system

Abstract

We provide the system. [Solution] A system that receives company name, name, contact information, and consultation details as input, uses generative AI to obtain answers regarding industry analysis, industry challenges, and proposed solutions, examines the obtained answers and compiles a final response, and reports to the management the procedure for contacting the generative AI and the analysis results.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method executed by at least one processor, the method comprising the steps of: receiving a user utterance; adding the user utterance to a prompt including an instruction associated with a description of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance responding to the user utterance.

Prior Art Literature

Patent Literature

[0003]

Patent Document 1

Summary of the Invention

Problem to be Solved by the Invention

[0004] Small and medium-sized enterprise managers who want to use generative AI for business but do not know how to do so lack means to efficiently grasp their industry analysis, industry issues, and action measures.

Means for Solving the Problem

[0005] A system is provided that receives an input of a company name, a name, contact information, and consultation matters, and obtains answers for industry analysis, industry issues, and action measures using generative AI. The obtained answers are examined, final answers are summarized, and the procedure of making an inquiry to generative AI and the analysis results are reported to the manager. This allows small and medium-sized enterprise managers to use a simple management analysis service utilizing generative AI.

Brief Description of the Drawings

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 3 of Example 3. [Figure 16]This is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3. [Figure 17] This is a sequence diagram showing the processing flow of the data processing system in Example 1 of the Form 1 when an emotion engine is combined. [Figure 18] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] This is a sequence diagram showing the processing flow of a data processing system in another embodiment. [Modes for carrying out the invention]

[0007] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0008] First, let's explain the terminology used in the following explanation.

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

[0010] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in the present specification, when three or more matters are expressed by being connected by "and / or", the same concept as that for "A and / or B" applies.

[0014] [First Embodiment]

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

[0016] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. A server is an example of the data processing device 12.

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

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

[0019] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0023] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

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

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

[0027] "Example of form 1"

[0028] In one embodiment of the system, a small business owner enters their company name, name, contact information, and inquiry into a form on a website. This information is sent to a server and received by a generative AI. Based on the entered inquiry, the generative AI generates an industry analysis, industry challenges, and proposed solutions. The generated responses are reviewed by experts, and a final response is compiled. The final response is sent to the business owner via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0029] "Example of form 2"

[0030] As a concrete example, if the consultation topic is "the possibility of a new business venture," the generative AI will analyze the market size, competitive landscape, and market growth potential of the relevant industry. It will also propose key industry challenges and solutions to those challenges. This information is reviewed by experts, and a final answer is compiled. This answer is sent to the management via email, and the procedure for contacting the generative AI and the analysis results are also reported simultaneously.

[0031] The following describes the processing flow for each example of the form.

[0032] "Example of form 1"

[0033] Step 1: Small business owners enter their company name, name, contact information, and inquiry details into a form on the website.

[0034] Step 2: The entered information is sent to the server and received by the generative AI.

[0035] Step 3: The generative AI generates industry analysis, industry challenges, and proposed solutions based on the input consultation details.

[0036] Step 4: The generated responses are reviewed by experts, and the final responses are compiled.

[0037] Step 5: The final response is sent to the management via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0038] "Example of form 2"

[0039] Step 1: If the consultation topic is "the possibility of a new business," the generative AI analyzes the market size, competitive landscape, and market growth potential of the relevant industry.

[0040] Step 2: Generative AI also proposes key industry challenges and solutions to those challenges.

[0041] Step 3: This information is reviewed by experts, and a final answer is compiled.

[0042] Step 4: This response is sent to management via email, along with a report of the steps taken to query the generative AI and the analysis results.

[0043] (Example 1)

[0044] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0045] The process of industry analysis, information gathering for problem-solving, and proposal development faced by small and medium-sized enterprise (SME) managers is time-consuming and labor-intensive. In particular, when specialized knowledge is required, it becomes necessary to hire external experts, which incurs costs. There is a need for a way to solve these problems and obtain industry analysis and proposals quickly and efficiently.

[0046] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0047] In this invention, the server includes means for providing an interface for users to input information, means for transmitting the input information to a processing unit via a communication device, and means for the processing unit to analyze the received information and generate and transmit prompt statements to a generation AI model. This enables users to quickly obtain industry analysis and suggestions.

[0048] "Users" refers to individuals or organizations that use the system to input information and receive industry analysis and recommendations.

[0049] "Interface" refers to the means, such as screens or forms, that users are provided with to input information.

[0050] "Communication equipment" refers to network devices and software used to transmit input information to a processing unit.

[0051] A "processing unit" refers to a computer system that analyzes received information and generates and sends prompt messages to a generation AI model.

[0052] A "generative AI model" refers to an artificial intelligence algorithm or program that automatically generates data analysis and suggestions based on prompt text.

[0053] A "prompt statement" refers to a text-based sentence generated to provide specific instructions to a generative AI model.

[0054] "Expert" refers to an individual or group with the knowledge to review the generated proposals and compile the final response.

[0055] "Electronic communication means" refers to communication methods such as email and websites used to report the final answer, the procedure for querying the generated AI model, and the analysis results to the user.

[0056] The embodiment for carrying out this invention is configured as follows.

[0057] The user enters their company name, name, contact information, and inquiry details using an interface provided via a web browser. The terminal sends this input information to the server as an HTTP request. The server analyzes the received information and generates prompt messages to send to the AI ​​model based on the inquiry details. These prompt messages provide specific instructions to the AI ​​model.

[0058] For the generative AI model, for example, the GPT model from OpenAI® can be used. The server sends the generated prompt text to this generative AI model, which automatically generates industry analysis, industry challenges, and solutions. The generated content is sent to experts via the server, who review it, make corrections as needed, and compile the final response.

[0059] The final response is sent from the server to the user via email. This email also includes the steps taken to query the generative AI model and the analysis results. This allows users to receive industry analysis and recommendations quickly and efficiently.

[0060] For example, if a user enters a request such as "I want to think about a new marketing strategy," the server will generate a prompt message such as "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." Based on this prompt message, the AI ​​model generates relevant industry analysis and suggestions, which are then provided to the user.

[0061] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0062] Step 1:

[0063] The user accesses the interface provided via a web browser and enters the company name, personal name, contact information, and inquiry details. The entered information is packaged as an HTTP request on the user's device. This request is then prepared to be sent to the server.

[0064] Step 2:

[0065] The terminal sends an HTTP request to the server containing the information entered by the user. The server receives this request, parses the data, and extracts the company name, name, contact information, and inquiry details. This data is temporarily stored on the server and passed on to the next processing step.

[0066] Step 3:

[0067] The server generates a prompt message to send to the AI ​​model based on the received inquiry. For example, if the input inquiry is "I want to think of a new marketing strategy," the prompt message would be "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." This prompt message is then sent to the AI ​​model.

[0068] Step 4:

[0069] The server sends the generated prompt text to the AI ​​model. The AI ​​model receives the prompt text and automatically generates industry analysis, industry challenges, and proposed solutions. The AI ​​model analyzes the input prompt text, collects and analyzes relevant data, and outputs appropriate suggestions.

[0070] Step 5:

[0071] The server sends the industry analysis and suggestions received from the generated AI model to experts. The experts review this content and make revisions as needed. The final response is then returned to the server.

[0072] Step 6:

[0073] The server sends the final answer, verified by experts, to the user via email. The email also includes the steps taken to query the generative AI model and the analysis results. The user can review the received email and utilize the provided information to perform industry analysis and make recommendations.

[0074] (Application Example 1)

[0075] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0076] Retail store operators face challenges in obtaining appropriate information and advice to quickly and efficiently resolve issues related to store operations. Furthermore, they have limited means of obtaining reliable solutions that incorporate expert opinions.

[0077] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0078] This invention includes a server that receives company name, name, contact information, and consultation details as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that allows store operators to consult about store operations using a mobile device; a server that allows the generative AI to propose industry analysis and solutions to challenges related to store operations; and a server that allows experts to review the proposals and send the final answer to the operator. This enables store operators to obtain reliable solutions quickly, efficiently, and with utmost speed.

[0079] A "company name" is a name used to identify a specific legal entity or organization.

[0080] "Name" refers to a name used to identify an individual.

[0081] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0082] "Consultation items" refer to the specific problems or questions that you wish to resolve.

[0083] "Generative AI" refers to artificial intelligence systems that automatically perform analysis and make suggestions based on input information.

[0084] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0085] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0086] "Measures to address a problem" refer to specific methods or strategies for solving a particular issue.

[0087] The "final answer" is the final solution after experts have reviewed and modified the proposal from the generative AI.

[0088] "Operator" refers to an individual or legal entity responsible for the management and operation of a physical store.

[0089] A "personal digital assistant" (PDI) is a portable electronic device such as a smartphone or tablet.

[0090] An "expert" is a person who possesses advanced knowledge and experience in a particular field.

[0091] The system for implementing this invention mainly consists of a server, a personal digital assistant (PDTA), a generative AI, and the cooperation of experts. The server receives company names, names, contact information, and consultation details transmitted from the PDTA. The PDTA refers to portable electronic devices such as smartphones and tablets. The users, who are operators of physical stores, use these devices to consult about store operations.

[0092] The server transmits the received information to a generative AI, which automatically generates industry analysis, industry challenges, and solutions based on the input consultation. The generative AI utilizes advanced artificial intelligence models such as OpenAI GPT-4®. The AI-generated proposals are reviewed by experts and modified as needed. The final response is sent from the server to the operator via email or website.

[0093] For example, if an operator inputs "I would like to discuss how to promote a new product," the generative AI will analyze industry trends and success stories and propose a specific promotion strategy. An example of a prompt used in this case would be, "I would like to discuss how to promote a new product. Please provide suggestions based on industry trends and success stories."

[0094] This system allows brick-and-mortar store operators to obtain quick, efficient, and reliable solutions.

[0095] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0096] Step 1:

[0097] The user uses a mobile device to enter the company name, their name, contact information, and the details of their inquiry. The entered data is sent from the device to the server. Here, "input" refers to the text data entered by the user on the device, and "output" refers to the data sent to the server.

[0098] Step 2:

[0099] The server sends the received data to the generative AI. The server converts the data into an appropriate format and generates prompt statements suitable for the generative AI model. These prompt statements form the basis for the AI ​​to generate industry analysis and problem solutions. The input is the user's inquiry, and the output is the prompt statements sent to the generative AI.

[0100] Step 3:

[0101] Generative AI automatically generates industry analysis, industry challenges, and proposed solutions based on prompt messages received from a server. The AI ​​utilizes its internal database and learning models to perform analysis related to the input information. The input is the prompt message, and the output is the generated analysis results and suggestions.

[0102] Step 4:

[0103] The server receives the output from the generative AI and sends it to experts. The experts review the proposals generated by the AI ​​and make revisions as needed. The input is the proposal from the AI, and the output is the final proposal reviewed and revised by the experts.

[0104] Step 5:

[0105] The server sends the final proposal, reviewed by experts, to the user. The user receives the final proposal via email or website. The input is the proposal reviewed by experts, and the output is the final proposal sent to the user.

[0106] This series of processes allows users to obtain reliable solutions quickly, efficiently, and effectively.

[0107] (Example 2)

[0108] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0109] In today's business environment, managers demand rapid and accurate industry analysis and solutions to challenges. However, traditional methods present challenges, such as the significant time and effort required for information gathering and analysis, making quick decision-making difficult.

[0110] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0111] This invention includes a server that receives consultation requests as input, an information processing device that collects market data using a generated AI model, and automatically generates industry analysis, industry challenges, and solutions; a means for experts to examine the generated analysis results and create a final response; and a means for transmitting the final response to management using electronic communication and reporting the procedures and analysis results of the queries made to the generated AI model. This enables the provision of rapid and accurate industry analysis and solutions to challenges.

[0112] "Consultation items" refer to the specific details that users input into the information processing device, requesting industry analysis or solutions to their problems.

[0113] An "information processing device" is a device that uses a generative AI model to collect market data and automatically generate industry analysis and solutions to problems.

[0114] A "generative AI model" is an artificial intelligence model that collects and analyzes relevant data based on the input prompt text.

[0115] "Market data" refers to data that includes information about the industry's market size, competitive landscape, and market growth potential.

[0116] "Industry analysis" is the process of evaluating the market size, competitive landscape, and market growth potential within a specific industry.

[0117] "Industry challenges" refer to the major problems or obstacles that a particular industry faces.

[0118] "Measures taken" refers to specific solutions or countermeasures for industry challenges.

[0119] An "expert" is someone who examines the analysis results generated by generative AI models and creates the final answer.

[0120] "Electronic communication methods" refer to communication methods such as email and websites used to send final responses and analysis results to management.

[0121] This invention begins with a user entering their inquiry using a terminal. The user enters specific details, such as "I would like you to analyze the potential of a new business." Based on the inquiry received from the user, the server uses a generative AI model to collect market data. In this process, the information processing device uses specific databases or APIs (e.g., market research databases or industry report APIs) to obtain data on relevant market size and competitive landscape.

[0122] The server inputs the collected data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing techniques to propose key industry challenges and solutions. These analysis results are sent to experts, who review the findings and formulate final answers.

[0123] The final response is sent to management via electronic means by the server. This email also includes the steps taken to query the generative AI model and the analysis results. An example of a specific prompt would be: "Regarding the potential of a new business, please analyze the market size, competitive landscape, and market growth potential of the relevant industry, and propose key challenges and solutions."

[0124] In this way, users can obtain rapid and accurate industry analysis and solutions to their problems.

[0125] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0126] Step 1:

[0127] Users access the system using a terminal and enter their inquiries. These inquiries are specific in nature, such as "I would like you to analyze the potential of a new business." This input forms the basis for subsequent data collection and analysis.

[0128] Step 2:

[0129] Based on the user's inquiries, the server generates prompt statements for the AI ​​model. These prompt statements include instructions for industry analysis and problem-solving. Using the generated prompt statements, the server collects market data from specific databases and APIs. For example, it might call an industry reporting API to obtain data on market size and competitive landscape.

[0130] Step 3:

[0131] The server inputs collected market data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing technology to propose key industry challenges and solutions. Specifically, the generative AI model analyzes market data, identifies trends and competitor activities, and proposes optimal strategies.

[0132] Step 4:

[0133] The server sends the analysis results generated by the generative AI model to experts. Experts review the received analysis results, make corrections and supplements as needed, and create a final answer. Leveraging their industry expertise, experts evaluate the generative AI model's proposals and develop actionable strategies.

[0134] Step 5:

[0135] The server sends the final response, prepared by experts, to management via electronic means. This email also includes the steps taken to query the generative AI model and the analysis results. Specifically, the server sends the final response as an email, which management receives and confirms.

[0136] (Application Example 2)

[0137] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0138] In developing new businesses or product categories in the market, operators face the challenge of difficulty in quickly and accurately grasping market size, competitive landscape, growth potential, and key challenges. As a result, operators are unable to efficiently obtain the information necessary for decision-making, making it difficult to formulate appropriate market entry strategies.

[0139] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0140] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain market analysis, competitive situation, growth potential, and problem proposals; a server that examines the obtained analysis results and compiles final proposals; a server that reports to the operator the procedure for querying the generative AI and the analysis results; and a server that sends the market analysis results via email. This enables the operator to quickly and accurately obtain the information necessary for entering the market for new businesses or product categories and to make effective decisions.

[0141] "Company information" refers to basic information about a company, such as its name, address, industry, and size.

[0142] "Personal information" refers to information that identifies a specific individual, such as their name, address, and contact information.

[0143] "Contact information" refers to information used to contact an individual or company, such as a phone number or email address.

[0144] "Consultation content" refers to the specific questions or issues that the operator asks the generative AI.

[0145] "Generative AI" is an artificial intelligence technology that automatically performs analysis and makes suggestions based on input data.

[0146] "Market analysis" refers to research and analysis conducted to evaluate the size, competitive landscape, growth potential, and other aspects of a particular market.

[0147] "Competitive landscape" refers to information such as the number of competitors, market share, and strategies within a particular market.

[0148] "Growth potential" is an indicator that shows how much a particular market or business is likely to grow in the future.

[0149] "Problem proposal" involves identifying key issues in a market or business and proposing solutions to them.

[0150] "Analysis results" refer to information obtained as a result of a generative AI performing market analysis and proposing solutions.

[0151] "Operator" refers to an individual or organization responsible for managing and operating an e-commerce site or business.

[0152] "Email" is a means of communication used to send and receive messages over the internet.

[0153] The system for carrying out this invention comprises a server and a user terminal. The server plays a central role in performing market analysis using a generative AI model. The user terminal functions as an interface for the operator to input information and receive results.

[0154] The server receives company information, personal information, contact information, and consultation details from the user's terminal. This information is input into a generative AI model (e.g., GPT-4), which automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are reviewed by the server and compiled into a final proposal.

[0155] The user terminal receives analysis results from the server and displays them to the operator. Furthermore, it has a function to send analysis results via email as needed. This allows the operator to quickly and accurately obtain the information necessary for market entry into new businesses or product categories.

[0156] For example, if the operator enters the prompt message, "I want to conduct a market analysis for a new eco-friendly household goods category," the server will use a generated AI model to analyze the market size, competitive landscape, growth potential, and key challenges, and provide the results. These results will be displayed on the user's terminal to support the operator's decision-making.

[0157] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0158] Step 1:

[0159] The user uses a device to input company information, personal information, contact information, and consultation details. This information is then prepared to be sent to the AI ​​model as prompt text. The entered data is then sent to the server.

[0160] Step 2:

[0161] The server inputs the received prompt message into a generating AI model (e.g., GPT-4). Based on the input information, the generating AI model automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are returned to the server.

[0162] Step 3:

[0163] The server examines the analysis results returned by the generated AI model and compiles them into a final proposal. In this process, it verifies the accuracy and relevance of the generated information and makes adjustments as needed.

[0164] Step 4:

[0165] The server sends the final proposal to the user's terminal. The user's terminal displays the received proposal to the administrator. The administrator can then make a decision based on the displayed information.

[0166] Step 5:

[0167] If necessary, the server will send the analysis results to the administrator via email. This feature allows the administrator to view the results even when offline.

[0168] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0169] "Example of form 1"

[0170] One embodiment of the present invention provides a system that combines an emotion engine. This system receives inquiries from business owners as input and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures. Furthermore, it uses the emotion engine to analyze the business owner's emotions and generates answers that reflect the results. Specifically, if a business owner inquires about "the possibility of a new business," the generative AI analyzes the market size, competitive situation, and market growth potential of the relevant industry. At the same time, the emotion engine recognizes the business owner's emotions and adjusts the generative AI's answers based on those emotions. For example, if the business owner is feeling anxious, the emotion engine conveys this information to the generative AI, and the generative AI generates answers that correspond to the business owner's emotions, such as making the answers to the business owner more careful or detailed.

[0171] "Example of form 2"

[0172] Furthermore, in another embodiment of the present invention, a system is provided that provides the procedure and analysis results of a query to a generative AI, as well as the sentiment analysis results from an emotion engine, via email or a website. Specifically, the analysis results from the generative AI and the emotion engine are reviewed by experts, and a final response is compiled. This response is sent to the manager via email, and the procedure and analysis results of the query to the generative AI, as well as the sentiment analysis results from the emotion engine, are also reported simultaneously. This allows the manager to understand how their emotions were analyzed and how the results were reflected in the response.

[0173] The following describes the processing flow for each example of the form.

[0174] "Example of form 1"

[0175] Step 1: The system receives inquiries from management.

[0176] Step 2: Generative AI generates answers regarding industry analysis, industry challenges, and proposed solutions.

[0177] Step 3: The emotion engine analyzes the emotions of the executives.

[0178] Step 4: Based on the analysis results of the emotion engine, the generative AI generates an emotionally appropriate response.

[0179] "Example of form 2"

[0180] Step 1: Generative AI and emotion engines perform analysis, and experts review the results.

[0181] Step 2: Experts compile the final answer.

[0182] Step 3: Send an email to the business owner containing the steps taken to query the generative AI, the analysis results, and the sentiment analysis results from the sentiment engine.

