition unit can analyze construction and development progress data in real time, predict delay risks, and propose countermeasures. The information acquisition unit, for example, builds a system that analyzes construction and development progress data in real time, predicts delay risks, and proposes countermeasures. For example, for projects that are behind schedule, it proposes adding resources or adjusting the schedule. The information acquisition unit also identifies processes with a high risk of delay based on the progress data and proposes specific countermeasures to reduce that risk. For example, it can allocate additional resources to specific processes. The information acquisition unit also develops a system that monitors construction and development progress data in real time and immediately proposes countermeasures when a risk of delay occurs. For example, if progress is behind schedule, it can propose resource reallocation or schedule readjustment. In this way, by analyzing construction and development progress data in real time, predicting delay risks, and proposing countermeasures, it is possible to smooth the progress of projects.

[0081] The information acquisition unit can analyze past project data and propose optimal resource allocation. The information acquisition unit, for example, analyzes past project data and builds a system that proposes optimal resource allocation. For example, the resource allocation of past successful projects is used as reference for a new project. The information acquisition unit also identifies resource surpluses and shortages based on project data and proposes optimal resource allocation. For example, additional resources can be allocated to specific processes. The information acquisition unit also analyzes past project data in real time and develops a system that proposes optimal resource allocation for current projects. For example, resources can be dynamically adjusted according to progress. This makes it possible to improve project efficiency by analyzing past project data and proposing optimal resource allocation.

[0082] The information acquisition unit can use the emotion estimation function to analyze the stress level of an engineer and suggest appropriate break timing. For example, the information acquisition unit uses the emotion estimation function to build a system that analyzes the stress level of an engineer in real time and suggests appropriate break timing. For example, it suggests taking a break when stress is high. The information acquisition unit also customizes and suggests optimal break timing for each engineer based on the engineer's emotion data. For example, it can suggest frequent breaks for engineers with high stress levels and longer breaks for engineers with low stress levels. The information acquisition unit also uses the emotion estimation function to develop a system that monitors the engineer's stress level and suggests relaxation methods or breaks when stress is high. For example, it can play relaxation music when stress is high. This allows the system to analyze the engineer's stress level and suggest appropriate break timing, thereby improving the engineer's health and work efficiency.

[0083] The information acquisition unit can visualize the progress of construction and development using AR technology. The information acquisition unit, for example, builds a system that visualizes the progress of construction and development using AR technology. For example, the progress at the site is displayed in real time using a smartphone or tablet. The information acquisition unit also uses AR technology to visualize the progress of construction and development as a 3D model. For example, the progress at a construction site can be displayed as a 3D model, allowing the site situation to be intuitively grasped. The information acquisition unit also uses AR technology to visualize the progress of construction and development in real time and develop a system that monitors the progress of a project. For example, the site situation can be displayed using AR based on progress data. As a result, the progress of construction and development can be visualized using AR technology, allowing the project progress to be intuitively grasped.

[0084] The information acquisition department can share construction and development information between different projects and introduce best practices. For example, the information acquisition department builds a system for sharing construction and development information between different projects and introducing best practices. For example, the methods and technologies of successful projects can be applied to other projects. The information acquisition department also shares information between different projects and introduces best practices to solve common issues and problems. For example, methods that were effective in past projects can be applied to other projects. The information acquisition department also develops a system for sharing construction and development information in real time and introducing best practices between different projects. For example, progress and problems can be shared and solutions from other projects can be applied. In this way, by sharing construction and development information between different projects and introducing best practices, the efficiency and quality of projects can be improved.

[0085] The information acquisition unit can use the emotion estimation function to assign tasks according to the emotions of engineers. For example, the information acquisition unit uses the emotion estimation function to analyze the emotional state of engineers in real time and build a system that assigns tasks according to their emotions. For example, lighter tasks are assigned to engineers with high stress levels, and important tasks are assigned to engineers with strong positive emotions. The information acquisition unit also customizes and assigns tasks that are optimal for each engineer based on the engineers' emotional data. For example, complex tasks can be assigned to engineers with stable emotions, and simple tasks can be assigned to engineers with unstable emotions. The information acquisition unit also uses the emotion estimation function to monitor the emotional state of engineers and develop a system that dynamically adjusts task assignment according to their emotions. For example, task priorities can be changed in real time based on the emotional data. This makes it possible to improve work efficiency and engineer satisfaction by assigning tasks according to the engineers' emotions.

