system

Abstract

Provide a system. A means for inputting investment goals and risk tolerance determined by a user; A means for linking with an artificial intelligence that generates investment advice based on the input information; means for acquiring the investment advice through competitive bidding with other users; means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder; A means for tracking the results of the investment advice and using the results to generate next advice; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional investment advice systems, users lacked the means to competitively access individual investment advice, and the system for tracking the effectiveness of that advice and using it to generate future advice was inadequate. As a result, users found it difficult to obtain the investment advice that was best suited to them, and were unable to implement effective investment strategies. In addition, the bidding process lacked transparency, preventing fair competition. [Means for solving the problem]

[0005] The present invention provides a system in which a user inputs their investment goals and risk tolerance, and artificial intelligence generates investment advice based on that information. Furthermore, the system provides a means for offering the investment advice in a bidding format, allowing users to compete fairly, and for the highest bidder to use the advice. The system also provides a means for tracking the results of the investment advice and using that data to generate the next round of advice, thereby providing continuous, highly accurate investment support. Furthermore, the use of a digital payment system improves the transparency and efficiency of the bidding and payment process.

[0006] "User" means an individual or legal entity that uses the System to receive investment advice or participate in bidding.

[0007] "Investment objectives" are specific investment objectives, such as expected return rates and investment periods, set by the user.

[0008] "Risk tolerance" is an indicator that indicates the range of risk that a user can tolerate in an investment.

[0009] "Input means" refers to an interface that allows users to register their investment goals and risk tolerance in the system.

[0010] "Artificial intelligence" is a program or system that automatically generates investment advice based on information entered by the user.

[0011] "Investment advice" refers to investment suggestions and specific instructions for portfolio optimization generated by artificial intelligence.

[0012] The "means of collaboration" is a mechanism for sending information from the user to the artificial intelligence and receiving the results.

[0013] "Competitive bidding" refers to a process in which multiple users submit prices for a certain piece of advice, and the highest bidder obtains the advice.

[0014] A "high bidder" is a user who submits the highest bid during the bidding process.

[0015] The "means for tracking and using it to generate next investment advice" is a mechanism for recording the results of investments made by the user and using that data when providing next investment advice.

[0016] "Digital payment system" means an electronic payment method through which users make bids and payments via online or mobile payments. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[0039] User Registration and Login

[0040] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0041] Collaboration with Investment Buddy AI

[0042] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0043] Generating and providing investment advice

[0044] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[0045] Launch of bidding system

[0046] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0047] Determination and notification of highest bidder

[0048] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0049] Use and implementation of investment advice

[0050] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0051] Specific examples

[0052] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0053] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] A user opens a website or application and clicks the login button with their PayPay account.

[0057] Step 2:

[0058] The terminal sends the entered user information to PayPay's authentication system.

[0059] Step 3:

[0060] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[0061] Step 4:

[0062] The terminal sends the received token to the server.

[0063] Step 5:

[0064] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[0065] Step 6:

[0066] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[0067] Step 7:

[0068] The terminal transmits the input investment profile information to the server.

[0069] Step 8:

[0070] The server generates an investment profile based on this information and sends the data to the Investment Buddy AI for collaboration.

[0071] Step 9:

[0072] Based on the investment profile received, the Investment Buddy AI generates appropriate investment advice (e.g., a portfolio of 70% stocks and 30% bonds) and returns it to the server.

[0073] Step 10:

[0074] The server stores the investment advice received from the investment buddy AI in a database.

[0075] Step 11:

[0076] The server notifies all users that new investment advice has been generated.

[0077] Step 12:

[0078] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[0079] Step 13:

[0080] The server initiates a bidding session for investment advice and sets a bidding period.

[0081] Step 14:

[0082] The user enters a bid amount for the displayed investment advice and makes a bid.

[0083] Step 15:

[0084] The terminal transmits the user's bid amount to the server.

[0085] Step 16:

[0086] The server compares it with the current maximum bid and updates the new maximum bid.

[0087] Step 17:

[0088] The server repeats this process until the bidding period ends.

[0089] Step 18:

[0090] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[0091] Step 19:

[0092] The server generates a notification to the highest bidder.

[0093] Step 20:

[0094] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[0095] Step 21:

[0096] The user reviews the investment advice they have received and decides whether to act on it.

[0097] Step 22:

[0098] The terminal provides an interface for the user to adjust the investment portfolio based on the investment advice.

[0099] Step 23:

[0100] Enter the investment actions taken by the user into the system.

[0101] Step 24:

[0102] The device sends the execution details to the server.

[0103] Step 25:

[0104] The server stores the investment data executed by the user in a database to help generate future advice.

[0105] Example 1

[0106] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0107] Conventional investment advice systems make it difficult for users to efficiently obtain and implement optimal investment advice. They also lack the ability to improve the quality of investment advice or provide individualized advice tailored to users' risk tolerance. Furthermore, they face the problem of being unable to consistently obtain investment advice competitively and track its effectiveness.

[0108] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0109] In this invention, the server includes means for inputting investment goals and risk tolerance determined by a user, means for linking with artificial intelligence that generates investment advice based on the input information, means for obtaining the investment advice through competitive bidding with other users, means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder, means for tracking the results of implementing the investment advice and using them to generate next advice, means for notifying the highest bidder, means for generating an investment profile, and means for saving the investment advice. This enables users to obtain optimal investment advice that takes into account their individual investment goals and risk tolerance through transparent and fair competition and to track its effectiveness.

[0110] "User" refers to an individual or corporation that uses the System to obtain investment advice.

[0111] "Investment goal" refers to the target investment return or asset growth that a user wishes to achieve.

[0112] "Risk tolerance" refers to the degree of risk a user is willing to accept in an investment.

[0113] "Input means" refers to an interface that allows a user to input information such as investment goals and risk tolerance.

[0114] "Artificial intelligence" refers to automated systems that use computer programs to generate investment advice based on user input data.

[0115] "Means for collaboration" refers to the means by which the server communicates with the artificial intelligence to generate investment advice.

[0116] "Means of obtaining through bidding" refers to the process by which a user obtains investment advice by making competitive bids with other users.

[0117] "Means for determining the highest bidder" refers to the means for identifying the bidder who offers the highest amount after the bidding period has ended.

[0118] "Means of providing investment advice" refers to the means of providing the generated investment advice to the highest bidder.

[0119] The "means for tracking execution results" refers to a means for recording the results of investment actions taken by a user based on investment advice, and for using the results to generate future advice.

[0120] "Means of Notification" means the method for sending notification to the highest bidder.

[0121] "Investment profile" refers to profile data generated based on information such as a user's investment goals, risk tolerance, and investment period.

[0122] "Means for storing" refers to a method for storing the generated investment advice in a storage device such as a database.

[0123] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[0124] System Configuration

[0125] The system consists of the following hardware and software components:

[0126] User terminal (terminal): A device that can connect to the Internet (such as a PC, smartphone, or tablet).

[0127] Server: A server for hosting back-end systems, including databases, application servers, and artificial intelligence models.

[0128] Investment Buddy AI (artificial intelligence): A generative AI model that generates investment advice based on input data from users.

[0129] User Registration and Login

[0130] A user opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0131] Collaboration with Investment Buddy AI

[0132] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0133] Generating and providing investment advice

[0134] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[0135] Launch of bidding system

[0136] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0137] Determination and notification of highest bidder

[0138] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0139] Use and implementation of investment advice

[0140] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0141] Specific examples

[0142] For example, a user sets an investment goal of "aiming for a 10% annual return," inputs a risk tolerance of "medium," and an investment period of "5 years." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of "70% stocks, 30% bonds." The server records this advice in a database and starts a bidding session. For example, User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0143] Prompt Sentence Examples

[0144] "Provide investment advice for those with a moderate risk tolerance, aiming for a 10% annual return."

[0145] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] A user accesses a website or application, opens the login screen, and enters their account information (username and password).

[0149] Input: Username, Password

[0150] Output: Login request

[0151] Specific operation: The user opens a login screen in a browser or application and enters their username and password in the designated form.

[0152] Step 2:

[0153] The device sends the user's login information (username and password) to the server.

[0154] Input: Username, Password

[0155] Output: HTTP POST request

[0156] Specific operation: The terminal sends the login information to the server using an HTTP POST request.

[0157] Step 3:

[0158] The server checks the login information against existing user information in the database, and if it matches, it issues a session ID as a successful authentication.

[0159] Input: Username, Password

[0160] Output: Authentication result (success / failure), session ID (if successful)

[0161] What happens: The server performs a database query to compare the login information with its records in the database, and if there is a match, generates a session ID.

[0162] Step 4:

[0163] The server returns the authentication result to the terminal, and if authentication is successful, the dashboard screen is displayed.

[0164] Input: Authentication result, session ID (if successful)

[0165] Output: Login success message, dashboard screen

[0166] Specific operation: The server returns the authentication result to the terminal as an HTTP response, and the terminal displays a login success message and the dashboard screen.

[0167] Step 5:

[0168] The user enters their investment goals, risk tolerance, and investment period.

[0169] Inputs: Investment goal, risk tolerance, investment period

[0170] Output: Investment information input request

[0171] Specific operation: The user enters information such as investment goals, risk tolerance, and investment period into a specified form.

[0172] Step 6:

[0173] The terminal transmits the user's investment information to the server.

[0174] Inputs: Investment goal, risk tolerance, investment period

[0175] Output: HTTP POST request

[0176] Specific operation: The terminal sends investment information to the server using an HTTP POST request.

[0177] Step 7:

[0178] The server generates an investment profile based on the user's investment information and sends that data to the investment buddy AI.

[0179] Inputs: Investment goal, risk tolerance, investment period

[0180] Output: Investment profile, API request

[0181] Specific operation: The server processes the investment information, creates an investment profile, and sends it to the investment buddy AI via an API request.

[0182] Step 8:

[0183] The Investment Buddy AI generates investment advice based on the investment profile received and sends the results back to the server.

[0184] Input: Investment Profile

[0185] Output: Investment advice

[0186] Specific operation: The Investment Buddy AI uses a generative AI model to analyze the investment profile, generate optimal investment advice, and send it back to the server via an API request.

[0187] Step 9:

[0188] The server stores the investment advice received from the investment buddy AI in a database and notifies the user.

[0189] Input: Investment advice

[0190] Output: Database records, advice notifications

[0191] Specific operation: The server stores the investment advice in a database and notifies all users of the advice.

[0192] Step 10:

[0193] The terminal provides an interface for displaying investment advice to the user.

[0194] Input:Advice Notice

[0195] Output: Advice display screen

[0196] Specific operation: The terminal generates and displays an HTML page for displaying the investment advice content on the user interface.