[0183] (Example 1)

[0184] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0185] There is a need to provide prompt and accurate analysis and answers to the questions that small and medium-sized business owners have regarding industry challenges and new business opportunities. However, traditional methods require the assistance of experts, which is time-consuming and costly. Furthermore, there is a problem of low satisfaction because answers do not take into account the feelings of business owners.

[0186] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0187] This invention includes a server that receives company information and consultation content as input, analyzes industry information using a generation AI model to generate problems and solutions, analyzes the inputter's emotions using an emotion analysis engine to adjust the generated responses, and has experts review the obtained responses to compile a final response. This enables rapid and accurate industry analysis and the provision of responses that take into account the emotions of business managers.

[0188] "Company information" refers to basic information used to identify a specific company or individual, such as company name, personal name, and contact information.

[0189] "Consultation details" refer to information that users enter to seek advice or solutions regarding a specific problem or issue.

[0190] A "generative AI model" is a type of artificial intelligence that analyzes industry information based on input data and automatically generates problems and solutions.

[0191] "Industry information" refers to data such as market size, competitive landscape, and market growth potential for a specific industry.

[0192] An "emotion analysis engine" is a technology that analyzes user emotions from their input and adjusts responses based on the results.

[0193] An "expert" is someone who possesses advanced knowledge and experience in a specific field, and whose role is to examine the generated answers and make corrections or additions as necessary.

[0194] "Electronic communication means" refers to methods for sending and receiving information via email, websites, etc.

[0195] The embodiment for carrying out this invention is configured as follows.

[0196] Users enter company information and their inquiry details into a form on the website using their device. Specifically, they enter the company name, their name, contact information, and the details of their inquiry. For example, "I would like to discuss the possibilities of a new business."

[0197] The server receives information sent by the user and transmits it to a generative AI model. This generative AI model analyzes specific industry information and generates problems and solutions. The generative AI model is designed to process data such as market size, competitive landscape, and market growth potential.

[0198] Furthermore, the server uses an emotion analysis engine to analyze the user's emotions from their input. This emotion analysis engine determines whether the user is experiencing emotions such as anxiety or anticipation, and communicates the result to the generating AI model.

[0199] The generative AI model adjusts its responses to reflect the user's emotions based on information from the emotion analysis engine. For example, if the user is feeling anxious, the generative AI model will generate a more polite and reassuring response.

[0200] Finally, experts review the generated answers and make corrections or additions as needed. The server then sends the final, expert-verified answers to the user via electronic means, such as email. The steps taken to query the generating AI model and the analysis results are also reported simultaneously.

[0201] An example of a prompt message would be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape."

[0202] The flow of the specific processing in Example 1 will be explained using Figure 15.

[0203] Step 1:

[0204] The user uses their device to enter company information (company name, name, contact information) and their inquiry into a form on the website. A typical prompt might be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape." The device then sends this information to the server.

[0205] Step 2:

[0206] The server processes the information received from the user and sends it to the generating AI model. The server stores the entered company information and consultation details in a database and converts the data into a format that the generating AI model can analyze.

[0207] Step 3:

[0208] The generative AI model analyzes industry information based on data received from the server. Specifically, it collects data such as market size, competitive landscape, and market growth potential, and extracts information relevant to the inquiry. Using this data, the generative AI model generates an initial response to the user's inquiry.

[0209] Step 4:

[0210] The server receives the initial response from the generated AI model and sends it to the sentiment analysis engine. The sentiment analysis engine analyzes the user's input and recognizes the emotions the user is experiencing (anxiety, expectation, etc.).

[0211] Step 5:

[0212] The emotion analysis engine returns the analysis results to the generative AI model. The generative AI model takes the emotion analysis results into consideration and adjusts the response to reflect the user's emotions. For example, if the user is feeling anxious, the generative AI model will make the response more detailed and reassuring.

[0213] Step 6:

[0214] The server receives the adjusted responses from the generating AI model and sends them to experts. The experts review the generated responses and make corrections or additions as needed.

[0215] Step 7:

[0216] The server sends the final answer, verified by experts, to the user via electronic communication. Specifically, the final answer is delivered to the user via email. The procedure used to query the generative AI model and the analysis results are also reported simultaneously.

[0217] (Application Example 1)

[0218] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0219] Small and medium-sized enterprise (SME) managers often lack the specialized knowledge and resources necessary for industry analysis and strategy development. Furthermore, managers' emotions and stress can influence decision-making, requiring emotionally sensitive advice. In addition, factories need concrete improvement measures for increased production efficiency and machine maintenance, but there is a lack of efficient means to provide these.

[0220] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0221] This invention includes a server that receives company name, name, contact information, and consultation topic as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; an emotion engine that analyzes the consultant's emotions and adjusts the generative AI's answers based on those emotions; a server that analyzes the production efficiency and machine status in the factory and proposes improvement measures; and a server that adjusts the answers according to the consultant's emotions. As a result, managers can efficiently obtain expert industry analysis and solutions, and receive advice that takes their emotions into consideration. Furthermore, factories can quickly obtain specific improvement measures regarding production efficiency and machine maintenance.

[0222] A "company name" is a name used to identify a specific legal entity or organization.

[0223] "Name" refers to a name used to identify an individual.

[0224] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0225] "Consultation items" refer to the specific problems or issues that the business owner seeks to resolve.

[0226] "Generative AI" refers to artificial intelligence technology that automatically generates analyses and responses based on input information.

[0227] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0228] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0229] A "solution" is a specific action plan to solve a particular problem.

[0230] The "emotional engine" is a technique that analyzes the client's emotions and incorporates the results into other processes.

[0231] "Production efficiency" is an indicator that shows the efficiency of resource utilization in a factory or production line.

[0232] "Machine status" refers to information indicating the operating status and performance of machinery and equipment within a factory.

[0233] An "improvement plan" is a specific method for solving the current problem and achieving a better state.

[0234] The system that realizes this invention operates through the collaboration of three parties: a server, a terminal, and a user. The server receives company name, name, contact information, and consultation topic as input, and uses generative AI to generate answers regarding industry analysis, industry challenges, and proposed solutions. The generated answers are reviewed by experts, and the final answers are compiled. The server reports to the management the procedure for which it queried the generative AI and the analysis results.

[0235] Furthermore, the server uses an emotion engine to analyze the client's emotions and adjusts the generative AI's response based on those emotions. This makes it possible to provide more thoughtful and detailed answers if the business owner is feeling anxious.

[0236] The terminal analyzes production efficiency and machine status in the factory and proposes improvement measures. Utilizing generative AI and an emotion engine, the terminal provides analysis based on the manager's consultation content and emotionally responsive advice.

[0237] For example, if a factory manager consults the AI ​​saying, "I want to improve the efficiency of the production line," the generative AI will suggest specific steps to increase production efficiency. If the emotion engine detects the manager's anxiety, it will provide more detailed steps.

[0238] An example of a prompt message is, "Please suggest ways to improve production efficiency: We want to increase the efficiency of the production line."

[0239] This system utilizes generative AI through the OpenAI API and performs sentiment analysis using the EmotionEngine library. This allows managers to efficiently obtain expert industry analysis and action plans, and receive emotionally sensitive advice. Furthermore, factories can quickly obtain concrete improvement measures for increasing production efficiency and machine maintenance.

[0240] The flow of a specific process in Application Example 1 will be explained using Figure 16.

[0241] Step 1:

[0242] The user uses a device to enter the company name, name, contact information, and inquiry details. The entered data is sent to the server. The server receives this data and prepares it to be passed on to the generative AI.

[0243] Step 2:

[0244] The server generates prompts for the generative AI and, based on the input data, generates industry analysis, industry challenges, and proposed solutions. Specifically, it uses a generative AI model to analyze market trends and competitive situations related to the input consultation and proposes appropriate solutions. The generated response is provided as output.

[0245] Step 3:

[0246] The server analyzes the user's emotions using an emotion engine. The user's consultation content and past interactions are used as input. The emotion engine evaluates the user's emotional state and reflects the results in the output of the generative AI. This results in a response that is adjusted according to the user's emotions.

[0247] Step 4:

[0248] The server sends the generated responses to experts for review. The experts review the responses and make corrections or additions as needed. The final responses are compiled and sent back to the server.

[0249] Step 5:

[0250] The server reports the final response, the steps taken to query the generative AI, and the analysis results to the user. The report is delivered via email or website. This allows the user to receive expert industry analysis and actionable strategies.

[0251] Step 6:

[0252] The terminal analyzes production efficiency and machine status in a factory and proposes improvement measures. Factory operation data and machine operating status are used as input. Utilizing generative AI and an emotion engine, it provides analysis based on the manager's consultation content and emotionally responsive advice. Specific improvement measures are provided as output.

[0253] (Example 2)

[0254] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0255] In today's business environment, managers are required to conduct rapid and accurate industry analysis and develop solutions to challenges. However, extracting useful data from vast amounts of information and making appropriate decisions is not easy. Furthermore, understanding the influence of a manager's own emotions on decision-making is also important, but there is a lack of objective means to evaluate this.

[0256] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0257] This invention includes a server that receives information from users as input, analyzes industry information using a generative AI model, and automatically generates problems and their solutions; a server that has experts evaluate the generated information and create a final answer; and a server that reports to managers the procedures for querying the generative AI model, the analysis results, and the sentiment analysis results. This enables managers to obtain rapid and accurate industry analysis and problem solutions, and to objectively understand the influence of their own emotions on decision-making.

[0258] A "user" is an individual or organization that inputs information into the system and seeks industry analysis or solutions to problems.

[0259] A "generative AI model" is an artificial intelligence algorithm that analyzes industry-related data based on input information and automatically generates problems and solutions.

[0260] An "expert" is an individual or group that possesses the knowledge and experience to evaluate information generated by generative AI models and formulate a final answer.

[0261] A "manager" is an individual or organization that requires industry analysis and problem-solving, and is responsible for making final decisions.

[0262] "Sentiment analysis results" are data that objectively shows the impact of user input on their emotions and their influence on decision-making.

[0263] "Electronic communication means" refers to means of transmitting information electronically, including email and websites.

[0264] This invention is a system that provides industry analysis and problem-solving solutions using generative AI models. Specific embodiments of this system are described below.

[0265] Users access the system using a terminal and enter prompt messages. For example, they might enter a specific question such as, "Please tell me about the potential for new business ventures." These prompt messages serve as the basic data for the system to perform industry analysis.

[0266] The server uses a generative AI model to process the prompt text received from the user. Specifically, it leverages a generative AI model such as OpenAI's GPT series to collect and analyze relevant industry data based on the input prompt text. This analysis includes market size, competitive landscape, and market growth potential.

[0267] Furthermore, the server uses an emotion engine to perform sentiment analysis on user input. This allows for the evaluation of the impact of user emotions on decision-making.

[0268] The generated industry analysis and sentiment analysis results are sent from the server to experts. Based on this information, the experts create the final answers. Their knowledge and experience further refine the information provided by the generated AI model, leading to actionable suggestions.

[0269] Ultimately, the server sends the expert-compiled answers to management via electronic communication. This communication includes the steps taken when querying the generative AI model, the analysis results, and the sentiment analysis results. This allows management to quickly obtain industry analysis and problem solutions, and to understand how their own emotions influence decision-making.

[0270] The flow of the specific processing in Example 2 will be explained using Figure 17.

[0271] Program processing steps

[0272] Step 1: The user enters a prompt.

[0273] Input: A user uses a terminal to input a prompt sentence for a generative AI model. By way of example, the user inputs a question: "Please tell me about the potential of a new business."

[0274] Output: The prompt sentence is transmitted to a server.

[0275] Step 2: The server analyzes data using a generative AI model

[0276] Input: The server receives the prompt sentence obtained from the user as an input.

[0277] Data processing / calculation: The server uses a generative AI model (e.g., OpenAI's GPT series) to analyze the market size, competitive situation and market growth potential of the relevant industry based on the prompt sentence.

[0278] Output: As an analysis result, information relating to the market size, major competitors and growth potential of the industry is generated.

[0279] Step 3: The server performs sentiment analysis using a sentiment engine

[0280] Input: The server receives the user's prompt sentence as an input.

[0281] Data processing / calculation: The server uses a sentiment engine to analyze the sentiment included in the prompt sentence.

[0282] Output: As a sentiment analysis result, data relating to the user's sentiment state is generated. By way of example, the result "the user has positive sentiment toward the new business" is obtained.

[0283] Step 4: The server transmits the analysis results to an expert

[0284] Input: The industry analysis result from the generative AI model and the sentiment analysis result from the sentiment engine.

[0285] Data Processing / Calculation: The server organizes the generated data and converts it into a format that is easy for experts to evaluate.

[0286] Output: The organized analysis results are sent to the experts.

[0287] Step 5: Experts compile the final answer.

[0288] Input: Analysis results and sentiment analysis results of the generated AI model sent from the server.

[0289] Data Processing / Calculation: Experts use industry knowledge to create the final answer based on the information received.

[0290] Output: The final answer to be provided to management.

[0291] Step 6: The server sends the results to management via email.

[0292] Input: The final answer compiled by the expert, the procedure used to query the generative AI model, the analysis results, and the sentiment analysis results.

[0293] Data processing / calculation: The server compiles the final answers and analysis results into a single report.

[0294] Output: Send the final response and analysis results to management via email.

[0295] (Application Example 2)

[0296] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0297] Modern managers and individuals need to quickly and accurately grasp industry trends and market challenges to make appropriate decisions. However, extracting and analyzing useful data from enormous volumes of information is no easy task. Furthermore, for personal expense management, there is also the problem that it is difficult to obtain effective advice that takes into account purchase history and emotions.

[0298] The specifying process performed by the specifying processing unit 290 of the data processing apparatus 12 in Application Example 2 is implemented by the following respective means.

[0299] In the present invention, the server includes: means for receiving corporate information, personal information, contact information, and consultation content as inputs, and obtaining responses for industry analysis, industry issues, and action measures using generative AI; means for examining the obtained responses and compiling a final response; means for reporting the procedure of querying the generative AI and the analysis results to the manager; means for analyzing the user's purchase history and expenditure pattern to propose an optimal expenditure management plan and money-saving methods; and means for analyzing the user's emotion using an emotion engine to provide advice for preventing wasteful spending. This enables managers to quickly grasp industry trends, and allows individuals to manage their expenses in consideration of their emotions.

[0300] "Corporate information" refers to basic information about a company such as its name, location, and contact information.

[0301] "Personal information" refers to basic information about an individual such as name, address, and contact information.

[0302] "Contact information" refers to information for contacting, such as a telephone number or e-mail address.

[0303] "Consultation content" refers to content that specifically describes problems or questions held by managers or individuals.

[0304] "Generative AI" refers to a system that analyzes data using artificial intelligence technology and automatically generates information and proposals in accordance with specific purposes.

[0305] "Industry analysis" refers to the process of evaluating the market size, competitive landscape, and growth potential of a particular industry.

[0306] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0307] "Measures taken" refers to specific methods or strategies implemented to solve a particular problem.

[0308] "Purchase history" refers to a record of purchases a user has made in the past.

[0309] "Spending patterns" refer to data that shows the trends and characteristics of users' consumption behavior.

[0310] A "spending management plan" refers to a plan or proposal for effectively managing a user's spending.

[0311] An "emotion engine" refers to a system that analyzes a user's emotions and provides information based on the results.

[0312] "Wasteful spending" refers to the act of consuming resources or money in excess of what is necessary.

[0313] "Advice" refers to suggestions or proposals given regarding a specific problem.

[0314] The system for implementing this invention operates in a network environment including a server and user terminals. The server receives corporate information, personal information, contact information, and consultation details, and uses generative AI to automatically generate industry analysis, industry challenges, and solutions. OpenAI's GPT-3 (registered trademark) is used as the generative AI. Experts review the analysis results obtained from the server and compile a final response.

[0315] The user terminal is a smartphone or computer, which receives the final response from the server. The user inputs their purchase history and spending patterns, and the server uses this information to suggest spending management plans and saving methods. Furthermore, it uses an emotion engine to analyze the user's emotions and provide advice to prevent wasteful spending. A general emotion analysis tool is used as the emotion engine.

[0316] For example, if a user feels that they have been spending too much money lately, the server will input the following prompt into the AI ​​model:

[0317] Example of a prompt:

[0318] Analyze the spending pattern for the following data: {"amount": 50, "category": "food"}, {"amount": 200, "category": "electronics"}. Provide insights on how to manage spending more effectively.

[0319] This prompt prompt allows the generating AI to analyze the user's spending patterns and suggest effective spending management methods. The server sends the generated suggestions to the user's terminal, allowing the user to manage their spending based on them.

[0320] The flow of a specific process in Application Example 2 will be explained using Figure 18.

[0321] Step 1:

[0322] The user inputs company information, personal information, contact information, and consultation details using a terminal. This information is sent to the server. The server stores the received information in a database and generates prompts for input into a generative AI model.

[0323] Step 2:

[0324] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates industry analysis, industry challenges, and proposed solutions based on the prompt text. The generated information is returned to the server.

[0325] Step 3:

[0326] The server presents the information returned by the generative AI model to experts, who then examine the information and formulate a final answer. The answer, after being evaluated by the experts, is stored on the server.

[0327] Step 4:

[0328] Users input their purchase history and spending patterns using a terminal. This data is sent to a server. The server analyzes the received data and generates prompts to suggest spending management plans and saving methods.

[0329] Step 5:

[0330] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates spending management plans and saving methods based on the prompt text. The generated suggestions are returned to the server.

[0331] Step 6:

[0332] The server uses an emotion engine to analyze the user's emotions. It receives user feedback as input and performs emotion analysis. The analysis results are used to generate advice to prevent wasteful spending.

[0333] Step 7:

[0334] The server sends the generated spending plan, saving methods, and sentiment analysis results to the user's terminal. The user can receive this information through their terminal and use it to help manage their spending.

[0335] (Other examples)

[0336] Next, other embodiments will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0337] In today's business environment, companies are required to conduct rapid and accurate industry analysis and develop solutions to problems. However, traditional methods are time-consuming and labor-intensive, and they also have the challenge of not being able to respond while taking emotional factors into consideration.

[0338] The identification process performed by the identification processing unit 290 of the data processing device 12 in other embodiments is realized by the following means.

[0339] This invention includes means for a server to receive information from a user and generate prompts to instruct a generative AI model to automatically generate answers regarding industry analysis, industry challenges, and solutions for analyzing that information; means for an expert to review the generated answers and compile the final answers; means for using electronic communication means to report the procedures and analysis results of the queries made to the generative AI model to the user; and means for adjusting the generated answers using an emotion engine to analyze the user's emotions. This enables the rapid and accurate provision of industry analysis and solutions to challenges, as well as flexible responses that take into account the user's emotions.

[0340] A "user" is an individual or legal entity that uses the system to provide information seeking industry analysis or solutions to problems.

[0341] A "terminal" is a device used by a user to input information and send it to a server, and includes personal computers and smartphones.

[0342] A "server" is a computer system that analyzes information received from users, generates prompts for automatically creating industry analysis and problem-solving solutions using AI models, and then reports the results to the user.

[0343] A "generative AI model" is an artificial intelligence model that automatically generates industry analysis and problem-solving solutions based on input prompts; OpenAI's GPT-3 is an example of this type.

[0344] A "prompt message" is a text-based instruction generated by a server to instruct the AI ​​model to automatically generate industry analysis and problem-solving solutions.

[0345] An "emotion engine" is a software component that analyzes a user's emotions and adjusts the responses generated based on those results.

[0346] A "specialist" is a human professional whose role is to examine the answers automatically generated by generative AI models and to compile the final answer.

[0347] Modes for carrying out the invention

[0348] This invention is a system that automatically performs analysis and makes suggestions using a generative AI model, based on information provided by the user seeking industry analysis and solutions to problems. Specific embodiments of this system are described below.

[0349] Hardware and software configuration

[0350] Users use a personal computer or smartphone as their terminal and input information via a dedicated application or web interface. The information entered includes company name, consultation details, and contact information.

[0351] The terminal converts the entered information into JSON format and sends it to the server using the HTTPS protocol.