[0086] The information acquisition unit can analyze business content in detail and propose optimal business processes. The information acquisition unit, for example, builds a system that analyzes business content in detail and proposes optimal business processes. For example, it analyzes business flows and proposes improvements for efficiency. The information acquisition unit also identifies bottlenecks in business processes based on business data and proposes solutions to those bottlenecks. For example, it can propose resource reallocation or process automation for specific processes. The information acquisition unit also develops a system that analyzes business content in real time and dynamically proposes optimal business processes. For example, it can propose process adjustments and improvements according to the progress of the business. As a result, business efficiency can be improved by analyzing business content in detail and proposing optimal business processes.

[0087] The information acquisition department can introduce an automatic notification system to promote information sharing between different business operations. The information acquisition department, for example, builds an automatic notification system to promote information sharing between different business operations. For example, when a specific task is completed, a notification is automatically sent to the relevant department. The information acquisition department also develops a system that monitors the progress of tasks in real time and automatically shares information between different tasks. For example, it can automatically notify the relevant departments of progress and important changes. The information acquisition department also uses the automatic notification system to facilitate communication between different tasks. For example, when a specific task is delayed, it can automatically notify the relevant departments and urge them to take measures. In this way, by introducing an automatic notification system to promote information sharing between different tasks, collaboration between tasks can be strengthened.

[0088] The information acquisition unit can use the emotion estimation function to make suggestions to facilitate communication between jobs. The information acquisition unit, for example, uses the emotion estimation function to build a system that makes suggestions to facilitate communication between jobs. For example, when emotions are high, the information acquisition unit makes a suggestion to encourage a calm response. The information acquisition unit also suggests optimal communication methods for communication between jobs based on the emotion estimation data. For example, when stress is high, the information acquisition unit can suggest conversations in a relaxed atmosphere. The information acquisition unit also uses the emotion estimation function to develop a system that monitors communication between jobs and dynamically suggests communication methods according to emotions. For example, the tone and content of communication can be adjusted based on the emotion data. As a result, by using the emotion estimation function to make suggestions to facilitate communication between jobs, it is possible to improve work efficiency and cooperation.

[0089] The information acquisition unit can visualize the content of work so that it can be understood intuitively. The information acquisition unit, for example, builds a system that visualizes the content of work so that it can be understood intuitively. For example, the information acquisition unit visually displays the work flow using diagrams and illustrations. The information acquisition unit also uses visualization tools to display the content of work in graphs and charts so that it can be understood intuitively. For example, the progress of work can be displayed in graphs. The information acquisition unit also develops a system that visualizes the content of work in real time so that it can be understood intuitively. For example, the progress of work can be updated in real time and visually displayed. In this way, the efficiency and understanding of work can be improved by visualizing the content of work so that it can be understood intuitively.

[0090] The information acquisition unit can periodically hold workshops to promote collaboration between different business functions. For example, the information acquisition unit periodically holds workshops to promote collaboration between different business functions and collects ideas that arise there. For example, the information acquisition unit provides a forum for the technical department and the sales department to jointly exchange ideas. The information acquisition unit also records the content of discussions at the workshops and saves them as audio data. After that, it can perform audio analysis to extract important ideas and opinions and store them in a database. The information acquisition unit also collects materials and presentation data used in the workshops and saves them in a database as background information for the ideas. This makes it possible to clarify the origin and basis of ideas. As a result, by periodically holding workshops to promote collaboration between different business functions, it is possible to improve business collaboration and creativity.