[0197] Step 11:

[0198] The server initiates a bidding session for investment advice and sets a bidding period.

[0199] Input: Investment advice

[0200] Output: Start of bidding session, bidding period setting

[0201] Specific operation: The server starts a bidding session and sends information setting the bidding period to the terminal.

[0202] Step 12:

[0203] The user enters the amount they would like to pay for the investment advice displayed and makes a bid.

[0204] Input: Bid amount

[0205] Output: Bid request

[0206] Specific operation: The user enters a bid amount and clicks the bid button.

[0207] Step 13:

[0208] The terminal transmits the user's bid amount to the server.

[0209] Input: Bid amount

[0210] Output: Send bid data

[0211] Specific operation: The terminal sends the bid data to the server using an HTTP POST request.

[0212] Step 14:

[0213] The server keeps updating the highest bids and checks the final results at the end of the bidding period.

[0214] Input: Bidding data

[0215] Output: Highest bid, final result

[0216] Specific operation: The server processes the bid data, stores it in the database, updates the highest bid, and confirms the final result at the end of the bidding period.

[0217] Step 15:

[0218] The server ultimately determines the highest bidder and records it in a database.

[0219] Input: Bid Results

[0220] Output: Highest bidder determination data

[0221] Specific Actions: The server identifies the highest bidder and records it in a database.

[0222] Step 16:

[0223] The terminal displays a notification to the highest bidder saying "Investment Advice Now Available."

[0224] Input: Highest bidder determination data

[0225] Output: Notification message

[0226] Specific operation: The terminal displays a notification to the highest bidder.

[0227] Step 17:

[0228] Review the investment advice you receive and adjust your investment portfolio accordingly.

[0229] Input: Investment advice

[0230] Output: Adjusted investment portfolio

[0231] Specific behavior: A user views investment advice and sets up a portfolio.

[0232] Step 18:

[0233] The terminal transmits the investment actions performed by the user to the server.

[0234] Input: Investment action data

[0235] Output: Investment action sending data

[0236] Specific operation: The terminal uses an HTTP POST request to send investment action data to the server.

[0237] Step 19:

[0238] The server stores the received investment action data in a database for use in later investment advice generation.

[0239] Input: Investment action submission data

[0240] Output: Database record

[0241] Specific operation: The server stores the received data in a database and uses it to generate advice next time.

[0242] (Application example 1)

[0243] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0244] In investment activities, there is a need for a means by which users can quickly and fairly obtain appropriate and effective investment advice. There is also a need for a mechanism to improve the accuracy of advice by reflecting the results of the implementation of competitively obtained advice in the generation of the next piece of advice. Furthermore, there is a need for a system that allows for real-time notifications of bidding information and investment advice, immediate implementation of the advice obtained, and feedback of the results.

[0245] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0246] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through competitive bidding with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate subsequent advice; means for notifying the user of the bidding information and advice in real time; and means for implementing the investment advice obtained by the user and providing feedback on the investment results. This allows users to quickly obtain and implement optimal investment advice under transparent and fair competition. Furthermore, by reflecting the results, the accuracy of subsequent advice can be improved.

[0247] A "user" is a person who uses the system to input investment goals and risk tolerance, competitively obtain investment advice, and then implement it.

[0248] An "investment goal" is a target value that indicates a specific outcome of an investment set by a user.

[0249] "Risk tolerance" indicates the degree of investment risk that a user can accept.

[0250] "Artificial intelligence" is a technology that generates optimal investment advice based on the investment goals and risk tolerance entered by the user.

[0251] "Bidding" is the process by which multiple users competitively offer prices to obtain investment advice.

[0252] A "high bidder" is a user who offers the highest price during the bidding process.

[0253] "Investment advice" is advice or suggestions generated by artificial intelligence to assist users in their investment activities.

[0254] "Execution results" is data showing the results and outcomes of the investment activities that the user carried out based on the investment advice.

[0255] "Real-time notification" is a function that instantly notifies users of bidding information and investment advice.

[0256] "Feedback" is a process of collecting the results of the user's investment advice and reflecting them in the next generation of advice.

[0257] MODE FOR CARRYING OUT THE INVENTION

[0258] This invention is a system that allows users to competitively obtain and implement investment advice generated based on their investment goals and risk tolerance. This system allows users to purchase investment advice through a bidding process, and provides feedback on the results of the implementation of the advice to help generate the next piece of advice.

[0259] System Program

[0260] To implement this system, the following programs are used:

[0261] Program processing and hardware / software used

[0262] 1. User Registration and Login:

[0263] Users log in to the electronic payment app and create their own investment account. Authentication is performed using Firebase Authentication, and user data is stored in the Firebase Realtime Database.

[0264] 2. Enter your investment goals and risk tolerance:

[0265] Users enter their investment goals and risk tolerance within the app, and this information is sent to a server via the electronic payment app's backend (e.g., Google® Cloud Functions).

[0266] 3. Investment advice generation:

[0267] The server receives the investment goals and risk tolerance and generates appropriate investment advice in cooperation with an artificial intelligence model (e.g., GPT-4 (registered trademark)). The generated advice is stored in a database.

[0268] 4. Operation of the bidding system:

[0269] Investment advice is provided to users in the form of a bid. The bidding process is run using the AWS (registered trademark) Lambda reference architecture, and bid information is sent in real time via Firebase Cloud Messaging. Users enter their bid amount, and the user who submits the highest bid becomes the highest bidder.

[0270] 5. Providing Investment Advice:

[0271] Once bidding closes, the highest bidder will be offered investment advice, and this notification will also be sent in real time via Firebase Cloud Messaging.

[0272] 6. Implementation and feedback of investment advice:

[0273] The highest bidder will make an investment based on the investment advice and provide feedback on the results to the app. The investment results will be sent back to the server and used to generate the next investment advice.

[0274] Specific examples

[0275] For example, User A logs into an electronic payment app, sets an investment goal of "aiming for an 8% annual return," and enters a risk tolerance of "high." The Investment Buddy AI then proposes a portfolio consisting of 80% stocks and 20% cryptocurrencies. This advice is provided in a bidding format, with User B being the highest bidder at 4,000 yen and obtaining this advice. User B then executes the investment through the electronic payment app and provides feedback on the results to the app.

[0276] Prompt Sentence Examples

[0277] "The user's investment goal is an 8% annual return, and their risk tolerance is high. Please suggest an optimal portfolio."

[0278] This system allows users to quickly obtain and implement optimal investment advice through transparent and fair competition. Furthermore, by reflecting the results, the accuracy of future advice can be improved.

[0279] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0280] Step 1: User Registration and Login

[0281] The user accesses the electronic payment app and creates an account.

[0282] Input: Username, email address, password, and other authentication information

[0283] Data processing: Validate credentials using Firebase Authentication and create user accounts

[0284] Output: Authentication token and user account information stored in Firebase Realtime Database.

[0285] What happens: When a user logs into your app, the server verifies the credentials entered and starts a session.

[0286] Step 2: Enter your investment goals and risk tolerance

[0287] Users enter their investment goals and risk tolerance into a form within the app.

[0288] Inputs: Investment goal (e.g., 8% annual return), risk tolerance (e.g., high)

[0289] Data processing: Convert the input information into JSON format and send it to the server via Google Cloud Functions

[0290] Output: Investment profile stored on the server

[0291] Specific operation: A request is sent from the terminal to the server, and the server stores the investment goals and risk tolerance in a database.

[0292] Step 3: Investment advice generation

[0293] The server then works with a generative AI model (GPT-4) based on the investment profile it receives.

[0294] Input: Investment goals and risk tolerance stored on the server

[0295] Data processing: Send prompts to the generative AI model to generate appropriate investment advice

[0296] Output: Generated investment advice saved in a database

[0297] Specific operation: The server sends the prompt statement "The user's investment goal is an 8% annual return and their risk tolerance is high. Please suggest the optimal portfolio." to the generative AI model and saves the advice obtained as a response.

[0298] Step 4: Operate the bidding system

[0299] Investment advice is provided in a bidding format, with multiple users making competitive bids.

[0300] Input: Bid amounts from multiple users

[0301] Data Processing: Bid amounts updated in real time and track the highest bids

[0302] Output: Real-time updated bidding information, highest bidder

[0303] How it works: Bid information is processed in real time using AWS Lambda, and users are notified via Firebase Cloud Messaging whenever the highest bid is updated.

[0304] Step 5: Providing investment advice

[0305] After the bidding closes, investment advice will be provided to the highest bidder.

[0306] Input: Maximum bid amount and highest bidder information

[0307] Data processing: Send notifications to the highest bidder and provide investment advice

[0308] Output: Advice given

[0309] Specific operation: The server confirms that the bidding has ended and notifies the highest bidder via Firebase Cloud Messaging to provide investment advice.

[0310] Step 6: Implementation and feedback of investment advice

[0311] The highest bidder makes an investment based on the investment advice obtained and feeds back the results to the server.

[0312] Input: Investment execution results

[0313] Data processing: Investment execution results are saved in a database and used to generate next-time advice.

[0314] Output: Feedback investment result data

[0315] Specific operation: The user makes an investment based on the investment advice, and sends the results to the server via the app. The server stores the results and uses them to generate the next investment advice.

[0316] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0317] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system uses artificial intelligence to generate investment advice based on the investment goals and risk tolerance entered by the user, and provides that advice through a bidding process. It also incorporates an emotion engine that recognizes the user's emotions, making it possible to tailor the investment advice according to the user's emotions.

[0318] User Registration and Login

[0319] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0320] Collaboration with Investment Buddy AI

[0321] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0322] Use of emotion engine

[0323] While the user is using the platform, the emotion engine recognizes the user's emotions. The emotion engine can use facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[0324] Generating and providing investment advice

[0325] The server sends the emotion data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates appropriate investment advice taking into account both the investment profile and the emotion data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[0326] Launch of bidding system

[0327] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0328] Determination and notification of highest bidder

[0329] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0330] Use and implementation of investment advice

[0331] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0332] Specific examples

[0333] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate subsequent advice.

[0334] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[0335] The processing flow will be explained below.

[0336] Step 1:

[0337] A user opens a website or application and clicks the login button with their PayPay account.

[0338] Step 2:

[0339] The terminal sends the entered user information to PayPay's authentication system.

[0340] Step 3:

[0341] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[0342] Step 4:

[0343] The terminal sends the received token to the server.

[0344] Step 5:

[0345] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[0346] Step 6:

[0347] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[0348] Step 7:

[0349] The terminal transmits this investment profile information to the server.