[0352] The server uses the Flask framework, implemented in Python, to parse the received JSON data. Natural language processing libraries (e.g., NLTK and spaCy) are used for the parsing.

[0353] Based on the analysis results, the server generates prompt statements to instruct the AI ​​model (e.g., OpenAI's GPT-3) to automatically generate industry analysis and problem solutions. These prompt statements are constructed using templates.

[0354] Data processing and data calculation

[0355] The server sends the generated prompt to the AI ​​model and receives the generated response via the API.

[0356] The server analyzes the user's emotions using an emotion engine (e.g., IBM Watson® Tone Analyzer). Based on the analysis results, it adjusts the generated responses.

[0357] Specific example

[0358] An example of a prompt message that is generated is: "Company name: ABC Corp, Inquiry topic: New product launch strategy, Contact: user@example.com. Please provide an industry analysis and solutions based on this."

[0359] The server presents the generated responses and sentiment analysis results to the experts, who then review the responses and make revisions as needed.

[0360] The server sends the final response to the user via electronic communication, and the user confirms the received information on their device.

[0361] This system allows users to obtain rapid and accurate industry analysis and problem-solving solutions, as well as flexible responses that take emotions into consideration.

[0362] The flow of a specific process in another embodiment will be explained using Figure 19.

[0363] Step 1:

[0364] Users access a dedicated application or web interface using their device and enter information such as company name, consultation details, and contact information. The entered information is converted to JSON format by the device. The converted JSON data is sent to the server using the HTTPS protocol.

[0365] Step 2:

[0366] The server parses the received JSON data using the Flask framework. Natural language processing libraries (e.g., NLTK and spaCy) are used for the parsing. As a result of the parsing, prompt statements are generated to instruct the generative AI model to automatically generate industry analysis and problem solutions. Specifically, these prompt statements are constructed using templates.

[0367] Step 3:

[0368] The server sends the generated prompt text to a generation AI model (e.g., OpenAI's GPT-3). The prompt text is sent via API, and the generation AI model provides industry analysis and problem-solving solutions. The received responses are temporarily stored on the server.

[0369] Step 4:

[0370] The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions. Specifically, it analyzes the user's emotions towards the generated response and uses the results to adjust the response. The adjusted response is then ready to be presented to an expert.

[0371] Step 5:

[0372] The server presents the generated responses and sentiment analysis results to the expert. The expert reviews the responses through a dedicated interface and makes corrections as needed. The revised final responses are then saved to a database by the server.

[0373] Step 6:

[0374] The server sends the final response to the user via electronic communication (e.g., SMTP protocol using a mail server). The user can then view the final response and analysis results received on their device.

[0375] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0376] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0377] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0378] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0379] [Second Embodiment]

[0380] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0381] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0382] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0383] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0384] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0385] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0386] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0387] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0388] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0389] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0390] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0391] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0392] "Example of form 1"

[0393] In one embodiment of the system, a small business owner enters their company name, name, contact information, and inquiry into a form on a website. This information is sent to a server and received by a generative AI. Based on the entered inquiry, the generative AI generates an industry analysis, industry challenges, and proposed solutions. The generated responses are reviewed by experts, and a final response is compiled. The final response is sent to the business owner via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0394] "Example of form 2"

[0395] As a concrete example, if the consultation topic is "the possibility of a new business venture," the generative AI will analyze the market size, competitive landscape, and market growth potential of the relevant industry. It will also propose key industry challenges and solutions to those challenges. This information is reviewed by experts, and a final answer is compiled. This answer is sent to the management via email, and the procedure for contacting the generative AI and the analysis results are also reported simultaneously.

[0396] The following describes the processing flow for each example of the form.

[0397] "Example of form 1"

[0398] Step 1: Small business owners enter their company name, name, contact information, and inquiry details into a form on the website.

[0399] Step 2: The entered information is sent to the server and received by the generative AI.

[0400] Step 3: The generative AI generates industry analysis, industry challenges, and proposed solutions based on the input consultation details.

[0401] Step 4: The generated responses are reviewed by experts, and the final responses are compiled.

[0402] Step 5: The final response is sent to the management via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0403] "Example of form 2"

[0404] Step 1: If the consultation topic is "the possibility of a new business," the generative AI analyzes the market size, competitive landscape, and market growth potential of the relevant industry.

[0405] Step 2: Generative AI also proposes key industry challenges and solutions to those challenges.

[0406] Step 3: This information is reviewed by experts, and a final answer is compiled.

[0407] Step 4: This response is sent to management via email, along with a report of the steps taken to query the generative AI and the analysis results.

[0408] (Example 1)

[0409] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0410] The process of industry analysis, information gathering for problem-solving, and proposal development faced by small and medium-sized enterprise (SME) managers is time-consuming and labor-intensive. In particular, when specialized knowledge is required, it becomes necessary to hire external experts, which incurs costs. There is a need for a way to solve these problems and obtain industry analysis and proposals quickly and efficiently.

[0411] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0412] In this invention, the server includes means for providing an interface for users to input information, means for transmitting the input information to a processing unit via a communication device, and means for the processing unit to analyze the received information and generate and transmit prompt statements to a generation AI model. This enables users to quickly obtain industry analysis and suggestions.

[0413] "Users" refers to individuals or organizations that use the system to input information and receive industry analysis and recommendations.

[0414] "Interface" refers to the means, such as screens or forms, that users are provided with to input information.

[0415] "Communication equipment" refers to network devices and software used to transmit input information to a processing unit.

[0416] A "processing unit" refers to a computer system that analyzes received information and generates and sends prompt messages to a generation AI model.

[0417] A "generative AI model" refers to an artificial intelligence algorithm or program that automatically generates data analysis and suggestions based on prompt text.

[0418] A "prompt statement" refers to a text-based sentence generated to provide specific instructions to a generative AI model.

[0419] "Expert" refers to an individual or group with the knowledge to review the generated proposals and compile the final response.

[0420] "Electronic communication means" refers to communication methods such as email and websites used to report the final answer, the procedure for querying the generated AI model, and the analysis results to the user.

[0421] The embodiment for carrying out this invention is configured as follows.

[0422] The user enters their company name, name, contact information, and inquiry details using an interface provided via a web browser. The terminal sends this input information to the server as an HTTP request. The server analyzes the received information and generates prompt messages to send to the AI ​​model based on the inquiry details. These prompt messages provide specific instructions to the AI ​​model.

[0423] For the generative AI model, for example, OpenAI's GPT model can be used. The server sends the generated prompt text to this generative AI model, which automatically generates industry analysis, industry challenges, and solutions. The generated content is sent to experts via the server, who review it, make corrections as needed, and compile the final response.

[0424] The final response is sent from the server to the user via email. This email also includes the steps taken to query the generative AI model and the analysis results. This allows users to receive industry analysis and recommendations quickly and efficiently.

[0425] For example, if a user enters a request such as "I want to think about a new marketing strategy," the server will generate a prompt message such as "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." Based on this prompt message, the AI ​​model generates relevant industry analysis and suggestions, which are then provided to the user.

[0426] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0427] Step 1:

[0428] The user accesses the interface provided via a web browser and enters the company name, personal name, contact information, and inquiry details. The entered information is packaged as an HTTP request on the user's device. This request is then prepared to be sent to the server.

[0429] Step 2:

[0430] The terminal sends an HTTP request to the server containing the information entered by the user. The server receives this request, parses the data, and extracts the company name, name, contact information, and inquiry details. This data is temporarily stored on the server and passed on to the next processing step.

[0431] Step 3:

[0432] The server generates a prompt message to send to the AI ​​model based on the received inquiry. For example, if the input inquiry is "I want to think of a new marketing strategy," the prompt message would be "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." This prompt message is then sent to the AI ​​model.

[0433] Step 4:

[0434] The server sends the generated prompt text to the AI ​​model. The AI ​​model receives the prompt text and automatically generates industry analysis, industry challenges, and proposed solutions. The AI ​​model analyzes the input prompt text, collects and analyzes relevant data, and outputs appropriate suggestions.

[0435] Step 5:

[0436] The server sends the industry analysis and suggestions received from the generated AI model to experts. The experts review this content and make revisions as needed. The final response is then returned to the server.

[0437] Step 6:

[0438] The server sends the final answer, verified by experts, to the user via email. The email also includes the steps taken to query the generative AI model and the analysis results. The user can review the received email and utilize the provided information to perform industry analysis and make recommendations.

[0439] (Application Example 1)

[0440] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0441] Retail store operators face challenges in obtaining appropriate information and advice to quickly and efficiently resolve issues related to store operations. Furthermore, they have limited means of obtaining reliable solutions that incorporate expert opinions.

[0442] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0443] This invention includes a server that receives company name, name, contact information, and consultation details as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that allows store operators to consult about store operations using a mobile device; a server that allows the generative AI to propose industry analysis and solutions to challenges related to store operations; and a server that allows experts to review the proposals and send the final answer to the operator. This enables store operators to obtain reliable solutions quickly, efficiently, and with utmost speed.

[0444] A "company name" is a name used to identify a specific legal entity or organization.

[0445] "Name" refers to a name used to identify an individual.

[0446] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0447] "Consultation items" refer to the specific problems or questions that you wish to resolve.

[0448] "Generative AI" refers to artificial intelligence systems that automatically perform analysis and make suggestions based on input information.

[0449] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0450] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0451] "Measures to address a problem" refer to specific methods or strategies for solving a particular issue.

[0452] The "final answer" is the final solution after experts have reviewed and modified the proposal from the generative AI.

[0453] "Operator" refers to an individual or legal entity responsible for the management and operation of a physical store.

[0454] A "personal digital assistant" (PDI) is a portable electronic device such as a smartphone or tablet.

[0455] An "expert" is a person who possesses advanced knowledge and experience in a particular field.

[0456] The system for implementing this invention mainly consists of a server, a personal digital assistant (PDTA), a generative AI, and the cooperation of experts. The server receives company names, names, contact information, and consultation details transmitted from the PDTA. The PDTA refers to portable electronic devices such as smartphones and tablets. The users, who are operators of physical stores, use these devices to consult about store operations.

[0457] The server sends the received information to a generative AI, which automatically generates industry analysis, industry challenges, and solutions based on the input consultation. The generative AI utilizes advanced artificial intelligence models such as OpenAI GPT-4. The AI-generated proposals are reviewed by experts and modified as needed. The final response is sent from the server to the operator via email or website.

[0458] For example, if an operator inputs "I would like to discuss how to promote a new product," the generative AI will analyze industry trends and success stories and propose a specific promotion strategy. An example of a prompt used in this case would be, "I would like to discuss how to promote a new product. Please provide suggestions based on industry trends and success stories."

[0459] This system allows brick-and-mortar store operators to obtain quick, efficient, and reliable solutions.

[0460] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0461] Step 1:

[0462] The user uses a mobile device to enter the company name, their name, contact information, and the details of their inquiry. The entered data is sent from the device to the server. Here, "input" refers to the text data entered by the user on the device, and "output" refers to the data sent to the server.

[0463] Step 2:

[0464] The server sends the received data to the generative AI. The server converts the data into an appropriate format and generates prompt statements suitable for the generative AI model. These prompt statements form the basis for the AI ​​to generate industry analysis and problem solutions. The input is the user's inquiry, and the output is the prompt statements sent to the generative AI.

[0465] Step 3:

[0466] Generative AI automatically generates industry analysis, industry challenges, and proposed solutions based on prompt messages received from a server. The AI ​​utilizes its internal database and learning models to perform analysis related to the input information. The input is the prompt message, and the output is the generated analysis results and suggestions.

[0467] Step 4:

[0468] The server receives the output from the generative AI and sends it to experts. The experts review the proposals generated by the AI ​​and make revisions as needed. The input is the proposal from the AI, and the output is the final proposal reviewed and revised by the experts.

[0469] Step 5:

[0470] The server sends the final proposal, reviewed by experts, to the user. The user receives the final proposal via email or website. The input is the proposal reviewed by experts, and the output is the final proposal sent to the user.

[0471] This series of processes allows users to obtain reliable solutions quickly, efficiently, and effectively.

[0472] (Example 2)

[0473] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0474] In today's business environment, managers demand rapid and accurate industry analysis and solutions to challenges. However, traditional methods present challenges, such as the significant time and effort required for information gathering and analysis, making quick decision-making difficult.

[0475] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0476] This invention includes a server that receives consultation requests as input, an information processing device that collects market data using a generated AI model, and automatically generates industry analysis, industry challenges, and solutions; a means for experts to examine the generated analysis results and create a final response; and a means for transmitting the final response to management using electronic communication and reporting the procedures and analysis results of the queries made to the generated AI model. This enables the provision of rapid and accurate industry analysis and solutions to challenges.

[0477] "Consultation items" refer to the specific details that users input into the information processing device, requesting industry analysis or solutions to their problems.

[0478] An "information processing device" is a device that uses a generative AI model to collect market data and automatically generate industry analysis and solutions to problems.

[0479] A "generative AI model" is an artificial intelligence model that collects and analyzes relevant data based on the input prompt text.

[0480] "Market data" refers to data that includes information about the industry's market size, competitive landscape, and market growth potential.

[0481] "Industry analysis" is the process of evaluating the market size, competitive landscape, and market growth potential within a specific industry.

[0482] "Industry challenges" refer to the major problems or obstacles that a particular industry faces.

[0483] "Measures taken" refers to specific solutions or countermeasures for industry challenges.

[0484] An "expert" is someone who examines the analysis results generated by generative AI models and creates the final answer.

[0485] "Electronic communication methods" refer to communication methods such as email and websites used to send final responses and analysis results to management.

[0486] This invention begins with a user entering their inquiry using a terminal. The user enters specific details, such as "I would like you to analyze the potential of a new business." Based on the inquiry received from the user, the server uses a generative AI model to collect market data. In this process, the information processing device uses specific databases or APIs (e.g., market research databases or industry report APIs) to obtain data on relevant market size and competitive landscape.

[0487] The server inputs the collected data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing techniques to propose key industry challenges and solutions. These analysis results are sent to experts, who review the findings and formulate final answers.

[0488] The final response is sent to management via electronic means by the server. This email also includes the steps taken to query the generative AI model and the analysis results. An example of a specific prompt would be: "Regarding the potential of a new business, please analyze the market size, competitive landscape, and market growth potential of the relevant industry, and propose key challenges and solutions."

[0489] In this way, users can obtain rapid and accurate industry analysis and solutions to their problems.

[0490] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0491] Step 1:

[0492] Users access the system using a terminal and enter their inquiries. These inquiries are specific in nature, such as "I would like you to analyze the potential of a new business." This input forms the basis for subsequent data collection and analysis.

[0493] Step 2:

[0494] Based on the user's inquiries, the server generates prompt statements for the AI ​​model. These prompt statements include instructions for industry analysis and problem-solving. Using the generated prompt statements, the server collects market data from specific databases and APIs. For example, it might call an industry reporting API to obtain data on market size and competitive landscape.

[0495] Step 3:

[0496] The server inputs collected market data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing technology to propose key industry challenges and solutions. Specifically, the generative AI model analyzes market data, identifies trends and competitor activities, and proposes optimal strategies.

[0497] Step 4:

[0498] The server sends the analysis results generated by the generative AI model to experts. Experts review the received analysis results, make corrections and supplements as needed, and create a final answer. Leveraging their industry expertise, experts evaluate the generative AI model's proposals and develop actionable strategies.

[0499] Step 5:

[0500] The server sends the final response, prepared by experts, to management via electronic means. This email also includes the steps taken to query the generative AI model and the analysis results. Specifically, the server sends the final response as an email, which management receives and confirms.

[0501] (Application Example 2)

[0502] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0503] In developing new businesses or product categories in the market, operators face the challenge of difficulty in quickly and accurately grasping market size, competitive landscape, growth potential, and key challenges. As a result, operators are unable to efficiently obtain the information necessary for decision-making, making it difficult to formulate appropriate market entry strategies.

[0504] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0505] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain market analysis, competitive situation, growth potential, and problem proposals; a server that examines the obtained analysis results and compiles final proposals; a server that reports to the operator the procedure for querying the generative AI and the analysis results; and a server that sends the market analysis results via email. This enables the operator to quickly and accurately obtain the information necessary for entering the market for new businesses or product categories and to make effective decisions.

[0506] "Company information" refers to basic information about a company, such as its name, address, industry, and size.

[0507] "Personal information" refers to information that identifies a specific individual, such as their name, address, and contact information.

[0508] "Contact information" refers to information used to contact an individual or company, such as a phone number or email address.

[0509] "Consultation content" refers to the specific questions or issues that the operator asks the generative AI.

[0510] "Generative AI" is an artificial intelligence technology that automatically performs analysis and makes suggestions based on input data.

[0511] "Market analysis" refers to research and analysis conducted to evaluate the size, competitive landscape, growth potential, and other aspects of a particular market.

[0512] "Competitive landscape" refers to information such as the number of competitors, market share, and strategies within a particular market.

[0513] "Growth potential" is an indicator that shows how much a particular market or business is likely to grow in the future.

[0514] "Problem proposal" involves identifying key issues in a market or business and proposing solutions to them.

[0515] "Analysis results" refer to information obtained as a result of a generative AI performing market analysis and proposing solutions.

[0516] "Operator" refers to an individual or organization responsible for managing and operating an e-commerce site or business.

[0517] "Email" is a means of communication used to send and receive messages over the internet.

[0518] The system for carrying out this invention comprises a server and a user terminal. The server plays a central role in performing market analysis using a generative AI model. The user terminal functions as an interface for the operator to input information and receive results.

[0519] The server receives company information, personal information, contact information, and consultation details from the user's terminal. This information is input into a generative AI model (e.g., GPT-4), which automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are reviewed by the server and compiled into a final proposal.

[0520] The user terminal receives analysis results from the server and displays them to the operator. Furthermore, it has a function to send analysis results via email as needed. This allows the operator to quickly and accurately obtain the information necessary for market entry into new businesses or product categories.

[0521] For example, if the operator enters the prompt message, "I want to conduct a market analysis for a new eco-friendly household goods category," the server will use a generated AI model to analyze the market size, competitive landscape, growth potential, and key challenges, and provide the results. These results will be displayed on the user's terminal to support the operator's decision-making.

[0522] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0523] Step 1:

[0524] The user uses a device to input company information, personal information, contact information, and consultation details. This information is then prepared to be sent to the AI ​​model as prompt text. The entered data is then sent to the server.

[0525] Step 2:

[0526] The server inputs the received prompt message into a generating AI model (e.g., GPT-4). Based on the input information, the generating AI model automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are returned to the server.

[0527] Step 3:

[0528] The server examines the analysis results returned by the generated AI model and compiles them into a final proposal. In this process, it verifies the accuracy and relevance of the generated information and makes adjustments as needed.

[0529] Step 4:

[0530] The server sends the final proposal to the user's terminal. The user's terminal displays the received proposal to the administrator. The administrator can then make a decision based on the displayed information.

[0531] Step 5:

[0532] If necessary, the server will send the analysis results to the administrator via email. This feature allows the administrator to view the results even when offline.

[0533] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0534] "Example of form 1"

[0535] One embodiment of the present invention provides a system that combines an emotion engine. This system receives inquiries from business owners as input and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures. Furthermore, it uses the emotion engine to analyze the business owner's emotions and generates answers that reflect the results. Specifically, if a business owner inquires about "the possibility of a new business," the generative AI analyzes the market size, competitive situation, and market growth potential of the relevant industry. At the same time, the emotion engine recognizes the business owner's emotions and adjusts the generative AI's answers based on those emotions. For example, if the business owner is feeling anxious, the emotion engine conveys this information to the generative AI, and the generative AI generates answers that correspond to the business owner's emotions, such as making the answers to the business owner more careful or detailed.

[0536] "Example of form 2"

[0537] Furthermore, in another embodiment of the present invention, a system is provided that provides the procedure and analysis results of a query to a generative AI, as well as the sentiment analysis results from an emotion engine, via email or a website. Specifically, the analysis results from the generative AI and the emotion engine are reviewed by experts, and a final response is compiled. This response is sent to the manager via email, and the procedure and analysis results of the query to the generative AI, as well as the sentiment analysis results from the emotion engine, are also reported simultaneously. This allows the manager to understand how their emotions were analyzed and how the results were reflected in the response.