[0091] The information acquisition unit can use the emotion estimation function to propose measures to reduce emotional friction between tasks. The information acquisition unit, for example, uses the emotion estimation function to build a system that proposes measures to reduce emotional friction between tasks. For example, when emotions are heightened, the information acquisition unit makes a proposal to encourage a calm response. The information acquisition unit also proposes an optimal communication method based on the emotion estimation data to reduce emotional friction between tasks. For example, when stress is high, the information acquisition unit can suggest a conversation in a relaxed atmosphere. The information acquisition unit also uses the emotion estimation function to monitor emotional friction between tasks and develop a system that dynamically proposes measures according to emotions. For example, the tone and content of communication can be adjusted based on the emotion data. As a result, the emotion estimation function can be used to propose measures to reduce emotional friction between tasks, thereby improving work efficiency and cooperation.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The information acquisition unit can automatically generate and share minutes of internal conferences and meetings. For example, it can convert statements made during a meeting into text in real time and automatically generate minutes after the meeting ends. The information acquisition unit can also automatically organize the minutes and highlight important points and action items. Furthermore, the information acquisition unit can automatically upload the minutes to an internal shared folder or cloud storage and notify relevant parties. This allows for efficient recording and sharing of meeting content, facilitating the smooth transmission of information and follow-up.

[0094] The information acquisition department can manage employee skills and qualifications and assign them to appropriate projects and tasks. For example, by registering employee skill sets and qualifications in a database, the department can automatically select the most suitable personnel based on project requirements. The information acquisition department can also track the update status of employees' skills and qualifications and notify them of the timing of necessary training or qualification renewal. Furthermore, the information acquisition department can suggest career paths and growth plans based on employees' skills and qualifications. This allows the department to effectively manage employee skills and qualifications and assign them to appropriate projects and tasks, thereby supporting work efficiency and employee growth.

[0095] The information acquisition department can integrate and centrally manage internal communication tools. For example, different communication tools such as email, chat, and video conferencing can be integrated into a single platform, making them easily accessible to employees. The information acquisition department can also automatically organize communication history and provide a search function, allowing employees to quickly refer to past interactions. Furthermore, the information acquisition department can analyze the usage of communication tools and suggest efficient communication methods. This allows for centralized management of internal communication and promotes efficient information sharing and collaboration.

[0096] The information acquisition unit can use the emotion estimation function to analyze employee motivation and propose appropriate incentives. For example, if employee motivation is low based on employee emotion data, incentives such as bonuses or special holidays can be proposed. The information acquisition unit can also use the emotion estimation function to provide feedback and evaluations to improve employee motivation. Furthermore, the information acquisition unit can analyze the motivation of the entire team based on employee emotion data and propose team building activities and events. In this way, by analyzing employee motivation and proposing appropriate incentives, it is possible to improve employee motivation and productivity.

[0097] The information acquisition department can enable employees to check company rules and systems through voice input or a chatbot. For example, employees can use the microphone on their smartphone or PC to voice-input questions, and the generation AI can provide answers using voice recognition technology. The information acquisition department can also introduce a chatbot to enable employees to check company rules and systems in text chat format. For example, if an employee types "How do I take paid leave?" into the chatbot, the generation AI can provide an appropriate answer. The information acquisition department can also build a hybrid system that combines voice input and a chatbot, allowing employees to check company rules and systems through both voice input and text chat. For example, they can ask questions via voice input and receive detailed answers from the chatbot. This improves employee convenience by allowing employees to check company rules and systems through voice input or a chatbot.

[0098] The information acquisition unit can use the emotion estimation function to automatically suggest training programs based on employees' emotions. For example, it can suggest relaxation and mental health training to employees with high stress levels. The information acquisition unit also builds a system that customizes and suggests optimal training programs for each employee based on the employee's emotional data. For example, it can suggest leadership training to employees with strong positive emotions. The information acquisition unit also uses the emotion estimation function to monitor employees' emotional states in real time and dynamically adjust training programs based on the results. For example, if stress increases during training, it can add a relaxation session. This makes it possible to support employee growth by automatically suggesting training programs based on employees' emotions.

[0099] The information acquisition department can build an internal knowledge sharing platform that employees can easily access. For example, it can centrally manage internal documents, manuals, and FAQs and provide a search function. The information acquisition department can also introduce posting and commenting functions so that employees can share their knowledge and experience. Furthermore, the information acquisition department can provide project management functions through the knowledge sharing platform to promote collaboration between employees. This allows for efficient sharing of internal knowledge, improving employee skills and streamlining work.

[0100] The information acquisition department can analyze past sales performance data and propose sales strategies with a high probability of success. For example, it can propose sales methods that are effective for specific industries or company sizes. The information acquisition department can also extract commonalities between successful sales deals based on sales performance data and propose new sales strategies based on that knowledge. For example, it can analyze the sales process and proposal content of successful deals to derive the optimal strategy. The information acquisition department can also develop a system that analyzes past sales performance data in real time and reflects this in current sales activities. For example, it can make optimal proposals to companies that salespeople visit based on past success stories. This makes it possible to improve the efficiency of sales activities by proposing sales strategies with a high probability of success based on past sales performance data.