[0350] Step 8:

[0351] The server generates an investment profile based on the input information and sends that data to the Investment Buddy AI.

[0352] Step 9:

[0353] Based on the investment profile received, the Investment Buddy AI generates initial investment advice and returns it to the server.

[0354] Step 10:

[0355] The server stores the investment advice received from the investment buddy AI in a database.

[0356] Step 11:

[0357] The server notifies all users that new investment advice has been generated.

[0358] Step 12:

[0359] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[0360] Step 13:

[0361] The emotion engine recognizes the user's emotions by capturing the user's face through the camera and analyzing the emotions.

[0362] Step 14:

[0363] The emotion engine analyzes the text entered by the user and evaluates its emotion.

[0364] Step 15:

[0365] The terminal transmits the user's emotion data to the server.

[0366] Step 16:

[0367] The server sends the emotional data to the investment buddy AI, instructing it to adjust its investment advice.

[0368] Step 17:

[0369] The investment buddy AI takes into account the emotional data, adjusts existing investment advice or generates new advice, and returns it to the server.

[0370] Step 18:

[0371] The server stores the updated investment advice in the database and notifies all users again.

[0372] Step 19:

[0373] The server initiates a bidding session for investment advice and sets a bidding period.

[0374] Step 20:

[0375] The user inputs the amount he or she wishes to pay for the displayed investment advice and makes a bid.

[0376] Step 21:

[0377] The terminal transmits the user's bid amount to the server.

[0378] Step 22:

[0379] The server compares it with the current maximum bid and updates the new maximum bid.

[0380] Step 23:

[0381] The server repeats this process until the bidding period ends.

[0382] Step 24:

[0383] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[0384] Step 25:

[0385] The server generates a notification to the highest bidder.

[0386] Step 26:

[0387] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[0388] Step 27:

[0389] The user reviews the investment advice they have received and decides whether to act on it.

[0390] Step 28:

[0391] The terminal provides an interface for adjusting the investment portfolio based on the investment advice.

[0392] Step 29:

[0393] Enter the investment actions taken by the user into the system.

[0394] Step 30:

[0395] The device sends the execution details to the server.

[0396] Step 31:

[0397] The server stores the investment data executed by the user in a database to help generate future advice.

[0398] Example 2

[0399] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0400] Current investment advice systems generate advice mechanically, taking into account a user's individual investment goals and risk tolerance while ignoring emotional influences. This makes it difficult to provide flexible and appropriate advice that reflects the user's emotional state. It is also difficult to obtain investment advice fairly through a competitive bidding system. This leads to problems such as a decline in the quality of investment advice and a decline in user satisfaction.

[0401] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0402] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by a user; means for linking with artificial intelligence that generates investment advice based on the input information; means for collecting and recognizing emotional data of the user; means for adjusting the investment advice taking the emotional data into consideration; means for obtaining the investment advice through competitive bidding with other users; means for determining a highest bidder based on the bidding results and providing the investment advice to the highest bidder; and means for tracking the results of the investment advice and using them to generate the next piece of advice. This makes it possible to provide flexible and appropriate investment advice that reflects the user's emotional state, and to obtain and implement investment advice through a fair bidding system.

[0403] "Investment goal" refers to the specific investment results or target values ​​that the user wants to achieve.

[0404] "Risk tolerance" indicates the range or level of risk that a user can tolerate.

[0405] "Artificial intelligence" refers to the technology that enables computer systems to mimic human intelligence in problem-solving and decision-making.

[0406] "Emotion data" refers to data that indicates the user's emotional state analyzed based on facial expressions, text input, etc.

[0407] "Investment Advice" means investment recommendations or instructions generated based on a user's investment goals, risk tolerance, and sentiment data.

[0408] A "bidding system" is a system in which multiple users conduct bidding procedures to competitively obtain investment advice.

[0409] A "highest bidder" is a user who submits the highest bid in the bidding system.

[0410] A "digital payment system" is a system for making monetary payments electronically.

[0411] "Investment Data" refers to data including investment actions taken by a user and past investment history.

[0412] An "investment profile" is comprehensive investment information that integrates a user's investment goals, risk tolerance, investment period, etc.

[0413] "Bidding results" refers to the results showing the bid amounts submitted in the bidding system and the final decision on bidders based on those bid amounts.

[0414] An "investment action" is a specific investment operation or behavior that a user performs based on investment advice.

[0415] MODE FOR CARRYING OUT THE INVENTION

[0416] The present invention relates to a system that enables users to competitively obtain effective investment advice and to efficiently carry out investment activities. A specific implementation method of this system will be described below.

[0417] User Registration and Login

[0418] A user opens a website or application and first logs in with their account. The user can be authenticated using a digital payment system. The server stores the user's information in a database and starts a session if authentication is successful.

[0419] Collaboration with Investment Buddy AI

[0420] Users input their investment goals, risk tolerance, and investment period into the terminal. The terminal sends this information to the server. The server generates an investment profile based on this data and sends that data to the Investment Buddy AI. The Investment Buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0421] Use of emotion engine

[0422] While the user is using the platform, the emotion engine recognizes the user's emotions. Specifically, it uses facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[0423] Generating and providing investment advice

[0424] The server sends the emotional data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates optimal investment advice taking into account both the investment profile and the emotional data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[0425] Launch of bidding system

[0426] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process is repeated until the bidding period ends.

[0427] Determination and notification of highest bidder

[0428] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0429] Use and implementation of investment advice

[0430] The user checks the investment advice he / she has received and takes an investment action based on it. The terminal sends the investment action taken by the user to the server. The server stores this investment data in a database and uses it for future investment advice generation.

[0431] Specific examples

[0432] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this information to the server, which passes it on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen, and User B bids 2,500 yen, with User B ultimately being determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0433] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[0434] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0435] Step 1:

[0436] A user opens a website or application and registers. The user enters information such as their name, email address, and password. This information is collected as input data on the device and sent to the server. The server stores this data in a database, completing the user registration.

[0437] Step 2:

[0438] The user logs in with an existing account. The login information (email address, password) is sent from the terminal to the server. The server compares it with the information in the database and starts a session if authentication is successful. The input is the login information and the output is a session ID.

[0439] Step 3:

[0440] The user inputs their investment goal (e.g., 10% annual return), risk tolerance (e.g., medium), and investment period (e.g., 5 years) into the terminal. This information is sent from the terminal to the server. The server generates an investment profile for the user based on this data. The input is the investment goal, and the output is the investment profile.

[0441] Step 4:

[0442] The server sends the generated investment profile to the investment buddy AI. The investment buddy AI analyzes the investment profile and generates appropriate investment advice. The generated investment advice is sent back to the server. The investment profile is the input, and the investment advice is the output.

[0443] Step 5:

[0444] When a user uses the system, the device uses facial recognition technology to capture the user's facial expressions and analyze emotional data in real time. The text entered by the user is also analyzed. This emotional data is sent to the server. The input is facial recognition data and text data, and the output is emotional data.

[0445] Step 6:

[0446] The server provides the emotional data obtained from the emotion engine to the Investment Buddy AI. The Investment Buddy AI adjusts investment advice taking this emotional data into account. For example, if the user's emotion is judged to be "anxiety," advice to reduce risk is generated. The input is emotional data, and the output is adjusted investment advice.

[0447] Step 7:

[0448] The server stores the adjusted investment advice in a database and notifies all users of it. The terminal provides an interface that displays the investment advice to users. The input is the adjusted investment advice, and the output is notification information.

[0449] Step 8:

[0450] The server starts a bidding session for each investment advice. The user inputs the amount they are willing to pay, which is sent from their terminal to the server. The server compares each bid and updates the maximum bid. The input is the bid amount, and the output is the current maximum bid.

[0451] Step 9:

[0452] When the bidding period ends, the server checks the final bidding results and determines the highest bidder. The terminal displays a notification to the highest bidder saying "Investment advice is now available." The input is bidding data, and the output is the final bidding result and notification.

[0453] Step 10:

[0454] The user checks the investment advice they receive and takes an investment action based on it. The terminal sends the user's investment action to the server. The server stores this data in a database and uses it to generate future advice. The input is investment action data, and the output is updated database information.

[0455] Through the above processing steps, users can obtain flexible and appropriate investment advice based on their individual investment goals and risk tolerance, and can make investments under fair competition.

[0456] (Application example 2)

[0457] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0458] Conventional investment systems lack a competitive method for users to obtain individually optimized investment advice, and do not provide investment advice that takes into account the user's emotions. This creates a problem in that the investment advice does not reflect the user's psychological state when making investment decisions. Furthermore, there is a lack of a method for optimizing and competitively obtaining investment educational content according to individual needs.

[0459] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0460] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through a competitive bidding process with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate the next piece of advice; means for recognizing the user's emotions and adjusting the investment advice in accordance with the emotions; and means for generating optimal educational content based on the user's emotional data and investment profile and providing the right to view the educational content through a bidding process. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and competitive optimization is also introduced into the method of providing educational content.

[0461] "Investment goal" refers to the specific profit or outcome that a user aims to achieve when making an investment.

[0462] "Risk tolerance" refers to the level of risk a user can accept in an investment.

[0463] "Artificial intelligence" refers to technology and programs that perform advanced calculations and analysis based on user input data to generate appropriate investment advice.

[0464] "Bidding" refers to a system in which multiple users submit amounts that indicate their willingness to pay to obtain specific investment advice, and the person who submits the highest amount receives the advice.

[0465] "Emotion recognition" is a technology that evaluates a user's psychological state and emotions through facial recognition technology and text analysis, and acquires that data.

[0466] "Educational Content" means educational information or instructional materials designed to enhance a user's investment knowledge or experience.

[0467] "Viewing rights" refers to the right of a specific user to view specific educational content.

[0468] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which users input their investment goals, risk tolerance, investment period, etc., and artificial intelligence generates optimal investment advice based on that information and provides that advice in a bidding format. It is also possible to recognize users' emotions and adjust the investment advice accordingly. Detailed embodiments of the system are described below.

[0469] The server first provides a means for users to input their investment goals and risk tolerance. Users input this information from devices such as smartphones or PCs and send it to the server. In this case, investment goals refer to the specific profits or results that the user aims to achieve, and risk tolerance refers to the level of risk the user is willing to accept in investments.

[0470] The server works with an artificial intelligence (AI) that generates investment advice based on the information sent by the user. This AI performs advanced calculations and analysis based on the data input by the user to generate appropriate investment advice.

[0471] Furthermore, an emotion engine for emotion recognition recognizes the user's emotions while the user is using the platform. Emotion recognition is a technology that evaluates the user's mental state and emotions through facial recognition technology and text analysis, and acquires the data. For this purpose, the smartphone's camera and various sensors are used. Specific examples include OpenCV (for facial recognition), TextBlob (text emotion analysis), and EmotionRecognitionEngine (for emotion recognition).