[0538] The following describes the processing flow for each example of the form.

[0539] "Example of form 1"

[0540] Step 1: The system receives inquiries from management.

[0541] Step 2: Generative AI generates answers regarding industry analysis, industry challenges, and proposed solutions.

[0542] Step 3: The emotion engine analyzes the emotions of the executives.

[0543] Step 4: Based on the analysis results of the emotion engine, the generative AI generates an emotionally appropriate response.

[0544] "Example of form 2"

[0545] Step 1: Generative AI and emotion engines perform analysis, and experts review the results.

[0546] Step 2: Experts compile the final answer.

[0547] Step 3: Send an email to the business owner containing the steps taken to query the generative AI, the analysis results, and the sentiment analysis results from the sentiment engine.

[0548] (Example 1)

[0549] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0550] There is a need to provide prompt and accurate analysis and answers to the questions that small and medium-sized business owners have regarding industry challenges and new business opportunities. However, traditional methods require the assistance of experts, which is time-consuming and costly. Furthermore, there is a problem of low satisfaction because answers do not take into account the feelings of business owners.

[0551] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0552] This invention includes a server that receives company information and consultation content as input, analyzes industry information using a generation AI model to generate problems and solutions, analyzes the inputter's emotions using an emotion analysis engine to adjust the generated responses, and has experts review the obtained responses to compile a final response. This enables rapid and accurate industry analysis and the provision of responses that take into account the emotions of business managers.

[0553] "Company information" refers to basic information used to identify a specific company or individual, such as company name, personal name, and contact information.

[0554] "Consultation details" refer to information that users enter to seek advice or solutions regarding a specific problem or issue.

[0555] A "generative AI model" is a type of artificial intelligence that analyzes industry information based on input data and automatically generates problems and solutions.

[0556] "Industry information" refers to data such as market size, competitive landscape, and market growth potential for a specific industry.

[0557] An "emotion analysis engine" is a technology that analyzes user emotions from their input and adjusts responses based on the results.

[0558] An "expert" is someone who possesses advanced knowledge and experience in a specific field, and whose role is to examine the generated answers and make corrections or additions as necessary.

[0559] "Electronic communication means" refers to methods for sending and receiving information via email, websites, etc.

[0560] The embodiment for carrying out this invention is configured as follows.

[0561] Users enter company information and their inquiry details into a form on the website using their device. Specifically, they enter the company name, their name, contact information, and the details of their inquiry. For example, "I would like to discuss the possibilities of a new business."

[0562] The server receives information sent by the user and transmits it to a generative AI model. This generative AI model analyzes specific industry information and generates problems and solutions. The generative AI model is designed to process data such as market size, competitive landscape, and market growth potential.

[0563] Furthermore, the server uses an emotion analysis engine to analyze the user's emotions from their input. This emotion analysis engine determines whether the user is experiencing emotions such as anxiety or anticipation, and communicates the result to the generating AI model.

[0564] The generative AI model adjusts its responses to reflect the user's emotions based on information from the emotion analysis engine. For example, if the user is feeling anxious, the generative AI model will generate a more polite and reassuring response.

[0565] Finally, experts review the generated answers and make corrections or additions as needed. The server then sends the final, expert-verified answers to the user via electronic means, such as email. The steps taken to query the generating AI model and the analysis results are also reported simultaneously.

[0566] An example of a prompt message would be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape."

[0567] The flow of the specific processing in Example 1 will be explained using Figure 15.

[0568] Step 1:

[0569] The user uses their device to enter company information (company name, name, contact information) and their inquiry into a form on the website. A typical prompt might be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape." The device then sends this information to the server.

[0570] Step 2:

[0571] The server processes the information received from the user and sends it to the generating AI model. The server stores the entered company information and consultation details in a database and converts the data into a format that the generating AI model can analyze.

[0572] Step 3:

[0573] The generative AI model analyzes industry information based on data received from the server. Specifically, it collects data such as market size, competitive landscape, and market growth potential, and extracts information relevant to the inquiry. Using this data, the generative AI model generates an initial response to the user's inquiry.

[0574] Step 4:

[0575] The server receives the initial response from the generated AI model and sends it to the sentiment analysis engine. The sentiment analysis engine analyzes the user's input and recognizes the emotions the user is experiencing (anxiety, expectation, etc.).

[0576] Step 5:

[0577] The emotion analysis engine returns the analysis results to the generative AI model. The generative AI model takes the emotion analysis results into consideration and adjusts the response to reflect the user's emotions. For example, if the user is feeling anxious, the generative AI model will make the response more detailed and reassuring.

[0578] Step 6:

[0579] The server receives the adjusted responses from the generating AI model and sends them to experts. The experts review the generated responses and make corrections or additions as needed.

[0580] Step 7:

[0581] The server sends the final answer, verified by experts, to the user via electronic communication. Specifically, the final answer is delivered to the user via email. The procedure used to query the generative AI model and the analysis results are also reported simultaneously.

[0582] (Application Example 1)

[0583] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0584] Small and medium-sized enterprise (SME) managers often lack the specialized knowledge and resources necessary for industry analysis and strategy development. Furthermore, managers' emotions and stress can influence decision-making, requiring emotionally sensitive advice. In addition, factories need concrete improvement measures for increased production efficiency and machine maintenance, but there is a lack of efficient means to provide these.

[0585] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0586] This invention includes a server that receives company name, name, contact information, and consultation topic as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; an emotion engine that analyzes the consultant's emotions and adjusts the generative AI's answers based on those emotions; a server that analyzes the production efficiency and machine status in the factory and proposes improvement measures; and a server that adjusts the answers according to the consultant's emotions. As a result, managers can efficiently obtain expert industry analysis and solutions, and receive advice that takes their emotions into consideration. Furthermore, factories can quickly obtain specific improvement measures regarding production efficiency and machine maintenance.

[0587] A "company name" is a name used to identify a specific legal entity or organization.

[0588] "Name" refers to a name used to identify an individual.

[0589] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0590] "Consultation items" refer to the specific problems or issues that the business owner seeks to resolve.

[0591] "Generative AI" refers to artificial intelligence technology that automatically generates analyses and responses based on input information.

[0592] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0593] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0594] A "solution" is a specific action plan to solve a particular problem.

[0595] The "emotional engine" is a technique that analyzes the client's emotions and incorporates the results into other processes.

[0596] "Production efficiency" is an indicator that shows the efficiency of resource utilization in a factory or production line.

[0597] "Machine status" refers to information indicating the operating status and performance of machinery and equipment within a factory.

[0598] An "improvement plan" is a specific method for solving the current problem and achieving a better state.

[0599] The system that realizes this invention operates through the collaboration of three parties: a server, a terminal, and a user. The server receives company name, name, contact information, and consultation topic as input, and uses generative AI to generate answers regarding industry analysis, industry challenges, and proposed solutions. The generated answers are reviewed by experts, and the final answers are compiled. The server reports to the management the procedure for which it queried the generative AI and the analysis results.

[0600] Furthermore, the server uses an emotion engine to analyze the client's emotions and adjusts the generative AI's response based on those emotions. This makes it possible to provide more thoughtful and detailed answers if the business owner is feeling anxious.

[0601] The terminal analyzes production efficiency and machine status in the factory and proposes improvement measures. Utilizing generative AI and an emotion engine, the terminal provides analysis based on the manager's consultation content and emotionally responsive advice.

[0602] For example, if a factory manager consults the AI ​​saying, "I want to improve the efficiency of the production line," the generative AI will suggest specific steps to increase production efficiency. If the emotion engine detects the manager's anxiety, it will provide more detailed steps.

[0603] An example of a prompt message is, "Please suggest ways to improve production efficiency: We want to increase the efficiency of the production line."

[0604] This system utilizes generative AI through the OpenAI API and performs sentiment analysis using the EmotionEngine library. This allows managers to efficiently obtain expert industry analysis and action plans, and receive emotionally sensitive advice. Furthermore, factories can quickly obtain concrete improvement measures for increasing production efficiency and machine maintenance.

[0605] The flow of a specific process in Application Example 1 will be explained using Figure 16.

[0606] Step 1:

[0607] The user uses a device to enter the company name, name, contact information, and inquiry details. The entered data is sent to the server. The server receives this data and prepares it to be passed on to the generative AI.

[0608] Step 2:

[0609] The server generates prompts for the generative AI and, based on the input data, generates industry analysis, industry challenges, and proposed solutions. Specifically, it uses a generative AI model to analyze market trends and competitive situations related to the input consultation and proposes appropriate solutions. The generated response is provided as output.

[0610] Step 3:

[0611] The server analyzes the user's emotions using an emotion engine. The user's consultation content and past interactions are used as input. The emotion engine evaluates the user's emotional state and reflects the results in the output of the generative AI. This results in a response that is adjusted according to the user's emotions.

[0612] Step 4:

[0613] The server sends the generated responses to experts for review. The experts review the responses and make corrections or additions as needed. The final responses are compiled and sent back to the server.

[0614] Step 5:

[0615] The server reports the final response, the steps taken to query the generative AI, and the analysis results to the user. The report is delivered via email or website. This allows the user to receive expert industry analysis and actionable strategies.

[0616] Step 6:

[0617] The terminal analyzes production efficiency and machine status in a factory and proposes improvement measures. Factory operation data and machine operating status are used as input. Utilizing generative AI and an emotion engine, it provides analysis based on the manager's consultation content and emotionally responsive advice. Specific improvement measures are provided as output.

[0618] (Example 2)

[0619] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0620] In today's business environment, managers are required to conduct rapid and accurate industry analysis and develop solutions to challenges. However, extracting useful data from vast amounts of information and making appropriate decisions is not easy. Furthermore, understanding the influence of a manager's own emotions on decision-making is also important, but there is a lack of objective means to evaluate this.

[0621] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0622] This invention includes a server that receives information from users as input, analyzes industry information using a generative AI model, and automatically generates problems and their solutions; a server that has experts evaluate the generated information and create a final answer; and a server that reports to managers the procedures for querying the generative AI model, the analysis results, and the sentiment analysis results. This enables managers to obtain rapid and accurate industry analysis and problem solutions, and to objectively understand the influence of their own emotions on decision-making.

[0623] A "user" is an individual or organization that inputs information into the system and seeks industry analysis or solutions to problems.

[0624] A "generative AI model" is an artificial intelligence algorithm that analyzes industry-related data based on input information and automatically generates problems and solutions.

[0625] An "expert" is an individual or group that possesses the knowledge and experience to evaluate information generated by generative AI models and formulate a final answer.

[0626] A "manager" is an individual or organization that requires industry analysis and problem-solving, and is responsible for making final decisions.

[0627] "Sentiment analysis results" are data that objectively shows the impact of user input on their emotions and their influence on decision-making.

[0628] "Electronic communication means" refers to means of transmitting information electronically, including email and websites.

[0629] This invention is a system that provides industry analysis and problem-solving solutions using generative AI models. Specific embodiments of this system are described below.

[0630] Users access the system using a terminal and enter prompt messages. For example, they might enter a specific question such as, "Please tell me about the potential for new business ventures." These prompt messages serve as the basic data for the system to perform industry analysis.

[0631] The server uses a generative AI model to process the prompt text received from the user. Specifically, it leverages a generative AI model such as OpenAI's GPT series to collect and analyze relevant industry data based on the input prompt text. This analysis includes market size, competitive landscape, and market growth potential.

[0632] Furthermore, the server uses an emotion engine to perform sentiment analysis on user input. This allows for the evaluation of the impact of user emotions on decision-making.

[0633] The generated industry analysis and sentiment analysis results are sent from the server to experts. Based on this information, the experts create the final answers. Their knowledge and experience further refine the information provided by the generated AI model, leading to actionable suggestions.

[0634] Ultimately, the server sends the expert-compiled answers to management via electronic communication. This communication includes the steps taken when querying the generative AI model, the analysis results, and the sentiment analysis results. This allows management to quickly obtain industry analysis and problem solutions, and to understand how their own emotions influence decision-making.

[0635] The flow of the specific processing in Example 2 will be explained using Figure 17.

[0636] Program processing steps

[0637] Step 1: The user enters a prompt.

[0638] Input: The user uses a terminal to enter prompts for the generated AI model. For example, the user might enter the question, "Please tell me about the possibilities for new businesses."

[0639] Output: The prompt message is sent to the server.

[0640] Step 2: The server analyzes the data using the generated AI model.

[0641] Input: The server receives prompt messages from the user as input.

[0642] Data Processing / Calculation: The server uses a generative AI model (e.g., OpenAI's GPT series) to analyze the market size, competitive landscape, and market growth potential of the relevant industry based on the prompt text.

[0643] Output: The analysis results generate information on the industry's market size, key competitors, and growth potential.

[0644] Step 3: The server performs sentiment analysis using the sentiment engine.

[0645] Input: The server receives the user's prompt as input.

[0646] Data processing / calculation: The server uses an emotion engine to analyze the emotions contained in the prompt message.

[0647] Output: The sentiment analysis results generate data about the user's emotional state. For example, the result might be, "The user has positive feelings towards the new business."

[0648] Step 4: The server sends the analysis results to the expert.

[0649] Input: Industry analysis results from a generative AI model and sentiment analysis results from an emotion engine.

[0650] Data Processing / Calculation: The server organizes the generated data and converts it into a format that is easy for experts to evaluate.

[0651] Output: The organized analysis results are sent to the experts.

[0652] Step 5: Experts compile the final answer.

[0653] Input: Analysis results and sentiment analysis results of the generated AI model sent from the server.

[0654] Data Processing / Calculation: Experts use industry knowledge to create the final answer based on the information received.

[0655] Output: The final answer to be provided to management.

[0656] Step 6: The server sends the results to management via email.

[0657] Input: The final answer compiled by the expert, the procedure used to query the generative AI model, the analysis results, and the sentiment analysis results.

[0658] Data processing / calculation: The server compiles the final answers and analysis results into a single report.

[0659] Output: Send the final response and analysis results to management via email.

[0660] (Application Example 2)

[0661] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0662] Modern business leaders and individuals need to quickly and accurately grasp industry trends and market challenges to make appropriate decisions. However, extracting and analyzing useful data from vast amounts of information is not easy. Furthermore, in personal spending management, obtaining effective advice that takes into account purchase history and emotions presents a challenge.

[0663] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0664] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that analyzes the user's purchase history and spending patterns and proposes an optimal spending management plan and saving methods; and an emotion engine that analyzes the user's emotions and provides advice to prevent wasteful spending. As a result, managers can quickly grasp industry trends, and individuals can manage their spending while taking their emotions into consideration.

[0665] "Company information" refers to basic information about a company, such as its name, address, and contact information.

[0666] "Personal information" refers to basic information about an individual, such as their name, address, and contact information.

[0667] "Contact information" refers to information used to contact someone, such as a phone number or email address.

[0668] "Consultation content" refers to a detailed description of the problems or questions faced by business owners or individuals.

[0669] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and automatically generate information and suggestions tailored to specific purposes.

[0670] "Industry analysis" refers to the process of evaluating the market size, competitive landscape, and growth potential of a particular industry.

[0671] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0672] "Measures taken" refers to specific methods or strategies implemented to solve a particular problem.

[0673] "Purchase history" refers to a record of purchases a user has made in the past.

[0674] "Spending patterns" refer to data that shows the trends and characteristics of users' consumption behavior.

[0675] A "spending management plan" refers to a plan or proposal for effectively managing a user's spending.

[0676] An "emotion engine" refers to a system that analyzes a user's emotions and provides information based on the results.

[0677] "Wasteful spending" refers to the act of consuming resources or money in excess of what is necessary.

[0678] "Advice" refers to suggestions or proposals given regarding a specific problem.

[0679] The system for implementing this invention operates in a network environment including a server and user terminals. The server receives corporate information, personal information, contact information, and consultation content, and automatically generates industry analysis, industry challenges, and solutions using generative AI. OpenAI's GPT-3 is used as the generative AI. Experts review the analysis results obtained from the server and compile the final response.

[0680] The user terminal is a smartphone or computer, which receives the final response from the server. The user inputs their purchase history and spending patterns, and the server uses this information to suggest spending management plans and saving methods. Furthermore, it uses an emotion engine to analyze the user's emotions and provide advice to prevent wasteful spending. A general emotion analysis tool is used as the emotion engine.

[0681] For example, if a user feels that they have been spending too much money lately, the server will input the following prompt into the AI ​​model:

[0682] Example of a prompt:

[0683] Analyze the spending pattern for the following data: {"amount": 50, "category": "food"}, {"amount": 200, "category": "electronics"}. Provide insights on how to manage spending more effectively.

[0684] This prompt prompt allows the generating AI to analyze the user's spending patterns and suggest effective spending management methods. The server sends the generated suggestions to the user's terminal, allowing the user to manage their spending based on them.

[0685] The flow of a specific process in Application Example 2 will be explained using Figure 18.

[0686] Step 1:

[0687] The user inputs company information, personal information, contact information, and consultation details using a terminal. This information is sent to the server. The server stores the received information in a database and generates prompts for input into a generative AI model.

[0688] Step 2:

[0689] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates industry analysis, industry challenges, and proposed solutions based on the prompt text. The generated information is returned to the server.

[0690] Step 3:

[0691] The server presents the information returned by the generative AI model to experts, who then examine the information and formulate a final answer. The answer, after being evaluated by the experts, is stored on the server.

[0692] Step 4:

[0693] Users input their purchase history and spending patterns using a terminal. This data is sent to a server. The server analyzes the received data and generates prompts to suggest spending management plans and saving methods.

[0694] Step 5:

[0695] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates spending management plans and saving methods based on the prompt text. The generated suggestions are returned to the server.

[0696] Step 6:

[0697] The server uses an emotion engine to analyze the user's emotions. It receives user feedback as input and performs emotion analysis. The analysis results are used to generate advice to prevent wasteful spending.

[0698] Step 7:

[0699] The server sends the generated spending plan, saving methods, and sentiment analysis results to the user's terminal. The user can receive this information through their terminal and use it to help manage their spending.

[0700] (Other examples)

[0701] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[0702] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0703] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0704] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[0705] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0706] [Third Embodiment]

[0707] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0708] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0709] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0710] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0711] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0712] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0713] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0714] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0715] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0716] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0717] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0718] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0719] "Example of form 1"

[0720] In one embodiment of the system, a small business owner enters their company name, name, contact information, and inquiry into a form on a website. This information is sent to a server and received by a generative AI. Based on the entered inquiry, the generative AI generates an industry analysis, industry challenges, and proposed solutions. The generated responses are reviewed by experts, and a final response is compiled. The final response is sent to the business owner via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0721] "Example of form 2"

[0722] As a concrete example, if the consultation topic is "the possibility of a new business venture," the generative AI will analyze the market size, competitive landscape, and market growth potential of the relevant industry. It will also propose key industry challenges and solutions to those challenges. This information is reviewed by experts, and a final answer is compiled. This answer is sent to the management via email, and the procedure for contacting the generative AI and the analysis results are also reported simultaneously.

[0723] The following describes the processing flow for each example of the form.

[0724] "Example of form 1"

[0725] Step 1: Small business owners enter their company name, name, contact information, and inquiry details into a form on the website.

[0726] Step 2: The entered information is sent to the server and received by the generative AI.

[0727] Step 3: The generative AI generates industry analysis, industry challenges, and proposed solutions based on the input consultation details.

[0728] Step 4: The generated responses are reviewed by experts, and the final responses are compiled.

[0729] Step 5: The final response is sent to the management via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[0730] "Example of form 2"

[0731] Step 1: If the consultation topic is "the possibility of a new business," the generative AI analyzes the market size, competitive landscape, and market growth potential of the relevant industry.

[0732] Step 2: Generative AI also proposes key industry challenges and solutions to those challenges.

[0733] Step 3: This information is reviewed by experts, and a final answer is compiled.

[0734] Step 4: This response is sent to management via email, along with a report of the steps taken to query the generative AI and the analysis results.