[0101] The information acquisition department can analyze a company's financial data and market trends in real time and propose optimal products. For example, it selects optimal products based on the company's financial situation and market trends. The information acquisition department also makes customized product proposals based on the company's needs based on financial data and market trends. For example, it can propose expansion support products to growing companies and efficiency products to companies in a stable phase. The information acquisition department can also develop a system that analyzes financial data and market trends collected in real time and proposes optimal products to companies visited by salespeople. For example, it can make proposals that reflect the latest market trends. This makes it possible to analyze a company's financial data and market trends in real time and propose optimal products, thereby increasing the effectiveness of sales activities.

[0102] The information acquisition unit can use the emotion estimation function to analyze the emotional state of a salesperson and suggest optimal timing for sales activities. For example, it can suggest important business negotiations when the salesperson is relaxed. Furthermore, based on the salesperson's emotional data, the information acquisition unit can suggest refreshment time when stress is high and recommend proactive sales activities when positive emotions are strong. For example, it can adjust the schedule according to the emotional state. Furthermore, the information acquisition unit can monitor the emotional state of a salesperson using the emotion estimation function and suggest important sales activities to be carried out when emotions are stable. For example, it can determine the optimal timing for visits based on the emotional data. This makes it possible to maximize the effectiveness of sales activities by analyzing the emotional state of a salesperson and suggesting optimal timing for sales activities.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The information acquisition unit acquires information such as internal company rules and systems, company information, visitor information, and construction progress information. For example, the information acquisition unit acquires document data on internal company rules and systems, and can also acquire the company's transaction history and visitor attribute information. It can also acquire the progress status of construction and development. Step 2: The analysis unit analyzes the information acquired by the information acquisition unit. For example, the analysis unit analyzes document data on internal company rules and systems to generate appropriate responses. It can also analyze a company's transaction history and customer attributes to suggest optimal products. It can also analyze the progress of construction and development projects and provide the latest information. Step 3: The proposal unit generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit. For example, the proposal unit generates appropriate answers to questions about internal rules and systems. It can also propose optimal products based on the company's transaction history and customer attributes. It can also generate the latest information based on the progress of construction and development. Step 4: The notification department notifies the information generated by the proposal department. For example, the notification department notifies employees of answers regarding company rules and systems. It can also notify salesmen and store visitors of optimal products. It can also notify engineers of the progress of construction and development projects.

[0105] 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.

[0106] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 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.

[0110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0111] 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.

[0112] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0113] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0118] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0119] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0120] 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.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 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.

[0125] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0126] 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.

[0127] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0128] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0133] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0134] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0135] 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.

[0136] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0137] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 7, the 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.

[0140] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0141] 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.

[0142] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0143] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0144] 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.

[0145] The control object 443 includes a display device, LEDs in the eyes, and motors that drive 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.

[0146] 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.

[0147] 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.

[0148] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0149] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0150] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0151] 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.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0154] 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.

[0155] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0156] 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.

[0157] 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).

[0158] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0159] 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."

[0160] 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.

[0161] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0166] The hardware resource that executes the specific process 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 process may be a single processor.

[0167] 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.

[0168] 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.

[0169] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0170] 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.

[0171] 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. [Explanation of symbols]

[0172] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an information acquisition unit that acquires information; an analysis unit that analyzes the information acquired by the information acquisition unit; a proposal unit that generates optimal answers, products, and progress information based on the results of the analysis by the analysis unit; a notification unit that notifies the user of the information generated by the suggestion unit. A system characterized by:

2. The information acquisition unit Analyze employees' past question history and provide customized answers that are best suited to each individual employee 2. The system of claim 1.

3. The information acquisition unit Track changes to internal rules and systems to always provide the latest information 2. The system of claim 1.

4. The information acquisition unit Analyze employees' emotions when asking questions and generate answers to reduce stress and anxiety 2. The system of claim 1.

5. The information acquisition unit Enable employees to check company rules and systems through voice input or chatbots 2. The system of claim 1.

Images