[0472] The server sends this emotional data to the investment buddy AI, which then generates optimal investment advice by taking into account both the investment profile and the emotional data. This generated advice is stored in a database and offered to users in a competitive bidding format. In a bidding format, multiple users submit the amount they are willing to pay to obtain a particular investment advice, and the person who submits the highest amount receives the advice.

[0473] Additionally, educational content is generated based on users' emotional data and investment profiles. Educational content refers to educational information and instructional materials to improve users' investment knowledge and experience. Viewing rights are also offered through a bidding process, and users participate by entering the amount they are willing to pay.

[0474] The server determines the highest bidder based on the bidding results and notifies the user. The highest bidder can then use the investment advice and educational content they have won to help them with their actual investment activities. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and introduces competitive optimization into the method of providing educational content.

[0475] For example, consider the following prompt:

[0476] "Recommend investment education content to a user with a medium risk tolerance who aims for a 10% annual return. The user's current emotion is 'anxious.' Based on this information, generate optimized investment education content and initiate a viewing rights bidding session tailored to that content."

[0477] In this way, the system of the present invention realizes the generation and provision of investment advice and educational content based on user input data and emotional data.

[0478] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0479] Step 1:

[0480] Users input their investment goals, risk tolerance, and investment period from a device such as a smartphone or PC. The device then sends this information to the server. The input here is text data, and the output is user profile data that is passed to the server.

[0481] Step 2:

[0482] The server passes the received user profile data to an artificial intelligence (Investment Buddy AI) that generates investment advice. The Investment Buddy AI generates an investment profile for the user based on this data and generates appropriate investment advice. The input here is the user profile data, and the output is investment advice.

[0483] Step 3:

[0484] While a user is using the platform, the device's camera and sensors are used to capture the user's facial expressions and input text in real time. The device then passes the collected data to an emotion engine, which analyzes the user's emotions. The input here is image and text data, and the output is emotion data.

[0485] Step 4:

[0486] The server sends the user's emotional data and investment advice to the investment buddy AI, which then regenerates optimized investment advice that takes the user's psychological state into account. The investment buddy AI then takes the user's emotional data into account and generates advice to reduce risk, etc. The input here is the emotional data and investment advice, and the output is the adjusted investment advice.

[0487] Step 5:

[0488] The server stores the generated adjusted investment advice in a database and provides it to users in the form of a bid. Users submit bids for the presented investment advice through their terminals. The bids are made through a digital payment system, and the output is bid amount data.

[0489] Step 6:

[0490] Once the bidding period ends, the server starts the process of determining the highest bidder. The input is the bid amount data of each user, and the output is the highest bidder information. The server notifies the highest bidder of the bidding result.

[0491] Step 7:

[0492] The highest bidder confirms the investment advice and reflects it in their actual investment activities. The terminal sends the investment actions taken by the user to the server. The input here is the user's investment action data, and the output is the updated investment data.

[0493] Step 8:

[0494] The server stores the user's investment action data in a database and uses it to generate investment advice from the next time onwards. The input here is the updated investment data, and the output is the optimized data used to generate the next investment advice.

[0495] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0496] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0497] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0498] [Second embodiment]

[0499] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0500] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0501] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0502] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0503] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0504] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0505] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0506] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0507] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0508] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0509] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0510] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0511] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[0512] User Registration and Login

[0513] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0514] Collaboration with Investment Buddy AI

[0515] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0516] Generating and providing investment advice

[0517] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[0518] Launch of bidding system

[0519] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0520] Determination and notification of highest bidder

[0521] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0522] Use and implementation of investment advice

[0523] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0524] Specific examples

[0525] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0526] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[0527] The processing flow will be explained below.

[0528] Step 1:

[0529] A user opens a website or application and clicks the login button with their PayPay account.

[0530] Step 2:

[0531] The terminal sends the entered user information to PayPay's authentication system.

[0532] Step 3:

[0533] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[0534] Step 4:

[0535] The terminal sends the received token to the server.

[0536] Step 5:

[0537] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[0538] Step 6:

[0539] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[0540] Step 7:

[0541] The terminal transmits the input investment profile information to the server.

[0542] Step 8:

[0543] The server generates an investment profile based on this information and sends the data to the Investment Buddy AI for collaboration.

[0544] Step 9:

[0545] Based on the investment profile received, the Investment Buddy AI generates appropriate investment advice (e.g., a portfolio of 70% stocks and 30% bonds) and returns it to the server.

[0546] Step 10:

[0547] The server stores the investment advice received from the investment buddy AI in a database.

[0548] Step 11:

[0549] The server notifies all users that new investment advice has been generated.

[0550] Step 12:

[0551] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[0552] Step 13:

[0553] The server initiates a bidding session for investment advice and sets a bidding period.

[0554] Step 14:

[0555] The user enters a bid amount for the displayed investment advice and makes a bid.

[0556] Step 15:

[0557] The terminal transmits the user's bid amount to the server.

[0558] Step 16:

[0559] The server compares it with the current maximum bid and updates the new maximum bid.

[0560] Step 17:

[0561] The server repeats this process until the bidding period ends.

[0562] Step 18:

[0563] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[0564] Step 19:

[0565] The server generates a notification to the highest bidder.

[0566] Step 20:

[0567] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[0568] Step 21:

[0569] The user reviews the investment advice they have received and decides whether to act on it.

[0570] Step 22:

[0571] The terminal provides an interface for the user to adjust the investment portfolio based on the investment advice.

[0572] Step 23:

[0573] Enter the investment actions taken by the user into the system.

[0574] Step 24:

[0575] The device sends the execution details to the server.

[0576] Step 25:

[0577] The server stores the investment data executed by the user in a database to help generate future advice.

[0578] Example 1

[0579] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0580] Conventional investment advice systems make it difficult for users to efficiently obtain and implement optimal investment advice. They also lack the ability to improve the quality of investment advice or provide individualized advice tailored to users' risk tolerance. Furthermore, they face the problem of being unable to consistently obtain investment advice competitively and track its effectiveness.

[0581] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0582] In this invention, the server includes means for inputting investment goals and risk tolerance determined by a user, means for linking with artificial intelligence that generates investment advice based on the input information, means for obtaining the investment advice through competitive bidding with other users, means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder, means for tracking the results of implementing the investment advice and using them to generate next advice, means for notifying the highest bidder, means for generating an investment profile, and means for saving the investment advice. This enables users to obtain optimal investment advice that takes into account their individual investment goals and risk tolerance through transparent and fair competition and to track its effectiveness.

[0583] "User" refers to an individual or corporation that uses the System to obtain investment advice.

[0584] "Investment goal" refers to the target investment return or asset growth that a user wishes to achieve.

[0585] "Risk tolerance" refers to the degree of risk a user is willing to accept in an investment.

[0586] "Input means" refers to an interface that allows a user to input information such as investment goals and risk tolerance.

[0587] "Artificial intelligence" refers to automated systems that use computer programs to generate investment advice based on user input data.

[0588] "Means for collaboration" refers to the means by which the server communicates with the artificial intelligence to generate investment advice.

[0589] "Means of obtaining through bidding" refers to the process by which a user obtains investment advice by making competitive bids with other users.

[0590] "Means for determining the highest bidder" refers to the means for identifying the bidder who offers the highest amount after the bidding period has ended.

[0591] "Means of providing investment advice" refers to the means of providing the generated investment advice to the highest bidder.

[0592] The "means for tracking execution results" refers to a means for recording the results of investment actions taken by a user based on investment advice, and for using the results to generate future advice.

[0593] "Means of Notification" means the method for sending notification to the highest bidder.

[0594] "Investment profile" refers to profile data generated based on information such as a user's investment goals, risk tolerance, and investment period.

[0595] "Means for storing" refers to a method for storing the generated investment advice in a storage device such as a database.

[0596] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[0597] System Configuration

[0598] The system consists of the following hardware and software components:

[0599] User terminal (terminal): A device that can connect to the Internet (such as a PC, smartphone, or tablet).

[0600] Server: A server for hosting back-end systems, including databases, application servers, and artificial intelligence models.

[0601] Investment Buddy AI (artificial intelligence): A generative AI model that generates investment advice based on input data from users.

[0602] User Registration and Login

[0603] A user opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0604] Collaboration with Investment Buddy AI

[0605] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0606] Generating and providing investment advice

[0607] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[0608] Launch of bidding system

[0609] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0610] Determination and notification of highest bidder

[0611] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0612] Use and implementation of investment advice

[0613] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0614] Specific examples

[0615] For example, a user sets an investment goal of "aiming for a 10% annual return," inputs a risk tolerance of "medium," and an investment period of "5 years." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of "70% stocks, 30% bonds." The server records this advice in a database and starts a bidding session. For example, User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0616] Prompt Sentence Examples

[0617] "Provide investment advice for those with a moderate risk tolerance, aiming for a 10% annual return."

[0618] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[0619] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0620] Step 1:

[0621] A user accesses a website or application, opens the login screen, and enters their account information (username and password).

[0622] Input: Username, Password

[0623] Output: Login request

[0624] Specific operation: The user opens a login screen in a browser or application and enters their username and password in the designated form.

[0625] Step 2:

[0626] The device sends the user's login information (username and password) to the server.

[0627] Input: Username, Password

[0628] Output: HTTP POST request

[0629] Specific operation: The terminal sends the login information to the server using an HTTP POST request.

[0630] Step 3:

[0631] The server checks the login information against existing user information in the database, and if it matches, it issues a session ID as a successful authentication.

[0632] Input: Username, Password

[0633] Output: Authentication result (success / failure), session ID (if successful)

[0634] What happens: The server performs a database query to compare the login information with its records in the database, and if there is a match, generates a session ID.

[0635] Step 4:

[0636] The server returns the authentication result to the terminal, and if authentication is successful, the dashboard screen is displayed.

[0637] Input: Authentication result, session ID (if successful)

[0638] Output: Login success message, dashboard screen

[0639] Specific operation: The server returns the authentication result to the terminal as an HTTP response, and the terminal displays a login success message and the dashboard screen.

[0640] Step 5:

[0641] The user enters their investment goals, risk tolerance, and investment period.

[0642] Inputs: Investment goal, risk tolerance, investment period

[0643] Output: Investment information input request

[0644] Specific operation: The user enters information such as investment goals, risk tolerance, and investment period into a specified form.

[0645] Step 6:

[0646] The terminal transmits the user's investment information to the server.