[0735] (Example 1)

[0736] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0737] The process of industry analysis, information gathering for problem-solving, and proposal development faced by small and medium-sized enterprise (SME) managers is time-consuming and labor-intensive. In particular, when specialized knowledge is required, it becomes necessary to hire external experts, which incurs costs. There is a need for a way to solve these problems and obtain industry analysis and proposals quickly and efficiently.

[0738] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0739] In this invention, the server includes means for providing an interface for users to input information, means for transmitting the input information to a processing unit via a communication device, and means for the processing unit to analyze the received information and generate and transmit prompt statements to a generation AI model. This enables users to quickly obtain industry analysis and suggestions.

[0740] "Users" refers to individuals or organizations that use the system to input information and receive industry analysis and recommendations.

[0741] "Interface" refers to the means, such as screens or forms, that users are provided with to input information.

[0742] "Communication equipment" refers to network devices and software used to transmit input information to a processing unit.

[0743] A "processing unit" refers to a computer system that analyzes received information and generates and sends prompt messages to a generation AI model.

[0744] A "generative AI model" refers to an artificial intelligence algorithm or program that automatically generates data analysis and suggestions based on prompt text.

[0745] A "prompt statement" refers to a text-based sentence generated to provide specific instructions to a generative AI model.

[0746] "Expert" refers to an individual or group with the knowledge to review the generated proposals and compile the final response.

[0747] "Electronic communication means" refers to communication methods such as email and websites used to report the final answer, the procedure for querying the generated AI model, and the analysis results to the user.

[0748] The embodiment for carrying out this invention is configured as follows.

[0749] The user enters their company name, name, contact information, and inquiry details using an interface provided via a web browser. The terminal sends this input information to the server as an HTTP request. The server analyzes the received information and generates prompt messages to send to the AI ​​model based on the inquiry details. These prompt messages provide specific instructions to the AI ​​model.

[0750] For the generative AI model, for example, OpenAI's GPT model can be used. The server sends the generated prompt text to this generative AI model, which automatically generates industry analysis, industry challenges, and solutions. The generated content is sent to experts via the server, who review it, make corrections as needed, and compile the final response.

[0751] The final response is sent from the server to the user via email. This email also includes the steps taken to query the generative AI model and the analysis results. This allows users to receive industry analysis and recommendations quickly and efficiently.

[0752] For example, if a user enters a request such as "I want to think about a new marketing strategy," the server will generate a prompt message such as "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." Based on this prompt message, the AI ​​model generates relevant industry analysis and suggestions, which are then provided to the user.

[0753] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0754] Step 1:

[0755] The user accesses the interface provided via a web browser and enters the company name, personal name, contact information, and inquiry details. The entered information is packaged as an HTTP request on the user's device. This request is then prepared to be sent to the server.

[0756] Step 2:

[0757] The terminal sends an HTTP request to the server containing the information entered by the user. The server receives this request, parses the data, and extracts the company name, name, contact information, and inquiry details. This data is temporarily stored on the server and passed on to the next processing step.

[0758] Step 3:

[0759] The server generates a prompt message to send to the AI ​​model based on the received inquiry. For example, if the input inquiry is "I want to think of a new marketing strategy," the prompt message would be "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." This prompt message is then sent to the AI ​​model.

[0760] Step 4:

[0761] The server sends the generated prompt text to the AI ​​model. The AI ​​model receives the prompt text and automatically generates industry analysis, industry challenges, and proposed solutions. The AI ​​model analyzes the input prompt text, collects and analyzes relevant data, and outputs appropriate suggestions.

[0762] Step 5:

[0763] The server sends the industry analysis and suggestions received from the generated AI model to experts. The experts review this content and make revisions as needed. The final response is then returned to the server.

[0764] Step 6:

[0765] The server sends the final answer, verified by experts, to the user via email. The email also includes the steps taken to query the generative AI model and the analysis results. The user can review the received email and utilize the provided information to perform industry analysis and make recommendations.

[0766] (Application Example 1)

[0767] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0768] Retail store operators face challenges in obtaining appropriate information and advice to quickly and efficiently resolve issues related to store operations. Furthermore, they have limited means of obtaining reliable solutions that incorporate expert opinions.

[0769] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0770] This invention includes a server that receives company name, name, contact information, and consultation details as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that allows store operators to consult about store operations using a mobile device; a server that allows the generative AI to propose industry analysis and solutions to challenges related to store operations; and a server that allows experts to review the proposals and send the final answer to the operator. This enables store operators to obtain reliable solutions quickly, efficiently, and with utmost speed.

[0771] A "company name" is a name used to identify a specific legal entity or organization.

[0772] "Name" refers to a name used to identify an individual.

[0773] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0774] "Consultation items" refer to the specific problems or questions that you wish to resolve.

[0775] "Generative AI" refers to artificial intelligence systems that automatically perform analysis and make suggestions based on input information.

[0776] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0777] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0778] "Measures to address a problem" refer to specific methods or strategies for solving a particular issue.

[0779] The "final answer" is the final solution after experts have reviewed and modified the proposal from the generative AI.

[0780] "Operator" refers to an individual or legal entity responsible for the management and operation of a physical store.

[0781] A "personal digital assistant" (PDI) is a portable electronic device such as a smartphone or tablet.

[0782] An "expert" is a person who possesses advanced knowledge and experience in a particular field.

[0783] The system for implementing this invention mainly consists of a server, a personal digital assistant (PDTA), a generative AI, and the cooperation of experts. The server receives company names, names, contact information, and consultation details transmitted from the PDTA. The PDTA refers to portable electronic devices such as smartphones and tablets. The users, who are operators of physical stores, use these devices to consult about store operations.

[0784] The server sends the received information to a generative AI, which automatically generates industry analysis, industry challenges, and solutions based on the input consultation. The generative AI utilizes advanced artificial intelligence models such as OpenAI GPT-4. The AI-generated proposals are reviewed by experts and modified as needed. The final response is sent from the server to the operator via email or website.

[0785] For example, if an operator inputs "I would like to discuss how to promote a new product," the generative AI will analyze industry trends and success stories and propose a specific promotion strategy. An example of a prompt used in this case would be, "I would like to discuss how to promote a new product. Please provide suggestions based on industry trends and success stories."

[0786] This system allows brick-and-mortar store operators to obtain quick, efficient, and reliable solutions.

[0787] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0788] Step 1:

[0789] The user uses a mobile device to enter the company name, their name, contact information, and the details of their inquiry. The entered data is sent from the device to the server. Here, "input" refers to the text data entered by the user on the device, and "output" refers to the data sent to the server.

[0790] Step 2:

[0791] The server sends the received data to the generative AI. The server converts the data into an appropriate format and generates prompt statements suitable for the generative AI model. These prompt statements form the basis for the AI ​​to generate industry analysis and problem solutions. The input is the user's inquiry, and the output is the prompt statements sent to the generative AI.

[0792] Step 3:

[0793] Generative AI automatically generates industry analysis, industry challenges, and proposed solutions based on prompt messages received from a server. The AI ​​utilizes its internal database and learning models to perform analysis related to the input information. The input is the prompt message, and the output is the generated analysis results and suggestions.

[0794] Step 4:

[0795] The server receives the output from the generative AI and sends it to experts. The experts review the proposals generated by the AI ​​and make revisions as needed. The input is the proposal from the AI, and the output is the final proposal reviewed and revised by the experts.

[0796] Step 5:

[0797] The server sends the final proposal, reviewed by experts, to the user. The user receives the final proposal via email or website. The input is the proposal reviewed by experts, and the output is the final proposal sent to the user.

[0798] This series of processes allows users to obtain reliable solutions quickly, efficiently, and effectively.

[0799] (Example 2)

[0800] Next, we will describe Example 2 of the Form Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0801] In today's business environment, managers demand rapid and accurate industry analysis and solutions to challenges. However, traditional methods present challenges, such as the significant time and effort required for information gathering and analysis, making quick decision-making difficult.

[0802] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0803] This invention includes a server that receives consultation requests as input, an information processing device that collects market data using a generated AI model, and automatically generates industry analysis, industry challenges, and solutions; a means for experts to examine the generated analysis results and create a final response; and a means for transmitting the final response to management using electronic communication and reporting the procedures and analysis results of the queries made to the generated AI model. This enables the provision of rapid and accurate industry analysis and solutions to challenges.

[0804] "Consultation items" refer to the specific details that users input into the information processing device, requesting industry analysis or solutions to their problems.

[0805] An "information processing device" is a device that uses a generative AI model to collect market data and automatically generate industry analysis and solutions to problems.

[0806] A "generative AI model" is an artificial intelligence model that collects and analyzes relevant data based on the input prompt text.

[0807] "Market data" refers to data that includes information about the industry's market size, competitive landscape, and market growth potential.

[0808] "Industry analysis" is the process of evaluating the market size, competitive landscape, and market growth potential within a specific industry.

[0809] "Industry challenges" refer to the major problems or obstacles that a particular industry faces.

[0810] "Measures taken" refers to specific solutions or countermeasures for industry challenges.

[0811] An "expert" is someone who examines the analysis results generated by generative AI models and creates the final answer.

[0812] "Electronic communication methods" refer to communication methods such as email and websites used to send final responses and analysis results to management.

[0813] This invention begins with a user entering their inquiry using a terminal. The user enters specific details, such as "I would like you to analyze the potential of a new business." Based on the inquiry received from the user, the server uses a generative AI model to collect market data. In this process, the information processing device uses specific databases or APIs (e.g., market research databases or industry report APIs) to obtain data on relevant market size and competitive landscape.

[0814] The server inputs the collected data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing techniques to propose key industry challenges and solutions. These analysis results are sent to experts, who review the findings and formulate final answers.

[0815] The final response is sent to management via electronic means by the server. This email also includes the steps taken to query the generative AI model and the analysis results. An example of a specific prompt would be: "Regarding the potential of a new business, please analyze the market size, competitive landscape, and market growth potential of the relevant industry, and propose key challenges and solutions."

[0816] In this way, users can obtain rapid and accurate industry analysis and solutions to their problems.

[0817] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0818] Step 1:

[0819] Users access the system using a terminal and enter their inquiries. These inquiries are specific in nature, such as "I would like you to analyze the potential of a new business." This input forms the basis for subsequent data collection and analysis.

[0820] Step 2:

[0821] Based on the user's inquiries, the server generates prompt statements for the AI ​​model. These prompt statements include instructions for industry analysis and problem-solving. Using the generated prompt statements, the server collects market data from specific databases and APIs. For example, it might call an industry reporting API to obtain data on market size and competitive landscape.

[0822] Step 3:

[0823] The server inputs collected market data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing technology to propose key industry challenges and solutions. Specifically, the generative AI model analyzes market data, identifies trends and competitor activities, and proposes optimal strategies.

[0824] Step 4:

[0825] The server sends the analysis results generated by the generative AI model to experts. Experts review the received analysis results, make corrections and supplements as needed, and create a final answer. Leveraging their industry expertise, experts evaluate the generative AI model's proposals and develop actionable strategies.

[0826] Step 5:

[0827] The server sends the final response, prepared by experts, to management via electronic means. This email also includes the steps taken to query the generative AI model and the analysis results. Specifically, the server sends the final response as an email, which management receives and confirms.

[0828] (Application Example 2)

[0829] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0830] In developing new businesses or product categories in the market, operators face the challenge of difficulty in quickly and accurately grasping market size, competitive landscape, growth potential, and key challenges. As a result, operators are unable to efficiently obtain the information necessary for decision-making, making it difficult to formulate appropriate market entry strategies.

[0831] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0832] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain market analysis, competitive situation, growth potential, and problem proposals; a server that examines the obtained analysis results and compiles final proposals; a server that reports to the operator the procedure for querying the generative AI and the analysis results; and a server that sends the market analysis results via email. This enables the operator to quickly and accurately obtain the information necessary for entering the market for new businesses or product categories and to make effective decisions.

[0833] "Company information" refers to basic information about a company, such as its name, address, industry, and size.

[0834] "Personal information" refers to information that identifies a specific individual, such as their name, address, and contact information.

[0835] "Contact information" refers to information used to contact an individual or company, such as a phone number or email address.

[0836] "Consultation content" refers to the specific questions or issues that the operator asks the generative AI.

[0837] "Generative AI" is an artificial intelligence technology that automatically performs analysis and makes suggestions based on input data.

[0838] "Market analysis" refers to research and analysis conducted to evaluate the size, competitive landscape, growth potential, and other aspects of a particular market.

[0839] "Competitive landscape" refers to information such as the number of competitors, market share, and strategies within a particular market.

[0840] "Growth potential" is an indicator that shows how much a particular market or business is likely to grow in the future.

[0841] "Problem proposal" involves identifying key issues in a market or business and proposing solutions to them.

[0842] "Analysis results" refer to information obtained as a result of a generative AI performing market analysis and proposing solutions.

[0843] "Operator" refers to an individual or organization responsible for managing and operating an e-commerce site or business.

[0844] "Email" is a means of communication used to send and receive messages over the internet.

[0845] The system for carrying out this invention comprises a server and a user terminal. The server plays a central role in performing market analysis using a generative AI model. The user terminal functions as an interface for the operator to input information and receive results.

[0846] The server receives company information, personal information, contact information, and consultation details from the user's terminal. This information is input into a generative AI model (e.g., GPT-4), which automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are reviewed by the server and compiled into a final proposal.

[0847] The user terminal receives analysis results from the server and displays them to the operator. Furthermore, it has a function to send analysis results via email as needed. This allows the operator to quickly and accurately obtain the information necessary for market entry into new businesses or product categories.

[0848] For example, if the operator enters the prompt message, "I want to conduct a market analysis for a new eco-friendly household goods category," the server will use a generated AI model to analyze the market size, competitive landscape, growth potential, and key challenges, and provide the results. These results will be displayed on the user's terminal to support the operator's decision-making.

[0849] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0850] Step 1:

[0851] The user uses a device to input company information, personal information, contact information, and consultation details. This information is then prepared to be sent to the AI ​​model as prompt text. The entered data is then sent to the server.

[0852] Step 2:

[0853] The server inputs the received prompt message into a generating AI model (e.g., GPT-4). Based on the input information, the generating AI model automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are returned to the server.

[0854] Step 3:

[0855] The server examines the analysis results returned by the generated AI model and compiles them into a final proposal. In this process, it verifies the accuracy and relevance of the generated information and makes adjustments as needed.

[0856] Step 4:

[0857] The server sends the final proposal to the user's terminal. The user's terminal displays the received proposal to the administrator. The administrator can then make a decision based on the displayed information.

[0858] Step 5:

[0859] If necessary, the server will send the analysis results to the administrator via email. This feature allows the administrator to view the results even when offline.

[0860] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0861] "Example of form 1"

[0862] One embodiment of the present invention provides a system that combines an emotion engine. This system receives inquiries from business owners as input and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures. Furthermore, it uses the emotion engine to analyze the business owner's emotions and generates answers that reflect the results. Specifically, if a business owner inquires about "the possibility of a new business," the generative AI analyzes the market size, competitive situation, and market growth potential of the relevant industry. At the same time, the emotion engine recognizes the business owner's emotions and adjusts the generative AI's answers based on those emotions. For example, if the business owner is feeling anxious, the emotion engine conveys this information to the generative AI, and the generative AI generates answers that correspond to the business owner's emotions, such as making the answers to the business owner more careful or detailed.

[0863] "Example of form 2"

[0864] Furthermore, in another embodiment of the present invention, a system is provided that provides the procedure and analysis results of a query to a generative AI, as well as the sentiment analysis results from an emotion engine, via email or a website. Specifically, the analysis results from the generative AI and the emotion engine are reviewed by experts, and a final response is compiled. This response is sent to the manager via email, and the procedure and analysis results of the query to the generative AI, as well as the sentiment analysis results from the emotion engine, are also reported simultaneously. This allows the manager to understand how their emotions were analyzed and how the results were reflected in the response.

[0865] The following describes the processing flow for each example of the form.

[0866] "Example of form 1"

[0867] Step 1: The system receives inquiries from management.

[0868] Step 2: Generative AI generates answers regarding industry analysis, industry challenges, and proposed solutions.

[0869] Step 3: The emotion engine analyzes the emotions of the executives.

[0870] Step 4: Based on the analysis results of the emotion engine, the generative AI generates an emotionally appropriate response.

[0871] "Example of form 2"

[0872] Step 1: Generative AI and emotion engines perform analysis, and experts review the results.

[0873] Step 2: Experts compile the final answer.

[0874] Step 3: Send an email to the business owner containing the steps taken to query the generative AI, the analysis results, and the sentiment analysis results from the sentiment engine.

[0875] (Example 1)

[0876] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0877] There is a need to provide prompt and accurate analysis and answers to the questions that small and medium-sized business owners have regarding industry challenges and new business opportunities. However, traditional methods require the assistance of experts, which is time-consuming and costly. Furthermore, there is a problem of low satisfaction because answers do not take into account the feelings of business owners.

[0878] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0879] This invention includes a server that receives company information and consultation content as input, analyzes industry information using a generation AI model to generate problems and solutions, analyzes the inputter's emotions using an emotion analysis engine to adjust the generated responses, and has experts review the obtained responses to compile a final response. This enables rapid and accurate industry analysis and the provision of responses that take into account the emotions of business managers.

[0880] "Company information" refers to basic information used to identify a specific company or individual, such as company name, personal name, and contact information.

[0881] "Consultation details" refer to information that users enter to seek advice or solutions regarding a specific problem or issue.

[0882] A "generative AI model" is a type of artificial intelligence that analyzes industry information based on input data and automatically generates problems and solutions.

[0883] "Industry information" refers to data such as market size, competitive landscape, and market growth potential for a specific industry.

[0884] An "emotion analysis engine" is a technology that analyzes user emotions from their input and adjusts responses based on the results.

[0885] An "expert" is someone who possesses advanced knowledge and experience in a specific field, and whose role is to examine the generated answers and make corrections or additions as necessary.

[0886] "Electronic communication means" refers to methods for sending and receiving information via email, websites, etc.

[0887] The embodiment for carrying out this invention is configured as follows.

[0888] Users enter company information and their inquiry details into a form on the website using their device. Specifically, they enter the company name, their name, contact information, and the details of their inquiry. For example, "I would like to discuss the possibilities of a new business."

[0889] The server receives information sent by the user and transmits it to a generative AI model. This generative AI model analyzes specific industry information and generates problems and solutions. The generative AI model is designed to process data such as market size, competitive landscape, and market growth potential.

[0890] Furthermore, the server uses an emotion analysis engine to analyze the user's emotions from their input. This emotion analysis engine determines whether the user is experiencing emotions such as anxiety or anticipation, and communicates the result to the generating AI model.

[0891] The generative AI model adjusts its responses to reflect the user's emotions based on information from the emotion analysis engine. For example, if the user is feeling anxious, the generative AI model will generate a more polite and reassuring response.

[0892] Finally, experts review the generated answers and make corrections or additions as needed. The server then sends the final, expert-verified answers to the user via electronic means, such as email. The steps taken to query the generating AI model and the analysis results are also reported simultaneously.

[0893] An example of a prompt message would be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape."

[0894] The flow of the specific processing in Example 1 will be explained using Figure 15.

[0895] Step 1:

[0896] The user uses their device to enter company information (company name, name, contact information) and their inquiry into a form on the website. A typical prompt might be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape." The device then sends this information to the server.

[0897] Step 2:

[0898] The server processes the information received from the user and sends it to the generating AI model. The server stores the entered company information and consultation details in a database and converts the data into a format that the generating AI model can analyze.

[0899] Step 3:

[0900] The generative AI model analyzes industry information based on data received from the server. Specifically, it collects data such as market size, competitive landscape, and market growth potential, and extracts information relevant to the inquiry. Using this data, the generative AI model generates an initial response to the user's inquiry.

[0901] Step 4:

[0902] The server receives the initial response from the generated AI model and sends it to the sentiment analysis engine. The sentiment analysis engine analyzes the user's input and recognizes the emotions the user is experiencing (anxiety, expectation, etc.).

[0903] Step 5:

[0904] The emotion analysis engine returns the analysis results to the generative AI model. The generative AI model takes the emotion analysis results into consideration and adjusts the response to reflect the user's emotions. For example, if the user is feeling anxious, the generative AI model will make the response more detailed and reassuring.

[0905] Step 6:

[0906] The server receives the adjusted responses from the generating AI model and sends them to experts. The experts review the generated responses and make corrections or additions as needed.

[0907] Step 7:

[0908] The server sends the final answer, verified by experts, to the user via electronic communication. Specifically, the final answer is delivered to the user via email. The procedure used to query the generative AI model and the analysis results are also reported simultaneously.

[0909] (Application Example 1)

[0910] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0911] Small and medium-sized enterprise (SME) managers often lack the specialized knowledge and resources necessary for industry analysis and strategy development. Furthermore, managers' emotions and stress can influence decision-making, requiring emotionally sensitive advice. In addition, factories need concrete improvement measures for increased production efficiency and machine maintenance, but there is a lack of efficient means to provide these.

[0912] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0913] This invention includes a server that receives company name, name, contact information, and consultation topic as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; an emotion engine that analyzes the consultant's emotions and adjusts the generative AI's answers based on those emotions; a server that analyzes the production efficiency and machine status in the factory and proposes improvement measures; and a server that adjusts the answers according to the consultant's emotions. As a result, managers can efficiently obtain expert industry analysis and solutions, and receive advice that takes their emotions into consideration. Furthermore, factories can quickly obtain specific improvement measures regarding production efficiency and machine maintenance.

[0914] A "company name" is a name used to identify a specific legal entity or organization.

[0915] "Name" refers to a name used to identify an individual.

[0916] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[0917] "Consultation items" refer to the specific problems or issues that the business owner seeks to resolve.

[0918] "Generative AI" refers to artificial intelligence technology that automatically generates analyses and responses based on input information.

[0919] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[0920] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0921] A "solution" is a specific action plan to solve a particular problem.

[0922] The "emotional engine" is a technique that analyzes the client's emotions and incorporates the results into other processes.

[0923] "Production efficiency" is an indicator that shows the efficiency of resource utilization in a factory or production line.

[0924] "Machine status" refers to information indicating the operating status and performance of machinery and equipment within a factory.

[0925] An "improvement plan" is a specific method for solving the current problem and achieving a better state.

[0926] The system that realizes this invention operates through the collaboration of three parties: a server, a terminal, and a user. The server receives company name, name, contact information, and consultation topic as input, and uses generative AI to generate answers regarding industry analysis, industry challenges, and proposed solutions. The generated answers are reviewed by experts, and the final answers are compiled. The server reports to the management the procedure for which it queried the generative AI and the analysis results.

[0927] Furthermore, the server uses an emotion engine to analyze the client's emotions and adjusts the generative AI's response based on those emotions. This makes it possible to provide more thoughtful and detailed answers if the business owner is feeling anxious.

[0928] The terminal analyzes production efficiency and machine status in the factory and proposes improvement measures. Utilizing generative AI and an emotion engine, the terminal provides analysis based on the manager's consultation content and emotionally responsive advice.

[0929] For example, if a factory manager consults the AI ​​saying, "I want to improve the efficiency of the production line," the generative AI will suggest specific steps to increase production efficiency. If the emotion engine detects the manager's anxiety, it will provide more detailed steps.

[0930] An example of a prompt message is, "Please suggest ways to improve production efficiency: We want to increase the efficiency of the production line."

[0931] This system utilizes generative AI through the OpenAI API and performs sentiment analysis using the EmotionEngine library. This allows managers to efficiently obtain expert industry analysis and action plans, and receive emotionally sensitive advice. Furthermore, factories can quickly obtain concrete improvement measures for increasing production efficiency and machine maintenance.

[0932] The flow of a specific process in Application Example 1 will be explained using Figure 16.

[0933] Step 1:

[0934] The user uses a device to enter the company name, name, contact information, and inquiry details. The entered data is sent to the server. The server receives this data and prepares it to be passed on to the generative AI.

[0935] Step 2:

[0936] The server generates prompts for the generative AI and, based on the input data, generates industry analysis, industry challenges, and proposed solutions. Specifically, it uses a generative AI model to analyze market trends and competitive situations related to the input consultation and proposes appropriate solutions. The generated response is provided as output.

[0937] Step 3:

[0938] The server analyzes the user's emotions using an emotion engine. The user's consultation content and past interactions are used as input. The emotion engine evaluates the user's emotional state and reflects the results in the output of the generative AI. This results in a response that is adjusted according to the user's emotions.

[0939] Step 4:

[0940] The server sends the generated responses to experts for review. The experts review the responses and make corrections or additions as needed. The final responses are compiled and sent back to the server.

[0941] Step 5:

[0942] The server reports the final response, the steps taken to query the generative AI, and the analysis results to the user. The report is delivered via email or website. This allows the user to receive expert industry analysis and actionable strategies.

[0943] Step 6:

[0944] The terminal analyzes production efficiency and machine status in a factory and proposes improvement measures. Factory operation data and machine operating status are used as input. Utilizing generative AI and an emotion engine, it provides analysis based on the manager's consultation content and emotionally responsive advice. Specific improvement measures are provided as output.

[0945] (Example 2)

[0946] Next, we will describe Example 2 of the Form Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0947] In today's business environment, managers are required to conduct rapid and accurate industry analysis and develop solutions to challenges. However, extracting useful data from vast amounts of information and making appropriate decisions is not easy. Furthermore, understanding the influence of a manager's own emotions on decision-making is also important, but there is a lack of objective means to evaluate this.

[0948] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0949] This invention includes a server that receives information from users as input, analyzes industry information using a generative AI model, and automatically generates problems and their solutions; a server that has experts evaluate the generated information and create a final answer; and a server that reports to managers the procedures for querying the generative AI model, the analysis results, and the sentiment analysis results. This enables managers to obtain rapid and accurate industry analysis and problem solutions, and to objectively understand the influence of their own emotions on decision-making.

[0950] A "user" is an individual or organization that inputs information into the system and seeks industry analysis or solutions to problems.

[0951] A "generative AI model" is an artificial intelligence algorithm that analyzes industry-related data based on input information and automatically generates problems and solutions.

[0952] An "expert" is an individual or group that possesses the knowledge and experience to evaluate information generated by generative AI models and formulate a final answer.

[0953] A "manager" is an individual or organization that requires industry analysis and problem-solving, and is responsible for making final decisions.

[0954] "Sentiment analysis results" are data that objectively shows the impact of user input on their emotions and their influence on decision-making.

[0955] "Electronic communication means" refers to means of transmitting information electronically, including email and websites.

[0956] This invention is a system that provides industry analysis and problem-solving solutions using generative AI models. Specific embodiments of this system are described below.

[0957] Users access the system using a terminal and enter prompt messages. For example, they might enter a specific question such as, "Please tell me about the potential for new business ventures." These prompt messages serve as the basic data for the system to perform industry analysis.

[0958] The server uses a generative AI model to process the prompt text received from the user. Specifically, it leverages a generative AI model such as OpenAI's GPT series to collect and analyze relevant industry data based on the input prompt text. This analysis includes market size, competitive landscape, and market growth potential.

[0959] Furthermore, the server uses an emotion engine to perform sentiment analysis on user input. This allows for the evaluation of the impact of user emotions on decision-making.

[0960] The generated industry analysis and sentiment analysis results are sent from the server to experts. Based on this information, the experts create the final answers. Their knowledge and experience further refine the information provided by the generated AI model, leading to actionable suggestions.

[0961] Ultimately, the server sends the expert-compiled answers to management via electronic communication. This communication includes the steps taken when querying the generative AI model, the analysis results, and the sentiment analysis results. This allows management to quickly obtain industry analysis and problem solutions, and to understand how their own emotions influence decision-making.

[0962] The flow of the specific processing in Example 2 will be explained using Figure 17.

[0963] Program processing steps

[0964] Step 1: The user enters a prompt.

[0965] Input: The user uses a terminal to enter prompts for the generated AI model. For example, the user might enter the question, "Please tell me about the possibilities for new businesses."

[0966] Output: The prompt message is sent to the server.

[0967] Step 2: The server analyzes the data using the generated AI model.

[0968] Input: The server receives prompt messages from the user as input.

[0969] Data Processing / Calculation: The server uses a generative AI model (e.g., OpenAI's GPT series) to analyze the market size, competitive landscape, and market growth potential of the relevant industry based on the prompt text.

[0970] Output: The analysis results generate information on the industry's market size, key competitors, and growth potential.

[0971] Step 3: The server performs sentiment analysis using the sentiment engine.

[0972] Input: The server receives the user's prompt as input.

[0973] Data processing / calculation: The server uses an emotion engine to analyze the emotions contained in the prompt message.

[0974] Output: The sentiment analysis results generate data about the user's emotional state. For example, the result might be, "The user has positive feelings towards the new business."

[0975] Step 4: The server sends the analysis results to the expert.

[0976] Input: Industry analysis results from a generative AI model and sentiment analysis results from an emotion engine.

[0977] Data Processing / Calculation: The server organizes the generated data and converts it into a format that is easy for experts to evaluate.

[0978] Output: The organized analysis results are sent to the experts.

[0979] Step 5: Experts compile the final answer.

[0980] Input: Analysis results and sentiment analysis results of the generated AI model sent from the server.

[0981] Data Processing / Calculation: Experts use industry knowledge to create the final answer based on the information received.

[0982] Output: The final answer to be provided to management.

[0983] Step 6: The server sends the results to management via email.

[0984] Input: The final answer compiled by the expert, the procedure used to query the generative AI model, the analysis results, and the sentiment analysis results.

[0985] Data processing / calculation: The server compiles the final answers and analysis results into a single report.

[0986] Output: Send the final response and analysis results to management via email.

[0987] (Application Example 2)

[0988] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0989] Modern business leaders and individuals need to quickly and accurately grasp industry trends and market challenges to make appropriate decisions. However, extracting and analyzing useful data from vast amounts of information is not easy. Furthermore, in personal spending management, obtaining effective advice that takes into account purchase history and emotions presents a challenge.

[0990] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0991] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that analyzes the user's purchase history and spending patterns and proposes an optimal spending management plan and saving methods; and an emotion engine that analyzes the user's emotions and provides advice to prevent wasteful spending. As a result, managers can quickly grasp industry trends, and individuals can manage their spending while taking their emotions into consideration.

[0992] "Company information" refers to basic information about a company, such as its name, address, and contact information.

[0993] "Personal information" refers to basic information about an individual, such as their name, address, and contact information.

[0994] "Contact information" refers to information used to contact someone, such as a phone number or email address.

[0995] "Consultation content" refers to a detailed description of the problems or questions faced by business owners or individuals.

[0996] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and automatically generate information and suggestions tailored to specific purposes.

[0997] "Industry analysis" refers to the process of evaluating the market size, competitive landscape, and growth potential of a particular industry.

[0998] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[0999] "Measures taken" refers to specific methods or strategies implemented to solve a particular problem.

[1000] "Purchase history" refers to a record of purchases a user has made in the past.

[1001] "Spending patterns" refer to data that shows the trends and characteristics of users' consumption behavior.

[1002] A "spending management plan" refers to a plan or proposal for effectively managing a user's spending.

[1003] An "emotion engine" refers to a system that analyzes a user's emotions and provides information based on the results.

[1004] "Wasteful spending" refers to the act of consuming resources or money in excess of what is necessary.

[1005] "Advice" refers to suggestions or proposals given regarding a specific problem.

[1006] The system for implementing this invention operates in a network environment including a server and user terminals. The server receives corporate information, personal information, contact information, and consultation content, and automatically generates industry analysis, industry challenges, and solutions using generative AI. OpenAI's GPT-3 is used as the generative AI. Experts review the analysis results obtained from the server and compile the final response.

[1007] The user terminal is a smartphone or computer, which receives the final response from the server. The user inputs their purchase history and spending patterns, and the server uses this information to suggest spending management plans and saving methods. Furthermore, it uses an emotion engine to analyze the user's emotions and provide advice to prevent wasteful spending. A general emotion analysis tool is used as the emotion engine.

[1008] For example, if a user feels that they have been spending too much money lately, the server will input the following prompt into the AI ​​model:

[1009] Example of a prompt:

[1010] Analyze the spending pattern for the following data: {"amount": 50, "category": "food"}, {"amount": 200, "category": "electronics"}. Provide insights on how to manage spending more effectively.

[1011] This prompt prompt allows the generating AI to analyze the user's spending patterns and suggest effective spending management methods. The server sends the generated suggestions to the user's terminal, allowing the user to manage their spending based on them.

[1012] The flow of a specific process in Application Example 2 will be explained using Figure 18.

[1013] Step 1:

[1014] The user inputs company information, personal information, contact information, and consultation details using a terminal. This information is sent to the server. The server stores the received information in a database and generates prompts for input into a generative AI model.

[1015] Step 2:

[1016] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates industry analysis, industry challenges, and proposed solutions based on the prompt text. The generated information is returned to the server.

[1017] Step 3:

[1018] The server presents the information returned by the generative AI model to experts, who then examine the information and formulate a final answer. The answer, after being evaluated by the experts, is stored on the server.

[1019] Step 4:

[1020] Users input their purchase history and spending patterns using a terminal. This data is sent to a server. The server analyzes the received data and generates prompts to suggest spending management plans and saving methods.

[1021] Step 5:

[1022] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates spending management plans and saving methods based on the prompt text. The generated suggestions are returned to the server.

[1023] Step 6:

[1024] The server uses an emotion engine to analyze the user's emotions. It receives user feedback as input and performs emotion analysis. The analysis results are used to generate advice to prevent wasteful spending.

[1025] Step 7:

[1026] The server sends the generated spending plan, saving methods, and sentiment analysis results to the user's terminal. The user can receive this information through their terminal and use it to help manage their spending.

[1027] (Other examples)

[1028] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1029] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1030] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1031] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1032] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1033] [Fourth Embodiment]

[1034] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1035] As shown in Figure 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.

[1036] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1037] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1038] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1039] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1040] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1041] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1042] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1043] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1044] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1045] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1046] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1047] "Example of form 1"

[1048] In one embodiment of the system, a small business owner enters their company name, name, contact information, and inquiry into a form on a website. This information is sent to a server and received by a generative AI. Based on the entered inquiry, the generative AI generates an industry analysis, industry challenges, and proposed solutions. The generated responses are reviewed by experts, and a final response is compiled. The final response is sent to the business owner via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[1049] "Example of form 2"

[1050] As a concrete example, if the consultation topic is "the possibility of a new business venture," the generative AI will analyze the market size, competitive landscape, and market growth potential of the relevant industry. It will also propose key industry challenges and solutions to those challenges. This information is reviewed by experts, and a final answer is compiled. This answer is sent to the management via email, and the procedure for contacting the generative AI and the analysis results are also reported simultaneously.

[1051] The following describes the processing flow for each example of the form.

[1052] "Example of form 1"

[1053] Step 1: Small business owners enter their company name, name, contact information, and inquiry details into a form on the website.

[1054] Step 2: The entered information is sent to the server and received by the generative AI.

[1055] Step 3: The generative AI generates industry analysis, industry challenges, and proposed solutions based on the input consultation details.

[1056] Step 4: The generated responses are reviewed by experts, and the final responses are compiled.

[1057] Step 5: The final response is sent to the management via email. The steps taken to contact the generative AI and the analysis results are also reported simultaneously.

[1058] "Example of form 2"

[1059] Step 1: If the consultation topic is "the possibility of a new business," the generative AI analyzes the market size, competitive landscape, and market growth potential of the relevant industry.

[1060] Step 2: Generative AI also proposes key industry challenges and solutions to those challenges.

[1061] Step 3: This information is reviewed by experts, and a final answer is compiled.

[1062] Step 4: This response is sent to management via email, along with a report of the steps taken to query the generative AI and the analysis results.

[1063] (Example 1)

[1064] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1065] The process of industry analysis, information gathering for problem-solving, and proposal development faced by small and medium-sized enterprise (SME) managers is time-consuming and labor-intensive. In particular, when specialized knowledge is required, it becomes necessary to hire external experts, which incurs costs. There is a need for a way to solve these problems and obtain industry analysis and proposals quickly and efficiently.

[1066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1067] In this invention, the server includes means for providing an interface for users to input information, means for transmitting the input information to a processing unit via a communication device, and means for the processing unit to analyze the received information and generate and transmit prompt statements to a generation AI model. This enables users to quickly obtain industry analysis and suggestions.

[1068] "Users" refers to individuals or organizations that use the system to input information and receive industry analysis and recommendations.

[1069] "Interface" refers to the means, such as screens or forms, that users are provided with to input information.

[1070] "Communication equipment" refers to network devices and software used to transmit input information to a processing unit.

[1071] A "processing unit" refers to a computer system that analyzes received information and generates and sends prompt messages to a generation AI model.

[1072] A "generative AI model" refers to an artificial intelligence algorithm or program that automatically generates data analysis and suggestions based on prompt text.

[1073] A "prompt statement" refers to a text-based sentence generated to provide specific instructions to a generative AI model.

[1074] "Expert" refers to an individual or group with the knowledge to review the generated proposals and compile the final response.

[1075] "Electronic communication means" refers to communication methods such as email and websites used to report the final answer, the procedure for querying the generated AI model, and the analysis results to the user.

[1076] The embodiment for carrying out this invention is configured as follows.

[1077] The user enters their company name, name, contact information, and inquiry details using an interface provided via a web browser. The terminal sends this input information to the server as an HTTP request. The server analyzes the received information and generates prompt messages to send to the AI ​​model based on the inquiry details. These prompt messages provide specific instructions to the AI ​​model.

[1078] For the generative AI model, for example, OpenAI's GPT model can be used. The server sends the generated prompt text to this generative AI model, which automatically generates industry analysis, industry challenges, and solutions. The generated content is sent to experts via the server, who review it, make corrections as needed, and compile the final response.

[1079] The final response is sent from the server to the user via email. This email also includes the steps taken to query the generative AI model and the analysis results. This allows users to receive industry analysis and recommendations quickly and efficiently.

[1080] For example, if a user enters a request such as "I want to think about a new marketing strategy," the server will generate a prompt message such as "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." Based on this prompt message, the AI ​​model generates relevant industry analysis and suggestions, which are then provided to the user.

[1081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1082] Step 1:

[1083] The user accesses the interface provided via a web browser and enters the company name, personal name, contact information, and inquiry details. The entered information is packaged as an HTTP request on the user's device. This request is then prepared to be sent to the server.

[1084] Step 2:

[1085] The terminal sends an HTTP request to the server containing the information entered by the user. The server receives this request, parses the data, and extracts the company name, name, contact information, and inquiry details. This data is temporarily stored on the server and passed on to the next processing step.

[1086] Step 3:

[1087] The server generates a prompt message to send to the AI ​​model based on the received inquiry. For example, if the input inquiry is "I want to think of a new marketing strategy," the prompt message would be "Please propose new approaches based on the latest trends and competitive analysis regarding marketing strategies for small and medium-sized enterprises." This prompt message is then sent to the AI ​​model.

[1088] Step 4:

[1089] The server sends the generated prompt text to the AI ​​model. The AI ​​model receives the prompt text and automatically generates industry analysis, industry challenges, and proposed solutions. The AI ​​model analyzes the input prompt text, collects and analyzes relevant data, and outputs appropriate suggestions.

[1090] Step 5:

[1091] The server sends the industry analysis and suggestions received from the generated AI model to experts. The experts review this content and make revisions as needed. The final response is then returned to the server.

[1092] Step 6:

[1093] The server sends the final answer, verified by experts, to the user via email. The email also includes the steps taken to query the generative AI model and the analysis results. The user can review the received email and utilize the provided information to perform industry analysis and make recommendations.

[1094] (Application Example 1)

[1095] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1096] Retail store operators face challenges in obtaining appropriate information and advice to quickly and efficiently resolve issues related to store operations. Furthermore, they have limited means of obtaining reliable solutions that incorporate expert opinions.