[0647] Inputs: Investment goal, risk tolerance, investment period

[0648] Output: HTTP POST request

[0649] Specific operation: The terminal sends investment information to the server using an HTTP POST request.

[0650] Step 7:

[0651] The server generates an investment profile based on the user's investment information and sends that data to the investment buddy AI.

[0652] Inputs: Investment goal, risk tolerance, investment period

[0653] Output: Investment profile, API request

[0654] Specific operation: The server processes the investment information, creates an investment profile, and sends it to the investment buddy AI via an API request.

[0655] Step 8:

[0656] The Investment Buddy AI generates investment advice based on the investment profile received and sends the results back to the server.

[0657] Input: Investment Profile

[0658] Output: Investment advice

[0659] Specific operation: The Investment Buddy AI uses a generative AI model to analyze the investment profile, generate optimal investment advice, and send it back to the server via an API request.

[0660] Step 9:

[0661] The server stores the investment advice received from the investment buddy AI in a database and notifies the user.

[0662] Input: Investment advice

[0663] Output: Database records, advice notifications

[0664] Specific operation: The server stores the investment advice in a database and notifies all users of the advice.

[0665] Step 10:

[0666] The terminal provides an interface for displaying investment advice to the user.

[0667] Input:Advice Notice

[0668] Output: Advice display screen

[0669] Specific operation: The terminal generates and displays an HTML page for displaying the investment advice content on the user interface.

[0670] Step 11:

[0671] The server initiates a bidding session for investment advice and sets a bidding period.

[0672] Input: Investment advice

[0673] Output: Start of bidding session, bidding period setting

[0674] Specific operation: The server starts a bidding session and sends information setting the bidding period to the terminal.

[0675] Step 12:

[0676] The user enters the amount they would like to pay for the investment advice displayed and makes a bid.

[0677] Input: Bid amount

[0678] Output: Bid request

[0679] Specific operation: The user enters a bid amount and clicks the bid button.

[0680] Step 13:

[0681] The terminal transmits the user's bid amount to the server.

[0682] Input: Bid amount

[0683] Output: Send bid data

[0684] Specific operation: The terminal sends the bid data to the server using an HTTP POST request.

[0685] Step 14:

[0686] The server keeps updating the highest bids and checks the final results at the end of the bidding period.

[0687] Input: Bidding data

[0688] Output: Highest bid, final result

[0689] Specific operation: The server processes the bid data, stores it in the database, updates the highest bid, and confirms the final result at the end of the bidding period.

[0690] Step 15:

[0691] The server ultimately determines the highest bidder and records it in a database.

[0692] Input: Bid Results

[0693] Output: Highest bidder determination data

[0694] Specific Actions: The server identifies the highest bidder and records it in a database.

[0695] Step 16:

[0696] The terminal displays a notification to the highest bidder saying "Investment Advice Now Available."

[0697] Input: Highest bidder determination data

[0698] Output: Notification message

[0699] Specific operation: The terminal displays a notification to the highest bidder.

[0700] Step 17:

[0701] Review the investment advice you receive and adjust your investment portfolio accordingly.

[0702] Input: Investment advice

[0703] Output: Adjusted investment portfolio

[0704] Specific behavior: A user views investment advice and sets up a portfolio.

[0705] Step 18:

[0706] The terminal transmits the investment actions performed by the user to the server.

[0707] Input: Investment action data

[0708] Output: Investment action sending data

[0709] Specific operation: The terminal uses an HTTP POST request to send investment action data to the server.

[0710] Step 19:

[0711] The server stores the received investment action data in a database for use in later investment advice generation.

[0712] Input: Investment action submission data

[0713] Output: Database record

[0714] Specific operation: The server stores the received data in a database and uses it to generate advice next time.

[0715] (Application example 1)

[0716] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0717] In investment activities, there is a need for a means by which users can quickly and fairly obtain appropriate and effective investment advice. There is also a need for a mechanism to improve the accuracy of advice by reflecting the results of the implementation of competitively obtained advice in the generation of the next piece of advice. Furthermore, there is a need for a system that allows for real-time notifications of bidding information and investment advice, immediate implementation of the advice obtained, and feedback of the results.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0719] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through competitive bidding with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate subsequent advice; means for notifying the user of the bidding information and advice in real time; and means for implementing the investment advice obtained by the user and providing feedback on the investment results. This allows users to quickly obtain and implement optimal investment advice under transparent and fair competition. Furthermore, by reflecting the results, the accuracy of subsequent advice can be improved.

[0720] A "user" is a person who uses the system to input investment goals and risk tolerance, competitively obtain investment advice, and then implement it.

[0721] An "investment goal" is a target value that indicates a specific outcome of an investment set by a user.

[0722] "Risk tolerance" indicates the degree of investment risk that a user can accept.

[0723] "Artificial intelligence" is a technology that generates optimal investment advice based on the investment goals and risk tolerance entered by the user.

[0724] "Bidding" is the process by which multiple users competitively offer prices to obtain investment advice.

[0725] A "high bidder" is a user who offers the highest price during the bidding process.

[0726] "Investment advice" is advice or suggestions generated by artificial intelligence to assist users in their investment activities.

[0727] "Execution results" is data showing the results and outcomes of the investment activities that the user carried out based on the investment advice.

[0728] "Real-time notification" is a function that instantly notifies users of bidding information and investment advice.

[0729] "Feedback" is a process of collecting the results of the user's investment advice and reflecting them in the next generation of advice.

[0730] MODE FOR CARRYING OUT THE INVENTION

[0731] This invention is a system that allows users to competitively obtain and implement investment advice generated based on their investment goals and risk tolerance. This system allows users to purchase investment advice through a bidding process, and provides feedback on the results of the implementation of the advice to help generate the next piece of advice.

[0732] System Program

[0733] To implement this system, the following programs are used:

[0734] Program processing and hardware / software used

[0735] 1. User Registration and Login:

[0736] Users log in to the electronic payment app and create their own investment account. Authentication is performed using Firebase Authentication, and user data is stored in the Firebase Realtime Database.

[0737] 2. Enter your investment goals and risk tolerance:

[0738] Users enter their investment goals and risk tolerance within the app, and this information is sent to a server via the electronic payment app's backend (e.g., Google Cloud Functions).

[0739] 3. Investment advice generation:

[0740] The server receives investment goals and risk tolerance, and works with an artificial intelligence model (e.g., GPT-4) to generate appropriate investment advice, which is then stored in a database.

[0741] 4. Operation of the bidding system:

[0742] Investment advice is provided to users in the form of a bid. The bidding process is run using the AWS Lambda reference architecture, and bid information is sent in real time via Firebase Cloud Messaging. Users enter their bid amount, and the user who submits the highest bid becomes the highest bidder.

[0743] 5. Providing Investment Advice:

[0744] Once bidding closes, the highest bidder will be offered investment advice, and this notification will also be sent in real time via Firebase Cloud Messaging.

[0745] 6. Implementation and feedback of investment advice:

[0746] The highest bidder will make an investment based on the investment advice and provide feedback on the results to the app. The investment results will be sent back to the server and used to generate the next investment advice.

[0747] Specific examples

[0748] For example, User A logs into an electronic payment app, sets an investment goal of "aiming for an 8% annual return," and enters a risk tolerance of "high." The Investment Buddy AI then proposes a portfolio consisting of 80% stocks and 20% cryptocurrencies. This advice is provided in a bidding format, with User B being the highest bidder at 4,000 yen and obtaining this advice. User B then executes the investment through the electronic payment app and provides feedback on the results to the app.

[0749] Prompt Sentence Examples

[0750] "The user's investment goal is an 8% annual return, and their risk tolerance is high. Please suggest an optimal portfolio."

[0751] This system allows users to quickly obtain and implement optimal investment advice through transparent and fair competition. Furthermore, by reflecting the results, the accuracy of future advice can be improved.

[0752] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0753] Step 1: User Registration and Login

[0754] The user accesses the electronic payment app and creates an account.

[0755] Input: Username, email address, password, and other authentication information

[0756] Data processing: Validate credentials using Firebase Authentication and create user accounts

[0757] Output: Authentication token and user account information stored in Firebase Realtime Database.

[0758] What happens: When a user logs into your app, the server verifies the credentials entered and starts a session.

[0759] Step 2: Enter your investment goals and risk tolerance

[0760] Users enter their investment goals and risk tolerance into a form within the app.

[0761] Inputs: Investment goal (e.g., 8% annual return), risk tolerance (e.g., high)

[0762] Data processing: Convert the input information into JSON format and send it to the server via Google Cloud Functions

[0763] Output: Investment profile stored on the server

[0764] Specific operation: A request is sent from the terminal to the server, and the server stores the investment goals and risk tolerance in a database.

[0765] Step 3: Investment advice generation

[0766] The server then works with a generative AI model (GPT-4) based on the investment profile it receives.

[0767] Input: Investment goals and risk tolerance stored on the server

[0768] Data processing: Send prompts to the generative AI model to generate appropriate investment advice

[0769] Output: Generated investment advice saved in a database

[0770] Specific operation: The server sends the prompt statement "The user's investment goal is an 8% annual return and their risk tolerance is high. Please suggest the optimal portfolio." to the generative AI model and saves the advice obtained as a response.

[0771] Step 4: Operate the bidding system

[0772] Investment advice is provided in a bidding format, with multiple users making competitive bids.

[0773] Input: Bid amounts from multiple users

[0774] Data Processing: Bid amounts updated in real time and track the highest bids

[0775] Output: Real-time updated bidding information, highest bidder

[0776] How it works: Bid information is processed in real time using AWS Lambda, and users are notified via Firebase Cloud Messaging whenever the highest bid is updated.

[0777] Step 5: Providing investment advice

[0778] After the bidding closes, investment advice will be provided to the highest bidder.

[0779] Input: Maximum bid amount and highest bidder information

[0780] Data processing: Send notifications to the highest bidder and provide investment advice

[0781] Output: Advice given

[0782] Specific operation: The server confirms that the bidding has ended and notifies the highest bidder via Firebase Cloud Messaging to provide investment advice.

[0783] Step 6: Implementation and feedback of investment advice

[0784] The highest bidder makes an investment based on the investment advice obtained and feeds back the results to the server.

[0785] Input: Investment execution results

[0786] Data processing: Investment execution results are saved in a database and used to generate next-time advice.

[0787] Output: Feedback investment result data

[0788] Specific operation: The user makes an investment based on the investment advice, and sends the results to the server via the app. The server stores the results and uses them to generate the next investment advice.

[0789] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0790] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system uses artificial intelligence to generate investment advice based on the investment goals and risk tolerance entered by the user, and provides that advice through a bidding process. It also incorporates an emotion engine that recognizes the user's emotions, making it possible to tailor the investment advice according to the user's emotions.

[0791] User Registration and Login

[0792] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0793] Collaboration with Investment Buddy AI

[0794] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0795] Use of emotion engine

[0796] While the user is using the platform, the emotion engine recognizes the user's emotions. The emotion engine can use facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[0797] Generating and providing investment advice

[0798] The server sends the emotion data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates appropriate investment advice taking into account both the investment profile and the emotion data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[0799] Launch of bidding system

[0800] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0801] Determination and notification of highest bidder

[0802] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0803] Use and implementation of investment advice

[0804] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0805] Specific examples

[0806] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate subsequent advice.

[0807] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[0808] The processing flow will be explained below.

[0809] Step 1:

[0810] A user opens a website or application and clicks the login button with their PayPay account.

[0811] Step 2:

[0812] The terminal sends the entered user information to PayPay's authentication system.

[0813] Step 3:

[0814] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[0815] Step 4:

[0816] The terminal sends the received token to the server.

[0817] Step 5:

[0818] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[0819] Step 6:

[0820] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[0821] Step 7:

[0822] The terminal transmits this investment profile information to the server.

[0823] Step 8:

[0824] The server generates an investment profile based on the input information and sends that data to the Investment Buddy AI.

[0825] Step 9:

[0826] Based on the investment profile received, the Investment Buddy AI generates initial investment advice and returns it to the server.

[0827] Step 10:

[0828] The server stores the investment advice received from the investment buddy AI in a database.

[0829] Step 11:

[0830] The server notifies all users that new investment advice has been generated.

[0831] Step 12:

[0832] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[0833] Step 13:

[0834] The emotion engine recognizes the user's emotions by capturing the user's face through the camera and analyzing the emotions.

[0835] Step 14:

[0836] The emotion engine analyzes the text entered by the user and evaluates its emotion.

[0837] Step 15:

[0838] The terminal transmits the user's emotion data to the server.

[0839] Step 16:

[0840] The server sends the emotional data to the investment buddy AI, instructing it to adjust its investment advice.

[0841] Step 17:

[0842] The investment buddy AI takes into account the emotional data, adjusts existing investment advice or generates new advice, and returns it to the server.

[0843] Step 18:

[0844] The server stores the updated investment advice in the database and notifies all users again.

[0845] Step 19:

[0846] The server initiates a bidding session for investment advice and sets a bidding period.

[0847] Step 20:

[0848] The user inputs the amount he or she wishes to pay for the displayed investment advice and makes a bid.

[0849] Step 21:

[0850] The terminal transmits the user's bid amount to the server.

[0851] Step 22:

[0852] The server compares it with the current maximum bid and updates the new maximum bid.

[0853] Step 23:

[0854] The server repeats this process until the bidding period ends.

[0855] Step 24:

[0856] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[0857] Step 25:

[0858] The server generates a notification to the highest bidder.

[0859] Step 26:

[0860] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[0861] Step 27:

[0862] The user reviews the investment advice they have received and decides whether to act on it.

[0863] Step 28:

[0864] The terminal provides an interface for adjusting the investment portfolio based on the investment advice.

[0865] Step 29:

[0866] Enter the investment actions taken by the user into the system.

[0867] Step 30:

[0868] The device sends the execution details to the server.

[0869] Step 31:

[0870] The server stores the investment data executed by the user in a database to help generate future advice.

[0871] Example 2

[0872] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0873] Current investment advice systems generate advice mechanically, taking into account a user's individual investment goals and risk tolerance while ignoring emotional influences. This makes it difficult to provide flexible and appropriate advice that reflects the user's emotional state. It is also difficult to obtain investment advice fairly through a competitive bidding system. This leads to problems such as a decline in the quality of investment advice and a decline in user satisfaction.

[0874] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0875] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by a user; means for linking with artificial intelligence that generates investment advice based on the input information; means for collecting and recognizing emotional data of the user; means for adjusting the investment advice taking the emotional data into consideration; means for obtaining the investment advice through competitive bidding with other users; means for determining a highest bidder based on the bidding results and providing the investment advice to the highest bidder; and means for tracking the results of the investment advice and using them to generate the next piece of advice. This makes it possible to provide flexible and appropriate investment advice that reflects the user's emotional state, and to obtain and implement investment advice through a fair bidding system.

[0876] "Investment goal" refers to the specific investment results or target values ​​that the user wants to achieve.

[0877] "Risk tolerance" indicates the range or level of risk that a user can tolerate.

[0878] "Artificial intelligence" refers to the technology that enables computer systems to mimic human intelligence in problem-solving and decision-making.

[0879] "Emotion data" refers to data that indicates the user's emotional state analyzed based on facial expressions, text input, etc.

[0880] "Investment Advice" means investment recommendations or instructions generated based on a user's investment goals, risk tolerance, and sentiment data.

[0881] A "bidding system" is a system in which multiple users conduct bidding procedures to competitively obtain investment advice.

[0882] A "highest bidder" is a user who submits the highest bid in the bidding system.

[0883] A "digital payment system" is a system for making monetary payments electronically.

[0884] "Investment Data" refers to data including investment actions taken by a user and past investment history.

[0885] An "investment profile" is comprehensive investment information that integrates a user's investment goals, risk tolerance, investment period, etc.

[0886] "Bidding results" refers to the results showing the bid amounts submitted in the bidding system and the final decision on bidders based on those bid amounts.

[0887] An "investment action" is a specific investment operation or behavior that a user performs based on investment advice.

[0888] MODE FOR CARRYING OUT THE INVENTION

[0889] The present invention relates to a system that enables users to competitively obtain effective investment advice and to efficiently carry out investment activities. A specific implementation method of this system will be described below.

[0890] User Registration and Login

[0891] A user opens a website or application and first logs in with their account. The user can be authenticated using a digital payment system. The server stores the user's information in a database and starts a session if authentication is successful.

[0892] Collaboration with Investment Buddy AI

[0893] Users input their investment goals, risk tolerance, and investment period into the terminal. The terminal sends this information to the server. The server generates an investment profile based on this data and sends that data to the Investment Buddy AI. The Investment Buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0894] Use of emotion engine

[0895] While the user is using the platform, the emotion engine recognizes the user's emotions. Specifically, it uses facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[0896] Generating and providing investment advice

[0897] The server sends the emotional data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates optimal investment advice taking into account both the investment profile and the emotional data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[0898] Launch of bidding system

[0899] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process is repeated until the bidding period ends.

[0900] Determination and notification of highest bidder

[0901] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0902] Use and implementation of investment advice

[0903] The user checks the investment advice he / she has received and takes an investment action based on it. The terminal sends the investment action taken by the user to the server. The server stores this investment data in a database and uses it for future investment advice generation.

[0904] Specific examples

[0905] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this information to the server, which passes it on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen, and User B bids 2,500 yen, with User B ultimately being determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0906] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[0907] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0908] Step 1:

[0909] A user opens a website or application and registers. The user enters information such as their name, email address, and password. This information is collected as input data on the device and sent to the server. The server stores this data in a database, completing the user registration.

[0910] Step 2:

[0911] The user logs in with an existing account. The login information (email address, password) is sent from the terminal to the server. The server compares it with the information in the database and starts a session if authentication is successful. The input is the login information and the output is a session ID.

[0912] Step 3:

[0913] The user inputs their investment goal (e.g., 10% annual return), risk tolerance (e.g., medium), and investment period (e.g., 5 years) into the terminal. This information is sent from the terminal to the server. The server generates an investment profile for the user based on this data. The input is the investment goal, and the output is the investment profile.

[0914] Step 4:

[0915] The server sends the generated investment profile to the investment buddy AI. The investment buddy AI analyzes the investment profile and generates appropriate investment advice. The generated investment advice is sent back to the server. The investment profile is the input, and the investment advice is the output.

[0916] Step 5:

[0917] When a user uses the system, the device uses facial recognition technology to capture the user's facial expressions and analyze emotional data in real time. The text entered by the user is also analyzed. This emotional data is sent to the server. The input is facial recognition data and text data, and the output is emotional data.

[0918] Step 6:

[0919] The server provides the emotional data obtained from the emotion engine to the Investment Buddy AI. The Investment Buddy AI adjusts investment advice taking this emotional data into account. For example, if the user's emotion is judged to be "anxiety," advice to reduce risk is generated. The input is emotional data, and the output is adjusted investment advice.

[0920] Step 7:

[0921] The server stores the adjusted investment advice in a database and notifies all users of it. The terminal provides an interface that displays the investment advice to users. The input is the adjusted investment advice, and the output is notification information.

[0922] Step 8:

[0923] The server starts a bidding session for each investment advice. The user inputs the amount they are willing to pay, which is sent from their terminal to the server. The server compares each bid and updates the maximum bid. The input is the bid amount, and the output is the current maximum bid.

[0924] Step 9:

[0925] When the bidding period ends, the server checks the final bidding results and determines the highest bidder. The terminal displays a notification to the highest bidder saying "Investment advice is now available." The input is bidding data, and the output is the final bidding result and notification.

[0926] Step 10:

[0927] The user checks the investment advice they receive and takes an investment action based on it. The terminal sends the user's investment action to the server. The server stores this data in a database and uses it to generate future advice. The input is investment action data, and the output is updated database information.

[0928] Through the above processing steps, users can obtain flexible and appropriate investment advice based on their individual investment goals and risk tolerance, and can make investments under fair competition.

[0929] (Application example 2)

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

[0931] Conventional investment systems lack a competitive method for users to obtain individually optimized investment advice, and do not provide investment advice that takes into account the user's emotions. This creates a problem in that the investment advice does not reflect the user's psychological state when making investment decisions. Furthermore, there is a lack of a method for optimizing and competitively obtaining investment educational content according to individual needs.

[0932] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0933] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through a competitive bidding process with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate the next piece of advice; means for recognizing the user's emotions and adjusting the investment advice in accordance with the emotions; and means for generating optimal educational content based on the user's emotional data and investment profile and providing the right to view the educational content through a bidding process. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and competitive optimization is also introduced into the method of providing educational content.

[0934] "Investment goal" refers to the specific profit or outcome that a user aims to achieve when making an investment.

[0935] "Risk tolerance" refers to the level of risk a user can accept in an investment.

[0936] "Artificial intelligence" refers to technology and programs that perform advanced calculations and analysis based on user input data to generate appropriate investment advice.

[0937] "Bidding" refers to a system in which multiple users submit amounts that indicate their willingness to pay to obtain specific investment advice, and the person who submits the highest amount receives the advice.