[1097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1098] This invention includes a server that receives company name, name, contact information, and consultation details as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that allows store operators to consult about store operations using a mobile device; a server that allows the generative AI to propose industry analysis and solutions to challenges related to store operations; and a server that allows experts to review the proposals and send the final answer to the operator. This enables store operators to obtain reliable solutions quickly, efficiently, and with utmost speed.

[1099] A "company name" is a name used to identify a specific legal entity or organization.

[1100] "Name" refers to a name used to identify an individual.

[1101] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[1102] "Consultation items" refer to the specific problems or questions that you wish to resolve.

[1103] "Generative AI" refers to artificial intelligence systems that automatically perform analysis and make suggestions based on input information.

[1104] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[1105] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[1106] "Measures to address a problem" refer to specific methods or strategies for solving a particular issue.

[1107] The "final answer" is the final solution after experts have reviewed and modified the proposal from the generative AI.

[1108] "Operator" refers to an individual or legal entity responsible for the management and operation of a physical store.

[1109] A "personal digital assistant" (PDI) is a portable electronic device such as a smartphone or tablet.

[1110] An "expert" is a person who possesses advanced knowledge and experience in a particular field.

[1111] The system for implementing this invention mainly consists of a server, a personal digital assistant (PDTA), a generative AI, and the cooperation of experts. The server receives company names, names, contact information, and consultation details transmitted from the PDTA. The PDTA refers to portable electronic devices such as smartphones and tablets. The users, who are operators of physical stores, use these devices to consult about store operations.

[1112] The server sends the received information to a generative AI, which automatically generates industry analysis, industry challenges, and solutions based on the input consultation. The generative AI utilizes advanced artificial intelligence models such as OpenAI GPT-4. The AI-generated proposals are reviewed by experts and modified as needed. The final response is sent from the server to the operator via email or website.

[1113] For example, if an operator inputs "I would like to discuss how to promote a new product," the generative AI will analyze industry trends and success stories and propose a specific promotion strategy. An example of a prompt used in this case would be, "I would like to discuss how to promote a new product. Please provide suggestions based on industry trends and success stories."

[1114] This system allows brick-and-mortar store operators to obtain quick, efficient, and reliable solutions.

[1115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1116] Step 1:

[1117] The user uses a mobile device to enter the company name, their name, contact information, and the details of their inquiry. The entered data is sent from the device to the server. Here, "input" refers to the text data entered by the user on the device, and "output" refers to the data sent to the server.

[1118] Step 2:

[1119] The server sends the received data to the generative AI. The server converts the data into an appropriate format and generates prompt statements suitable for the generative AI model. These prompt statements form the basis for the AI ​​to generate industry analysis and problem solutions. The input is the user's inquiry, and the output is the prompt statements sent to the generative AI.

[1120] Step 3:

[1121] Generative AI automatically generates industry analysis, industry challenges, and proposed solutions based on prompt messages received from a server. The AI ​​utilizes its internal database and learning models to perform analysis related to the input information. The input is the prompt message, and the output is the generated analysis results and suggestions.

[1122] Step 4:

[1123] The server receives the output from the generative AI and sends it to experts. The experts review the proposals generated by the AI ​​and make revisions as needed. The input is the proposal from the AI, and the output is the final proposal reviewed and revised by the experts.

[1124] Step 5:

[1125] The server sends the final proposal, reviewed by experts, to the user. The user receives the final proposal via email or website. The input is the proposal reviewed by experts, and the output is the final proposal sent to the user.

[1126] This series of processes allows users to obtain reliable solutions quickly, efficiently, and effectively.

[1127] (Example 2)

[1128] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1129] In today's business environment, managers demand rapid and accurate industry analysis and solutions to challenges. However, traditional methods present challenges, such as the significant time and effort required for information gathering and analysis, making quick decision-making difficult.

[1130] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1131] This invention includes a server that receives consultation requests as input, an information processing device that collects market data using a generated AI model, and automatically generates industry analysis, industry challenges, and solutions; a means for experts to examine the generated analysis results and create a final response; and a means for transmitting the final response to management using electronic communication and reporting the procedures and analysis results of the queries made to the generated AI model. This enables the provision of rapid and accurate industry analysis and solutions to challenges.

[1132] "Consultation items" refer to the specific details that users input into the information processing device, requesting industry analysis or solutions to their problems.

[1133] An "information processing device" is a device that uses a generative AI model to collect market data and automatically generate industry analysis and solutions to problems.

[1134] A "generative AI model" is an artificial intelligence model that collects and analyzes relevant data based on the input prompt text.

[1135] "Market data" refers to data that includes information about the industry's market size, competitive landscape, and market growth potential.

[1136] "Industry analysis" is the process of evaluating the market size, competitive landscape, and market growth potential within a specific industry.

[1137] "Industry challenges" refer to the major problems or obstacles that a particular industry faces.

[1138] "Measures taken" refers to specific solutions or countermeasures for industry challenges.

[1139] An "expert" is someone who examines the analysis results generated by generative AI models and creates the final answer.

[1140] "Electronic communication methods" refer to communication methods such as email and websites used to send final responses and analysis results to management.

[1141] This invention begins with a user entering their inquiry using a terminal. The user enters specific details, such as "I would like you to analyze the potential of a new business." Based on the inquiry received from the user, the server uses a generative AI model to collect market data. In this process, the information processing device uses specific databases or APIs (e.g., market research databases or industry report APIs) to obtain data on relevant market size and competitive landscape.

[1142] The server inputs the collected data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing techniques to propose key industry challenges and solutions. These analysis results are sent to experts, who review the findings and formulate final answers.

[1143] The final response is sent to management via electronic means by the server. This email also includes the steps taken to query the generative AI model and the analysis results. An example of a specific prompt would be: "Regarding the potential of a new business, please analyze the market size, competitive landscape, and market growth potential of the relevant industry, and propose key challenges and solutions."

[1144] In this way, users can obtain rapid and accurate industry analysis and solutions to their problems.

[1145] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1146] Step 1:

[1147] Users access the system using a terminal and enter their inquiries. These inquiries are specific in nature, such as "I would like you to analyze the potential of a new business." This input forms the basis for subsequent data collection and analysis.

[1148] Step 2:

[1149] Based on the user's inquiries, the server generates prompt statements for the AI ​​model. These prompt statements include instructions for industry analysis and problem-solving. Using the generated prompt statements, the server collects market data from specific databases and APIs. For example, it might call an industry reporting API to obtain data on market size and competitive landscape.

[1150] Step 3:

[1151] The server inputs collected market data into a generative AI model to analyze the industry's market size, competitive landscape, and market growth potential. The generative AI model uses natural language processing technology to propose key industry challenges and solutions. Specifically, the generative AI model analyzes market data, identifies trends and competitor activities, and proposes optimal strategies.

[1152] Step 4:

[1153] The server sends the analysis results generated by the generative AI model to experts. Experts review the received analysis results, make corrections and supplements as needed, and create a final answer. Leveraging their industry expertise, experts evaluate the generative AI model's proposals and develop actionable strategies.

[1154] Step 5:

[1155] The server sends the final response, prepared by experts, to management via electronic means. This email also includes the steps taken to query the generative AI model and the analysis results. Specifically, the server sends the final response as an email, which management receives and confirms.

[1156] (Application Example 2)

[1157] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1158] In developing new businesses or product categories in the market, operators face the challenge of difficulty in quickly and accurately grasping market size, competitive landscape, growth potential, and key challenges. As a result, operators are unable to efficiently obtain the information necessary for decision-making, making it difficult to formulate appropriate market entry strategies.

[1159] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1160] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain market analysis, competitive situation, growth potential, and problem proposals; a server that examines the obtained analysis results and compiles final proposals; a server that reports to the operator the procedure for querying the generative AI and the analysis results; and a server that sends the market analysis results via email. This enables the operator to quickly and accurately obtain the information necessary for entering the market for new businesses or product categories and to make effective decisions.

[1161] "Company information" refers to basic information about a company, such as its name, address, industry, and size.

[1162] "Personal information" refers to information that identifies a specific individual, such as their name, address, and contact information.

[1163] "Contact information" refers to information used to contact an individual or company, such as a phone number or email address.

[1164] "Consultation content" refers to the specific questions or issues that the operator asks the generative AI.

[1165] "Generative AI" is an artificial intelligence technology that automatically performs analysis and makes suggestions based on input data.

[1166] "Market analysis" refers to research and analysis conducted to evaluate the size, competitive landscape, growth potential, and other aspects of a particular market.

[1167] "Competitive landscape" refers to information such as the number of competitors, market share, and strategies within a particular market.

[1168] "Growth potential" is an indicator that shows how much a particular market or business is likely to grow in the future.

[1169] "Problem proposal" involves identifying key issues in a market or business and proposing solutions to them.

[1170] "Analysis results" refer to information obtained as a result of a generative AI performing market analysis and proposing solutions.

[1171] "Operator" refers to an individual or organization responsible for managing and operating an e-commerce site or business.

[1172] "Email" is a means of communication used to send and receive messages over the internet.

[1173] The system for carrying out this invention comprises a server and a user terminal. The server plays a central role in performing market analysis using a generative AI model. The user terminal functions as an interface for the operator to input information and receive results.

[1174] The server receives company information, personal information, contact information, and consultation details from the user's terminal. This information is input into a generative AI model (e.g., GPT-4), which automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are reviewed by the server and compiled into a final proposal.

[1175] The user terminal receives analysis results from the server and displays them to the operator. Furthermore, it has a function to send analysis results via email as needed. This allows the operator to quickly and accurately obtain the information necessary for market entry into new businesses or product categories.

[1176] For example, if the operator enters the prompt message, "I want to conduct a market analysis for a new eco-friendly household goods category," the server will use a generated AI model to analyze the market size, competitive landscape, growth potential, and key challenges, and provide the results. These results will be displayed on the user's terminal to support the operator's decision-making.

[1177] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1178] Step 1:

[1179] The user uses a device to input company information, personal information, contact information, and consultation details. This information is then prepared to be sent to the AI ​​model as prompt text. The entered data is then sent to the server.

[1180] Step 2:

[1181] The server inputs the received prompt message into a generating AI model (e.g., GPT-4). Based on the input information, the generating AI model automatically generates market analysis, competitive landscape analysis, growth potential, and proposed challenges. The generated analysis results are returned to the server.

[1182] Step 3:

[1183] The server examines the analysis results returned by the generated AI model and compiles them into a final proposal. In this process, it verifies the accuracy and relevance of the generated information and makes adjustments as needed.

[1184] Step 4:

[1185] The server sends the final proposal to the user's terminal. The user's terminal displays the received proposal to the administrator. The administrator can then make a decision based on the displayed information.

[1186] Step 5:

[1187] If necessary, the server will send the analysis results to the administrator via email. This feature allows the administrator to view the results even when offline.

[1188] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1189] "Example of form 1"

[1190] One embodiment of the present invention provides a system that combines an emotion engine. This system receives inquiries from business owners as input and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures. Furthermore, it uses the emotion engine to analyze the business owner's emotions and generates answers that reflect the results. Specifically, if a business owner inquires about "the possibility of a new business," the generative AI analyzes the market size, competitive situation, and market growth potential of the relevant industry. At the same time, the emotion engine recognizes the business owner's emotions and adjusts the generative AI's answers based on those emotions. For example, if the business owner is feeling anxious, the emotion engine conveys this information to the generative AI, and the generative AI generates answers that correspond to the business owner's emotions, such as making the answers to the business owner more careful or detailed.

[1191] "Example of form 2"

[1192] Furthermore, in another embodiment of the present invention, a system is provided that provides the procedure and analysis results of a query to a generative AI, as well as the sentiment analysis results from an emotion engine, via email or a website. Specifically, the analysis results from the generative AI and the emotion engine are reviewed by experts, and a final response is compiled. This response is sent to the manager via email, and the procedure and analysis results of the query to the generative AI, as well as the sentiment analysis results from the emotion engine, are also reported simultaneously. This allows the manager to understand how their emotions were analyzed and how the results were reflected in the response.

[1193] The following describes the processing flow for each example of the form.

[1194] "Example of form 1"

[1195] Step 1: The system receives inquiries from management.

[1196] Step 2: Generative AI generates answers regarding industry analysis, industry challenges, and proposed solutions.

[1197] Step 3: The emotion engine analyzes the emotions of the executives.

[1198] Step 4: Based on the analysis results of the emotion engine, the generative AI generates an emotionally appropriate response.

[1199] "Example of form 2"

[1200] Step 1: Generative AI and emotion engines perform analysis, and experts review the results.

[1201] Step 2: Experts compile the final answer.

[1202] Step 3: Send an email to the business owner containing the steps taken to query the generative AI, the analysis results, and the sentiment analysis results from the sentiment engine.

[1203] (Example 1)

[1204] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1205] There is a need to provide prompt and accurate analysis and answers to the questions that small and medium-sized business owners have regarding industry challenges and new business opportunities. However, traditional methods require the assistance of experts, which is time-consuming and costly. Furthermore, there is a problem of low satisfaction because answers do not take into account the feelings of business owners.

[1206] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1207] This invention includes a server that receives company information and consultation content as input, analyzes industry information using a generation AI model to generate problems and solutions, analyzes the inputter's emotions using an emotion analysis engine to adjust the generated responses, and has experts review the obtained responses to compile a final response. This enables rapid and accurate industry analysis and the provision of responses that take into account the emotions of business managers.

[1208] "Company information" refers to basic information used to identify a specific company or individual, such as company name, personal name, and contact information.

[1209] "Consultation details" refer to information that users enter to seek advice or solutions regarding a specific problem or issue.

[1210] A "generative AI model" is a type of artificial intelligence that analyzes industry information based on input data and automatically generates problems and solutions.

[1211] "Industry information" refers to data such as market size, competitive landscape, and market growth potential for a specific industry.

[1212] An "emotion analysis engine" is a technology that analyzes user emotions from their input and adjusts responses based on the results.

[1213] An "expert" is someone who possesses advanced knowledge and experience in a specific field, and whose role is to examine the generated answers and make corrections or additions as necessary.

[1214] "Electronic communication means" refers to methods for sending and receiving information via email, websites, etc.

[1215] The embodiment for carrying out this invention is configured as follows.

[1216] Users enter company information and their inquiry details into a form on the website using their device. Specifically, they enter the company name, their name, contact information, and the details of their inquiry. For example, "I would like to discuss the possibilities of a new business."

[1217] The server receives information sent by the user and transmits it to a generative AI model. This generative AI model analyzes specific industry information and generates problems and solutions. The generative AI model is designed to process data such as market size, competitive landscape, and market growth potential.

[1218] Furthermore, the server uses an emotion analysis engine to analyze the user's emotions from their input. This emotion analysis engine determines whether the user is experiencing emotions such as anxiety or anticipation, and communicates the result to the generating AI model.

[1219] The generative AI model adjusts its responses to reflect the user's emotions based on information from the emotion analysis engine. For example, if the user is feeling anxious, the generative AI model will generate a more polite and reassuring response.

[1220] Finally, experts review the generated answers and make corrections or additions as needed. The server then sends the final, expert-verified answers to the user via electronic means, such as email. The steps taken to query the generating AI model and the analysis results are also reported simultaneously.

[1221] An example of a prompt message would be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape."

[1222] The flow of the specific processing in Example 1 will be explained using Figure 15.

[1223] Step 1:

[1224] The user uses their device to enter company information (company name, name, contact information) and their inquiry into a form on the website. A typical prompt might be, "I'd like to discuss the possibility of a new business venture. I'd like to know more about the market size and competitive landscape." The device then sends this information to the server.

[1225] Step 2:

[1226] The server processes the information received from the user and sends it to the generating AI model. The server stores the entered company information and consultation details in a database and converts the data into a format that the generating AI model can analyze.

[1227] Step 3:

[1228] The generative AI model analyzes industry information based on data received from the server. Specifically, it collects data such as market size, competitive landscape, and market growth potential, and extracts information relevant to the inquiry. Using this data, the generative AI model generates an initial response to the user's inquiry.

[1229] Step 4:

[1230] The server receives the initial response from the generated AI model and sends it to the sentiment analysis engine. The sentiment analysis engine analyzes the user's input and recognizes the emotions the user is experiencing (anxiety, expectation, etc.).

[1231] Step 5:

[1232] The emotion analysis engine returns the analysis results to the generative AI model. The generative AI model takes the emotion analysis results into consideration and adjusts the response to reflect the user's emotions. For example, if the user is feeling anxious, the generative AI model will make the response more detailed and reassuring.

[1233] Step 6:

[1234] The server receives the adjusted responses from the generating AI model and sends them to experts. The experts review the generated responses and make corrections or additions as needed.

[1235] Step 7:

[1236] The server sends the final answer, verified by experts, to the user via electronic communication. Specifically, the final answer is delivered to the user via email. The procedure used to query the generative AI model and the analysis results are also reported simultaneously.

[1237] (Application Example 1)

[1238] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1239] Small and medium-sized enterprise (SME) managers often lack the specialized knowledge and resources necessary for industry analysis and strategy development. Furthermore, managers' emotions and stress can influence decision-making, requiring emotionally sensitive advice. In addition, factories need concrete improvement measures for increased production efficiency and machine maintenance, but there is a lack of efficient means to provide these.

[1240] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1241] This invention includes a server that receives company name, name, contact information, and consultation topic as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and solutions; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; an emotion engine that analyzes the consultant's emotions and adjusts the generative AI's answers based on those emotions; a server that analyzes the production efficiency and machine status in the factory and proposes improvement measures; and a server that adjusts the answers according to the consultant's emotions. As a result, managers can efficiently obtain expert industry analysis and solutions, and receive advice that takes their emotions into consideration. Furthermore, factories can quickly obtain specific improvement measures regarding production efficiency and machine maintenance.

[1242] A "company name" is a name used to identify a specific legal entity or organization.

[1243] "Name" refers to a name used to identify an individual.

[1244] "Contact information" refers to information used to contact an individual or legal entity, including phone numbers and email addresses.

[1245] "Consultation items" refer to the specific problems or issues that the business owner seeks to resolve.

[1246] "Generative AI" refers to artificial intelligence technology that automatically generates analyses and responses based on input information.

[1247] "Industry analysis" is the process of evaluating market trends and competitive conditions within a specific industry.

[1248] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[1249] A "solution" is a specific action plan to solve a particular problem.

[1250] The "emotional engine" is a technique that analyzes the client's emotions and incorporates the results into other processes.

[1251] "Production efficiency" is an indicator that shows the efficiency of resource utilization in a factory or production line.

[1252] "Machine status" refers to information indicating the operating status and performance of machinery and equipment within a factory.

[1253] An "improvement plan" is a specific method for solving the current problem and achieving a better state.

[1254] The system that realizes this invention operates through the collaboration of three parties: a server, a terminal, and a user. The server receives company name, name, contact information, and consultation topic as input, and uses generative AI to generate answers regarding industry analysis, industry challenges, and proposed solutions. The generated answers are reviewed by experts, and the final answers are compiled. The server reports to the management the procedure for which it queried the generative AI and the analysis results.

[1255] Furthermore, the server uses an emotion engine to analyze the client's emotions and adjusts the generative AI's response based on those emotions. This makes it possible to provide more thoughtful and detailed answers if the business owner is feeling anxious.

[1256] The terminal analyzes production efficiency and machine status in the factory and proposes improvement measures. Utilizing generative AI and an emotion engine, the terminal provides analysis based on the manager's consultation content and emotionally responsive advice.

[1257] For example, if a factory manager consults the AI ​​saying, "I want to improve the efficiency of the production line," the generative AI will suggest specific steps to increase production efficiency. If the emotion engine detects the manager's anxiety, it will provide more detailed steps.

[1258] An example of a prompt message is, "Please suggest ways to improve production efficiency: We want to increase the efficiency of the production line."

[1259] This system utilizes generative AI through the OpenAI API and performs sentiment analysis using the EmotionEngine library. This allows managers to efficiently obtain expert industry analysis and action plans, and receive emotionally sensitive advice. Furthermore, factories can quickly obtain concrete improvement measures for increasing production efficiency and machine maintenance.

[1260] The flow of a specific process in Application Example 1 will be explained using Figure 16.

[1261] Step 1:

[1262] The user uses a device to enter the company name, name, contact information, and inquiry details. The entered data is sent to the server. The server receives this data and prepares it to be passed on to the generative AI.

[1263] Step 2:

[1264] The server generates prompts for the generative AI and, based on the input data, generates industry analysis, industry challenges, and proposed solutions. Specifically, it uses a generative AI model to analyze market trends and competitive situations related to the input consultation and proposes appropriate solutions. The generated response is provided as output.

[1265] Step 3:

[1266] The server analyzes the user's emotions using an emotion engine. The user's consultation content and past interactions are used as input. The emotion engine evaluates the user's emotional state and reflects the results in the output of the generative AI. This results in a response that is adjusted according to the user's emotions.

[1267] Step 4:

[1268] The server sends the generated responses to experts for review. The experts review the responses and make corrections or additions as needed. The final responses are compiled and sent back to the server.

[1269] Step 5:

[1270] The server reports the final response, the steps taken to query the generative AI, and the analysis results to the user. The report is delivered via email or website. This allows the user to receive expert industry analysis and actionable strategies.

[1271] Step 6:

[1272] The terminal analyzes production efficiency and machine status in a factory and proposes improvement measures. Factory operation data and machine operating status are used as input. Utilizing generative AI and an emotion engine, it provides analysis based on the manager's consultation content and emotionally responsive advice. Specific improvement measures are provided as output.

[1273] (Example 2)

[1274] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1275] In today's business environment, managers are required to conduct rapid and accurate industry analysis and develop solutions to challenges. However, extracting useful data from vast amounts of information and making appropriate decisions is not easy. Furthermore, understanding the influence of a manager's own emotions on decision-making is also important, but there is a lack of objective means to evaluate this.

[1276] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1277] This invention includes a server that receives information from users as input, analyzes industry information using a generative AI model, and automatically generates problems and their solutions; a server that has experts evaluate the generated information and create a final answer; and a server that reports to managers the procedures for querying the generative AI model, the analysis results, and the sentiment analysis results. This enables managers to obtain rapid and accurate industry analysis and problem solutions, and to objectively understand the influence of their own emotions on decision-making.

[1278] A "user" is an individual or organization that inputs information into the system and seeks industry analysis or solutions to problems.

[1279] A "generative AI model" is an artificial intelligence algorithm that analyzes industry-related data based on input information and automatically generates problems and solutions.

[1280] An "expert" is an individual or group that possesses the knowledge and experience to evaluate information generated by generative AI models and formulate a final answer.

[1281] A "manager" is an individual or organization that requires industry analysis and problem-solving, and is responsible for making final decisions.

[1282] "Sentiment analysis results" are data that objectively shows the impact of user input on their emotions and their influence on decision-making.

[1283] "Electronic communication means" refers to means of transmitting information electronically, including email and websites.

[1284] This invention is a system that provides industry analysis and problem-solving solutions using generative AI models. Specific embodiments of this system are described below.

[1285] Users access the system using a terminal and enter prompt messages. For example, they might enter a specific question such as, "Please tell me about the potential for new business ventures." These prompt messages serve as the basic data for the system to perform industry analysis.

[1286] The server uses a generative AI model to process the prompt text received from the user. Specifically, it leverages a generative AI model such as OpenAI's GPT series to collect and analyze relevant industry data based on the input prompt text. This analysis includes market size, competitive landscape, and market growth potential.

[1287] Furthermore, the server uses an emotion engine to perform sentiment analysis on user input. This allows for the evaluation of the impact of user emotions on decision-making.

[1288] The generated industry analysis and sentiment analysis results are sent from the server to experts. Based on this information, the experts create the final answers. Their knowledge and experience further refine the information provided by the generated AI model, leading to actionable suggestions.

[1289] Ultimately, the server sends the expert-compiled answers to management via electronic communication. This communication includes the steps taken when querying the generative AI model, the analysis results, and the sentiment analysis results. This allows management to quickly obtain industry analysis and problem solutions, and to understand how their own emotions influence decision-making.

[1290] The flow of the specific processing in Example 2 will be explained using Figure 17.

[1291] Program processing steps

[1292] Step 1: The user enters a prompt.

[1293] Input: The user uses a terminal to enter prompts for the generated AI model. For example, the user might enter the question, "Please tell me about the possibilities for new businesses."

[1294] Output: The prompt message is sent to the server.

[1295] Step 2: The server analyzes the data using the generated AI model.

[1296] Input: The server receives prompt messages from the user as input.

[1297] Data Processing / Calculation: The server uses a generative AI model (e.g., OpenAI's GPT series) to analyze the market size, competitive landscape, and market growth potential of the relevant industry based on the prompt text.

[1298] Output: The analysis results generate information on the industry's market size, key competitors, and growth potential.

[1299] Step 3: The server performs sentiment analysis using the sentiment engine.

[1300] Input: The server receives the user's prompt as input.

[1301] Data processing / calculation: The server uses an emotion engine to analyze the emotions contained in the prompt message.

[1302] Output: The sentiment analysis results generate data about the user's emotional state. For example, the result might be, "The user has positive feelings towards the new business."

[1303] Step 4: The server sends the analysis results to the expert.

[1304] Input: Industry analysis results from a generative AI model and sentiment analysis results from an emotion engine.

[1305] Data Processing / Calculation: The server organizes the generated data and converts it into a format that is easy for experts to evaluate.

[1306] Output: The organized analysis results are sent to the experts.

[1307] Step 5: Experts compile the final answer.

[1308] Input: Analysis results and sentiment analysis results of the generated AI model sent from the server.

[1309] Data Processing / Calculation: Experts use industry knowledge to create the final answer based on the information received.

[1310] Output: The final answer to be provided to management.

[1311] Step 6: The server sends the results to management via email.

[1312] Input: The final answer compiled by the expert, the procedure used to query the generative AI model, the analysis results, and the sentiment analysis results.

[1313] Data processing / calculation: The server compiles the final answers and analysis results into a single report.

[1314] Output: Send the final response and analysis results to management via email.

[1315] (Application Example 2)

[1316] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1317] Modern business leaders and individuals need to quickly and accurately grasp industry trends and market challenges to make appropriate decisions. However, extracting and analyzing useful data from vast amounts of information is not easy. Furthermore, in personal spending management, obtaining effective advice that takes into account purchase history and emotions presents a challenge.

[1318] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1319] This invention includes a server that receives corporate information, personal information, contact information, and consultation content as input, and uses a generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures; a server that examines the obtained answers and compiles a final answer; a server that reports to the manager the procedure for querying the generative AI and the analysis results; a server that analyzes the user's purchase history and spending patterns and proposes an optimal spending management plan and saving methods; and an emotion engine that analyzes the user's emotions and provides advice to prevent wasteful spending. As a result, managers can quickly grasp industry trends, and individuals can manage their spending while taking their emotions into consideration.

[1320] "Company information" refers to basic information about a company, such as its name, address, and contact information.

[1321] "Personal information" refers to basic information about an individual, such as their name, address, and contact information.

[1322] "Contact information" refers to information used to contact someone, such as a phone number or email address.

[1323] "Consultation content" refers to a detailed description of the problems or questions faced by business owners or individuals.

[1324] "Generative AI" refers to a system that uses artificial intelligence technology to analyze data and automatically generate information and suggestions tailored to specific purposes.

[1325] "Industry analysis" refers to the process of evaluating the market size, competitive landscape, and growth potential of a particular industry.

[1326] "Industry challenges" refer to problems or obstacles that a particular industry faces.

[1327] "Measures taken" refers to specific methods or strategies implemented to solve a particular problem.

[1328] "Purchase history" refers to a record of purchases a user has made in the past.

[1329] "Spending patterns" refer to data that shows the trends and characteristics of users' consumption behavior.

[1330] A "spending management plan" refers to a plan or proposal for effectively managing a user's spending.

[1331] An "emotion engine" refers to a system that analyzes a user's emotions and provides information based on the results.

[1332] "Wasteful spending" refers to the act of consuming resources or money in excess of what is necessary.

[1333] "Advice" refers to suggestions or proposals given regarding a specific problem.

[1334] The system for implementing this invention operates in a network environment including a server and user terminals. The server receives corporate information, personal information, contact information, and consultation content, and automatically generates industry analysis, industry challenges, and solutions using generative AI. OpenAI's GPT-3 is used as the generative AI. Experts review the analysis results obtained from the server and compile the final response.

[1335] The user terminal is a smartphone or computer, which receives the final response from the server. The user inputs their purchase history and spending patterns, and the server uses this information to suggest spending management plans and saving methods. Furthermore, it uses an emotion engine to analyze the user's emotions and provide advice to prevent wasteful spending. A general emotion analysis tool is used as the emotion engine.

[1336] For example, if a user feels that they have been spending too much money lately, the server will input the following prompt into the AI ​​model:

[1337] Example of a prompt:

[1338] Analyze the spending pattern for the following data: {"amount": 50, "category": "food"}, {"amount": 200, "category": "electronics"}. Provide insights on how to manage spending more effectively.

[1339] This prompt prompt allows the generating AI to analyze the user's spending patterns and suggest effective spending management methods. The server sends the generated suggestions to the user's terminal, allowing the user to manage their spending based on them.

[1340] The flow of a specific process in Application Example 2 will be explained using Figure 18.

[1341] Step 1:

[1342] The user inputs company information, personal information, contact information, and consultation details using a terminal. This information is sent to the server. The server stores the received information in a database and generates prompts for input into a generative AI model.

[1343] Step 2:

[1344] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates industry analysis, industry challenges, and proposed solutions based on the prompt text. The generated information is returned to the server.

[1345] Step 3:

[1346] The server presents the information returned by the generative AI model to experts, who then examine the information and formulate a final answer. The answer, after being evaluated by the experts, is stored on the server.

[1347] Step 4:

[1348] Users input their purchase history and spending patterns using a terminal. This data is sent to a server. The server analyzes the received data and generates prompts to suggest spending management plans and saving methods.

[1349] Step 5:

[1350] The server sends the generated prompt text to the generative AI model. The generative AI model automatically generates spending management plans and saving methods based on the prompt text. The generated suggestions are returned to the server.

[1351] Step 6:

[1352] The server uses an emotion engine to analyze the user's emotions. It receives user feedback as input and performs emotion analysis. The analysis results are used to generate advice to prevent wasteful spending.

[1353] Step 7:

[1354] The server sends the generated spending plan, saving methods, and sentiment analysis results to the user's terminal. The user can receive this information through their terminal and use it to help manage their spending.

[1355] (Other examples)

[1356] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1357] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1358] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1359] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1360] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1361] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1362] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1363] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1364] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1365] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1366] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1367] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1368] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[1369] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1370] 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.

[1371] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1372] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1373] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1374] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1375] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1376] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1377] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1378] The following is further disclosed regarding the embodiments described above.

[1379] (Claim 1)

[1380] This system includes a mechanism for receiving company name, name, contact information, and consultation details as input, using generative AI to obtain answers regarding industry analysis, industry challenges, and proposed solutions, a mechanism for reviewing the obtained answers and compiling a final response, and a mechanism for reporting to management the procedure for contacting the generative AI and the analysis results.

[1381] (Claim 2)

[1382] The system according to claim 1, wherein the generation AI automatically generates industry analysis, industry challenges, and countermeasures based on consultations from business managers.

[1383] (Claim 3)

[1384] The system according to claim 1, wherein the reporting means provides the procedure and analysis results of the query made to the generative AI via email or on a website.

[1385] (Claim 4)

[1386] The system according to claim 1, wherein the generation AI automatically generates industry analysis, industry challenges, and countermeasures based on consultations from business owners, and analyzes the emotions of business owners using an emotion engine that recognizes user emotions, and generates a response that reflects the results.

[1387] (Claim 5)

[1388] The system according to claim 4, wherein the emotion engine recognizes the emotions of the manager and adjusts the response of the generative AI based on those emotions.

[1389] (Claim 6)

[1390] The system according to claim 4 or 5, wherein the reporting means provides the procedure and analysis results of the query to the generative AI, and the sentiment analysis results by the sentiment engine, via email or on a website.

[1391] "Example 1"

[1392] (Claim 1)

[1393] A means of providing an interface for users to input information,

[1394] Means for transmitting input information to a processing unit via a communication device,

[1395] A means for the processing unit to analyze the received information, generate a prompt message for the generating AI model, and send it,

[1396] A means by which a generative AI model automatically generates data analysis and suggestions based on prompt sentences,

[1397] A means for experts to review the generated proposals and compile a final response,

[1398] The final response and the procedure for querying the generated AI model, along with the means of reporting the analysis results to the user,

[1399] A system that includes this.

[1400] (Claim 2)

[1401] The system according to claim 1, wherein the generating AI model automatically generates data analysis and suggestions based on input information from the user.

[1402] (Claim 3)

[1403] The system according to claim 1, wherein the reporting means provides the procedure for querying the generating AI model and the analysis results via electronic communication means.

[1404] "Application Example 1"

[1405] (Claim 1)

[1406] A method that receives company name, name, contact information, and consultation details as input, and uses generative AI to obtain answers regarding industry analysis, industry challenges, and proposed solutions.

[1407] A means of examining the responses received and compiling a final answer,

[1408] The procedure for inquiring with a generative AI and the means for reporting the analysis results to the management,

[1409] A means for store operators to consult about store operations using mobile devices,

[1410] Generative AI provides a means for proposing industry analysis and solutions to challenges related to store operations,

[1411] A means for experts to review the proposals and send the final response to the administrator,

[1412] A system that includes this.

[1413] (Claim 2)

[1414] The system according to claim 1, wherein the generation AI automatically generates industry analysis, industry challenges, and countermeasures based on inquiries from operators.

[1415] (Claim 3)

[1416] The system according to claim 1, wherein the reporting means provides the procedure and analysis results of the query made to the generative AI via email or on a website.

[1417] Example 2

[1418] (Claim 1)

[1419] A means of receiving consultation requests as input, using an information processing device to collect market data with an AI model, and automatically generating industry analysis, industry challenges, and countermeasures.

[1420] A means by which experts examine the generated analysis results and create a final answer,

[1421] The final response is sent to the management via electronic communication, and the procedure for querying the generating AI model and the analysis results are reported.

[1422] A system that includes this.

[1423] (Claim 2)

[1424] The system according to claim 1, wherein the information processing device uses a generating AI model to collect market data based on consultation matters and automatically generates industry analysis, industry challenges, and countermeasures.

[1425] (Claim 3)

[1426] The system according to claim 1, wherein the reporting means provides the procedure for querying the generating AI model and the analysis results using electronic communication means.

[1427] "Application Example 2"

[1428] (Claim 1)

[1429] A means of obtaining market analysis, competitive landscape, growth potential, and problem-solving proposals by receiving company information, personal information, contact information, and consultation details as input, and using generative AI.

[1430] A means of examining the obtained analysis results and formulating a final proposal,

[1431] The procedure for contacting the generative AI and the means for reporting the analysis results to the operator,

[1432] A means of sending market analysis results via email,

[1433] A system that includes this.

[1434] (Claim 2)

[1435] The system according to claim 1, wherein the generation AI automatically generates market analysis, competitive situation, growth potential, and proposed challenges based on the content of the consultation from the operator.

[1436] (Claim 3)

[1437] The system according to claim 1, wherein the reporting means provides the procedure and analysis results of the query made to the generative AI via email or on an online platform.

[1438] "Example 1 of combining an emotion engine"

[1439] (Claim 1)

[1440] A method for receiving company information and consultation details as input, analyzing industry information using a generation AI model, and generating problems and solutions.

[1441] A means of analyzing the emotions of the inputter using an emotion analysis engine and adjusting the generated response,

[1442] A method for experts to examine the responses received and compile a final answer,

[1443] A means of reporting to the input user the procedure for querying the generating AI model and the analysis results,

[1444] ...

[1445] A system that includes this.

[1446] (Claim 2)

[1447] The system according to claim 1, wherein the generating AI model analyzes industry information based on the content of the inquiry from the inputter and automatically generates problems and solutions.

[1448] (Claim 3)

[1449] The system according to claim 1, wherein the reporting means provides the procedure for querying the generated AI model and the analysis results via electronic communication means.

[1450] "Application example 1 of combining emotional engines"

[1451] (Claim 1)

[1452] A method that receives company name, name, contact information, and consultation details as input, and uses generative AI to obtain answers regarding industry analysis, industry challenges, and proposed solutions.

[1453] A means of examining the responses received and compiling a final answer,

[1454] The procedure for inquiring with a generative AI and the means for reporting the analysis results to the management,

[1455] A means of analyzing the client's emotions using an emotion engine and adjusting the response of a generative AI based on those emotions,

[1456] A means of analyzing production efficiency and machine condition in a factory and proposing improvement measures,

[1457] A means of adjusting the answer according to the feelings of the person seeking advice,

[1458] A system that includes this.

[1459] (Claim 2)

[1460] The system according to claim 1, wherein the generation AI automatically generates industry analysis, industry challenges, and countermeasures based on consultations from business managers.

[1461] (Claim 3)

[1462] The system according to claim 1, wherein the reporting means provides the procedure and analysis results of the query made to the generative AI via email or on a website.

[1463] "Example 2 of combining an emotion engine"

[1464] (Claim 1)

[1465] A means of receiving information from users as input, analyzing industry-related information using a generation AI model, and automatically generating problems and their solutions.

[1466] A means for experts to evaluate the generated information and create a final answer,

[1467] A means of reporting to business managers the procedure for querying the generative AI model, the analysis results, and the sentiment analysis results,

[1468] A system that includes this.

[1469] (Claim 2)

[1470] The system according to claim 1, wherein the generating AI model analyzes industry information based on user input and automatically generates problems and their solutions.

[1471] (Claim 3)

[1472] The system according to claim 1, wherein the reporting means provides the procedure for querying the generating AI model, the analysis results, and the sentiment analysis results via electronic communication means.

[1473] "Application example 2 when combining with an emotional engine"

[1474] (Claim 1)

[1475] A means of receiving company information, personal information, contact information, and consultation details as input, and using generative AI to obtain answers regarding industry analysis, industry challenges, and countermeasures.

[1476] A means of examining the responses received and compiling a final answer,

[1477] The procedure for inquiring with a generative AI and the means for reporting the analysis results to the management,

[1478] A means of analyzing users' purchase history and spending patterns to propose optimal spending management plans and saving methods,

[1479] A means of analyzing user emotions using an emotion engine and providing advice to prevent wasteful spending,

[1480] A system that includes this.

[1481] (Claim 2)

[1482] The system according to claim 1, wherein the generation AI automatically generates industry analysis, industry challenges, and countermeasures based on the content of consultations from business owners, and further analyzes the user's purchase history to propose an expenditure management plan.

[1483] (Claim 3)

[1484] The system according to claim 1, wherein the reporting means provides the procedure and analysis results of querying a generative AI via electronic communication means or a web platform, and further includes the sentiment analysis results from an emotion engine. [Explanation of Symbols]

[1485] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] Equipped with a processor, The aforementioned processor, We receive information from users, including company name, name, contact information, and details of their inquiry. Based on the consultation items included in the aforementioned information, prompt sentences are generated to cause the generating AI model to generate industry analysis, industry challenges, and countermeasures for the said industry challenges. The generated prompt sentence is sent to the generation AI model. Obtain an initial response, including the industry analysis, industry challenges, and proposed solutions, generated by the aforementioned AI model. The sentiment analysis engine analyzes the input content, including the consultation items, entered by the user, and obtains sentiment analysis results from the sentiment analysis engine indicating whether the user is experiencing feelings of anxiety or expectation based on the input content. The emotion analysis results are transmitted to the generative AI model. The AI ​​generation model generates an adjusted response by adjusting the initial response in a way that takes into account the user's emotions, taking into account the emotion analysis results. Obtain the aforementioned adjusted response, and send the obtained adjusted response to the expert. Upon receiving the final response, which has been reviewed or revised by the aforementioned expert, The final response, the inquiry procedure including the generation and transmission of the prompt text to the generation AI model, the analysis results including the industry analysis by the generation AI model, and the sentiment analysis results are sent to the user via email. system.

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