[0938] "Emotion recognition" is a technology that evaluates a user's psychological state and emotions through facial recognition technology and text analysis, and acquires that data.

[0939] "Educational Content" means educational information or instructional materials designed to enhance a user's investment knowledge or experience.

[0940] "Viewing rights" refers to the right of a specific user to view specific educational content.

[0941] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which users input their investment goals, risk tolerance, investment period, etc., and artificial intelligence generates optimal investment advice based on that information and provides that advice in a bidding format. It is also possible to recognize users' emotions and adjust the investment advice accordingly. Detailed embodiments of the system are described below.

[0942] The server first provides a means for users to input their investment goals and risk tolerance. Users input this information from devices such as smartphones or PCs and send it to the server. In this case, investment goals refer to the specific profits or results that the user aims to achieve, and risk tolerance refers to the level of risk the user is willing to accept in investments.

[0943] The server works with an artificial intelligence (AI) that generates investment advice based on the information sent by the user. This AI performs advanced calculations and analysis based on the data input by the user to generate appropriate investment advice.

[0944] Furthermore, an emotion engine for emotion recognition recognizes the user's emotions while the user is using the platform. Emotion recognition is a technology that evaluates the user's mental state and emotions through facial recognition technology and text analysis, and acquires the data. For this purpose, the smartphone's camera and various sensors are used. Specific examples include OpenCV (for facial recognition), TextBlob (text emotion analysis), and EmotionRecognitionEngine (for emotion recognition).

[0945] The server sends this emotional data to the investment buddy AI, which then generates optimal investment advice by taking into account both the investment profile and the emotional data. This generated advice is stored in a database and offered to users in a competitive bidding format. In a bidding format, multiple users submit the amount they are willing to pay to obtain a particular investment advice, and the person who submits the highest amount receives the advice.

[0946] Additionally, educational content is generated based on users' emotional data and investment profiles. Educational content refers to educational information and instructional materials to improve users' investment knowledge and experience. Viewing rights are also offered through a bidding process, and users participate by entering the amount they are willing to pay.

[0947] The server determines the highest bidder based on the bidding results and notifies the user. The highest bidder can then use the investment advice and educational content they have won to help them with their actual investment activities. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and introduces competitive optimization into the method of providing educational content.

[0948] For example, consider the following prompt:

[0949] "Recommend investment education content to a user with a medium risk tolerance who aims for a 10% annual return. The user's current emotion is 'anxious.' Based on this information, generate optimized investment education content and initiate a viewing rights bidding session tailored to that content."

[0950] In this way, the system of the present invention realizes the generation and provision of investment advice and educational content based on user input data and emotional data.

[0951] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0952] Step 1:

[0953] Users input their investment goals, risk tolerance, and investment period from a device such as a smartphone or PC. The device then sends this information to the server. The input here is text data, and the output is user profile data that is passed to the server.

[0954] Step 2:

[0955] The server passes the received user profile data to an artificial intelligence (Investment Buddy AI) that generates investment advice. The Investment Buddy AI generates an investment profile for the user based on this data and generates appropriate investment advice. The input here is the user profile data, and the output is investment advice.

[0956] Step 3:

[0957] While a user is using the platform, the device's camera and sensors are used to capture the user's facial expressions and input text in real time. The device then passes the collected data to an emotion engine, which analyzes the user's emotions. The input here is image and text data, and the output is emotion data.

[0958] Step 4:

[0959] The server sends the user's emotional data and investment advice to the investment buddy AI, which then regenerates optimized investment advice that takes the user's psychological state into account. The investment buddy AI then takes the user's emotional data into account and generates advice to reduce risk, etc. The input here is the emotional data and investment advice, and the output is the adjusted investment advice.

[0960] Step 5:

[0961] The server stores the generated adjusted investment advice in a database and provides it to users in the form of a bid. Users submit bids for the presented investment advice through their terminals. The bids are made through a digital payment system, and the output is bid amount data.

[0962] Step 6:

[0963] Once the bidding period ends, the server starts the process of determining the highest bidder. The input is the bid amount data of each user, and the output is the highest bidder information. The server notifies the highest bidder of the bidding result.

[0964] Step 7:

[0965] The highest bidder confirms the investment advice and reflects it in their actual investment activities. The terminal sends the investment actions taken by the user to the server. The input here is the user's investment action data, and the output is the updated investment data.

[0966] Step 8:

[0967] The server stores the user's investment action data in a database and uses it to generate investment advice from the next time onwards. The input here is the updated investment data, and the output is the optimized data used to generate the next investment advice.

[0968] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0969] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0970] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0971] [Third embodiment]

[0972] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0973] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0974] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0975] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0976] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0977] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0978] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0979] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0980] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0981] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0982] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0983] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0984] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[0985] User Registration and Login

[0986] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[0987] Collaboration with Investment Buddy AI

[0988] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[0989] Generating and providing investment advice

[0990] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[0991] Launch of bidding system

[0992] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[0993] Determination and notification of highest bidder

[0994] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[0995] Use and implementation of investment advice

[0996] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[0997] Specific examples

[0998] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[0999] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[1000] The processing flow will be explained below.

[1001] Step 1:

[1002] A user opens a website or application and clicks the login button with their PayPay account.

[1003] Step 2:

[1004] The terminal sends the entered user information to PayPay's authentication system.

[1005] Step 3:

[1006] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[1007] Step 4:

[1008] The terminal sends the received token to the server.

[1009] Step 5:

[1010] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[1011] Step 6:

[1012] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[1013] Step 7:

[1014] The terminal transmits the input investment profile information to the server.

[1015] Step 8:

[1016] The server generates an investment profile based on this information and sends the data to the Investment Buddy AI for collaboration.

[1017] Step 9:

[1018] Based on the investment profile received, the Investment Buddy AI generates appropriate investment advice (e.g., a portfolio of 70% stocks and 30% bonds) and returns it to the server.

[1019] Step 10:

[1020] The server stores the investment advice received from the investment buddy AI in a database.

[1021] Step 11:

[1022] The server notifies all users that new investment advice has been generated.

[1023] Step 12:

[1024] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[1025] Step 13:

[1026] The server initiates a bidding session for investment advice and sets a bidding period.

[1027] Step 14:

[1028] The user enters a bid amount for the displayed investment advice and makes a bid.

[1029] Step 15:

[1030] The terminal transmits the user's bid amount to the server.

[1031] Step 16:

[1032] The server compares it with the current maximum bid and updates the new maximum bid.

[1033] Step 17:

[1034] The server repeats this process until the bidding period ends.

[1035] Step 18:

[1036] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[1037] Step 19:

[1038] The server generates a notification to the highest bidder.

[1039] Step 20:

[1040] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[1041] Step 21:

[1042] The user reviews the investment advice they have received and decides whether to act on it.

[1043] Step 22:

[1044] The terminal provides an interface for the user to adjust the investment portfolio based on the investment advice.

[1045] Step 23:

[1046] Enter the investment actions taken by the user into the system.

[1047] Step 24:

[1048] The device sends the execution details to the server.

[1049] Step 25:

[1050] The server stores the investment data executed by the user in a database to help generate future advice.

[1051] Example 1

[1052] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1053] Conventional investment advice systems make it difficult for users to efficiently obtain and implement optimal investment advice. They also lack the ability to improve the quality of investment advice or provide individualized advice tailored to users' risk tolerance. Furthermore, they face the problem of being unable to consistently obtain investment advice competitively and track its effectiveness.

[1054] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1055] In this invention, the server includes means for inputting investment goals and risk tolerance determined by a user, means for linking with artificial intelligence that generates investment advice based on the input information, means for obtaining the investment advice through competitive bidding with other users, means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder, means for tracking the results of implementing the investment advice and using them to generate next advice, means for notifying the highest bidder, means for generating an investment profile, and means for saving the investment advice. This enables users to obtain optimal investment advice that takes into account their individual investment goals and risk tolerance through transparent and fair competition and to track its effectiveness.

[1056] "User" refers to an individual or corporation that uses the System to obtain investment advice.

[1057] "Investment goal" refers to the target investment return or asset growth that a user wishes to achieve.

[1058] "Risk tolerance" refers to the degree of risk a user is willing to accept in an investment.

[1059] "Input means" refers to an interface that allows a user to input information such as investment goals and risk tolerance.

[1060] "Artificial intelligence" refers to automated systems that use computer programs to generate investment advice based on user input data.

[1061] "Means for collaboration" refers to the means by which the server communicates with the artificial intelligence to generate investment advice.

[1062] "Means of obtaining through bidding" refers to the process by which a user obtains investment advice by making competitive bids with other users.

[1063] "Means for determining the highest bidder" refers to the means for identifying the bidder who offers the highest amount after the bidding period has ended.

[1064] "Means of providing investment advice" refers to the means of providing the generated investment advice to the highest bidder.

[1065] The "means for tracking execution results" refers to a means for recording the results of investment actions taken by a user based on investment advice, and for using the results to generate future advice.

[1066] "Means of Notification" means the method for sending notification to the highest bidder.

[1067] "Investment profile" refers to profile data generated based on information such as a user's investment goals, risk tolerance, and investment period.

[1068] "Means for storing" refers to a method for storing the generated investment advice in a storage device such as a database.

[1069] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[1070] System Configuration

[1071] The system consists of the following hardware and software components:

[1072] User terminal (terminal): A device that can connect to the Internet (such as a PC, smartphone, or tablet).

[1073] Server: A server for hosting back-end systems, including databases, application servers, and artificial intelligence models.

[1074] Investment Buddy AI (artificial intelligence): A generative AI model that generates investment advice based on input data from users.

[1075] User Registration and Login

[1076] A user opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[1077] Collaboration with Investment Buddy AI

[1078] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1079] Generating and providing investment advice

[1080] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[1081] Launch of bidding system

[1082] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[1083] Determination and notification of highest bidder

[1084] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1085] Use and implementation of investment advice

[1086] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[1087] Specific examples

[1088] For example, a user sets an investment goal of "aiming for a 10% annual return," inputs a risk tolerance of "medium," and an investment period of "5 years." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of "70% stocks, 30% bonds." The server records this advice in a database and starts a bidding session. For example, User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[1089] Prompt Sentence Examples

[1090] "Provide investment advice for those with a moderate risk tolerance, aiming for a 10% annual return."

[1091] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[1092] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1093] Step 1:

[1094] A user accesses a website or application, opens the login screen, and enters their account information (username and password).

[1095] Input: Username, Password

[1096] Output: Login request

[1097] Specific operation: The user opens a login screen in a browser or application and enters their username and password in the designated form.

[1098] Step 2:

[1099] The device sends the user's login information (username and password) to the server.

[1100] Input: Username, Password

[1101] Output: HTTP POST request

[1102] Specific operation: The terminal sends the login information to the server using an HTTP POST request.

[1103] Step 3:

[1104] The server checks the login information against existing user information in the database, and if it matches, it issues a session ID as a successful authentication.

[1105] Input: Username, Password

[1106] Output: Authentication result (success / failure), session ID (if successful)

[1107] What happens: The server performs a database query to compare the login information with its records in the database, and if there is a match, generates a session ID.

[1108] Step 4:

[1109] The server returns the authentication result to the terminal, and if authentication is successful, the dashboard screen is displayed.

[1110] Input: Authentication result, session ID (if successful)

[1111] Output: Login success message, dashboard screen

[1112] Specific operation: The server returns the authentication result to the terminal as an HTTP response, and the terminal displays a login success message and the dashboard screen.

[1113] Step 5:

[1114] The user enters their investment goals, risk tolerance, and investment period.

[1115] Inputs: Investment goal, risk tolerance, investment period

[1116] Output: Investment information input request

[1117] Specific operation: The user enters information such as investment goals, risk tolerance, and investment period into a specified form.

[1118] Step 6:

[1119] The terminal transmits the user's investment information to the server.

[1120] Inputs: Investment goal, risk tolerance, investment period

[1121] Output: HTTP POST request

[1122] Specific operation: The terminal sends investment information to the server using an HTTP POST request.

[1123] Step 7:

[1124] The server generates an investment profile based on the user's investment information and sends that data to the investment buddy AI.

[1125] Inputs: Investment goal, risk tolerance, investment period

[1126] Output: Investment profile, API request

[1127] Specific operation: The server processes the investment information, creates an investment profile, and sends it to the investment buddy AI via an API request.

[1128] Step 8:

[1129] The Investment Buddy AI generates investment advice based on the investment profile received and sends the results back to the server.

[1130] Input: Investment Profile

[1131] Output: Investment advice

[1132] Specific operation: The Investment Buddy AI uses a generative AI model to analyze the investment profile, generate optimal investment advice, and send it back to the server via an API request.

[1133] Step 9:

[1134] The server stores the investment advice received from the investment buddy AI in a database and notifies the user.

[1135] Input: Investment advice

[1136] Output: Database records, advice notifications

[1137] Specific operation: The server stores the investment advice in a database and notifies all users of the advice.

[1138] Step 10:

[1139] The terminal provides an interface for displaying investment advice to the user.

[1140] Input:Advice Notice

[1141] Output: Advice display screen

[1142] Specific operation: The terminal generates and displays an HTML page for displaying the investment advice content on the user interface.

[1143] Step 11:

[1144] The server initiates a bidding session for investment advice and sets a bidding period.

[1145] Input: Investment advice

[1146] Output: Start of bidding session, bidding period setting

[1147] Specific operation: The server starts a bidding session and sends information setting the bidding period to the terminal.

[1148] Step 12:

[1149] The user enters the amount they would like to pay for the investment advice displayed and makes a bid.

[1150] Input: Bid amount

[1151] Output: Bid request

[1152] Specific operation: The user enters a bid amount and clicks the bid button.

[1153] Step 13:

[1154] The terminal transmits the user's bid amount to the server.

[1155] Input: Bid amount

[1156] Output: Send bid data

[1157] Specific operation: The terminal sends the bid data to the server using an HTTP POST request.

[1158] Step 14:

[1159] The server keeps updating the highest bids and checks the final results at the end of the bidding period.

[1160] Input: Bidding data

[1161] Output: Highest bid, final result

[1162] Specific operation: The server processes the bid data, stores it in the database, updates the highest bid, and confirms the final result at the end of the bidding period.

[1163] Step 15:

[1164] The server ultimately determines the highest bidder and records it in a database.

[1165] Input: Bid Results

[1166] Output: Highest bidder determination data

[1167] Specific Actions: The server identifies the highest bidder and records it in a database.

[1168] Step 16:

[1169] The terminal displays a notification to the highest bidder saying "Investment Advice Now Available."

[1170] Input: Highest bidder determination data

[1171] Output: Notification message

[1172] Specific operation: The terminal displays a notification to the highest bidder.

[1173] Step 17:

[1174] Review the investment advice you receive and adjust your investment portfolio accordingly.

[1175] Input: Investment advice

[1176] Output: Adjusted investment portfolio

[1177] Specific behavior: A user views investment advice and sets up a portfolio.

[1178] Step 18:

[1179] The terminal transmits the investment actions performed by the user to the server.

[1180] Input: Investment action data

[1181] Output: Investment action sending data

[1182] Specific operation: The terminal uses an HTTP POST request to send investment action data to the server.

[1183] Step 19:

[1184] The server stores the received investment action data in a database for use in later investment advice generation.

[1185] Input: Investment action submission data

[1186] Output: Database record

[1187] Specific operation: The server stores the received data in a database and uses it to generate advice next time.

[1188] (Application example 1)

[1189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1190] In investment activities, there is a need for a means by which users can quickly and fairly obtain appropriate and effective investment advice. There is also a need for a mechanism to improve the accuracy of advice by reflecting the results of the implementation of competitively obtained advice in the generation of the next piece of advice. Furthermore, there is a need for a system that allows for real-time notifications of bidding information and investment advice, immediate implementation of the advice obtained, and feedback of the results.

[1191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1192] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through competitive bidding with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate subsequent advice; means for notifying the user of the bidding information and advice in real time; and means for implementing the investment advice obtained by the user and providing feedback on the investment results. This allows users to quickly obtain and implement optimal investment advice under transparent and fair competition. Furthermore, by reflecting the results, the accuracy of subsequent advice can be improved.

[1193] A "user" is a person who uses the system to input investment goals and risk tolerance, competitively obtain investment advice, and then implement it.

[1194] An "investment goal" is a target value that indicates a specific outcome of an investment set by a user.

[1195] "Risk tolerance" indicates the degree of investment risk that a user can accept.

[1196] "Artificial intelligence" is a technology that generates optimal investment advice based on the investment goals and risk tolerance entered by the user.

[1197] "Bidding" is the process by which multiple users competitively offer prices to obtain investment advice.

[1198] A "high bidder" is a user who offers the highest price during the bidding process.

[1199] "Investment advice" is advice or suggestions generated by artificial intelligence to assist users in their investment activities.

[1200] "Execution results" is data showing the results and outcomes of the investment activities that the user carried out based on the investment advice.

[1201] "Real-time notification" is a function that instantly notifies users of bidding information and investment advice.

[1202] "Feedback" is a process of collecting the results of the user's investment advice and reflecting them in the next generation of advice.

[1203] MODE FOR CARRYING OUT THE INVENTION

[1204] This invention is a system that allows users to competitively obtain and implement investment advice generated based on their investment goals and risk tolerance. This system allows users to purchase investment advice through a bidding process, and provides feedback on the results of the implementation of the advice to help generate the next piece of advice.

[1205] System Program

[1206] To implement this system, the following programs are used:

[1207] Program processing and hardware / software used

[1208] 1. User Registration and Login:

[1209] Users log in to the electronic payment app and create their own investment account. Authentication is performed using Firebase Authentication, and user data is stored in the Firebase Realtime Database.

[1210] 2. Enter your investment goals and risk tolerance:

[1211] Users enter their investment goals and risk tolerance within the app, and this information is sent to a server via the electronic payment app's backend (e.g., Google Cloud Functions).

[1212] 3. Investment advice generation:

[1213] The server receives investment goals and risk tolerance, and works with an artificial intelligence model (e.g., GPT-4) to generate appropriate investment advice, which is then stored in a database.

[1214] 4. Operation of the bidding system:

[1215] Investment advice is provided to users in the form of a bid. The bidding process is run using the AWS Lambda reference architecture, and bid information is sent in real time via Firebase Cloud Messaging. Users enter their bid amount, and the user who submits the highest bid becomes the highest bidder.

[1216] 5. Providing Investment Advice:

[1217] Once bidding closes, the highest bidder will be offered investment advice, and this notification will also be sent in real time via Firebase Cloud Messaging.

[1218] 6. Implementation and feedback of investment advice:

[1219] The highest bidder will make an investment based on the investment advice and provide feedback on the results to the app. The investment results will be sent back to the server and used to generate the next investment advice.

[1220] Specific examples

[1221] For example, User A logs into an electronic payment app, sets an investment goal of "aiming for an 8% annual return," and enters a risk tolerance of "high." The Investment Buddy AI then proposes a portfolio consisting of 80% stocks and 20% cryptocurrencies. This advice is provided in a bidding format, with User B being the highest bidder at 4,000 yen and obtaining this advice. User B then executes the investment through the electronic payment app and provides feedback on the results to the app.

[1222] Prompt Sentence Examples

[1223] "The user's investment goal is an 8% annual return, and their risk tolerance is high. Please suggest an optimal portfolio."

[1224] This system allows users to quickly obtain and implement optimal investment advice through transparent and fair competition. Furthermore, by reflecting the results, the accuracy of future advice can be improved.

[1225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1226] Step 1: User Registration and Login

[1227] The user accesses the electronic payment app and creates an account.

[1228] Input: Username, email address, password, and other authentication information

[1229] Data processing: Validate credentials using Firebase Authentication and create user accounts

[1230] Output: Authentication token and user account information stored in Firebase Realtime Database.

[1231] What happens: When a user logs into your app, the server verifies the credentials entered and starts a session.

[1232] Step 2: Enter your investment goals and risk tolerance

[1233] Users enter their investment goals and risk tolerance into a form within the app.

[1234] Inputs: Investment goal (e.g., 8% annual return), risk tolerance (e.g., high)

[1235] Data processing: Convert the input information into JSON format and send it to the server via Google Cloud Functions

[1236] Output: Investment profile stored on the server

[1237] Specific operation: A request is sent from the terminal to the server, and the server stores the investment goals and risk tolerance in a database.

[1238] Step 3: Investment advice generation

[1239] The server then works with a generative AI model (GPT-4) based on the investment profile it receives.

[1240] Input: Investment goals and risk tolerance stored on the server

[1241] Data processing: Send prompts to the generative AI model to generate appropriate investment advice

[1242] Output: Generated investment advice saved in a database

[1243] Specific operation: The server sends the prompt statement "The user's investment goal is an 8% annual return and their risk tolerance is high. Please suggest the optimal portfolio." to the generative AI model and saves the advice obtained as a response.

[1244] Step 4: Operate the bidding system

[1245] Investment advice is provided in a bidding format, with multiple users making competitive bids.

[1246] Input: Bid amounts from multiple users

[1247] Data Processing: Bid amounts updated in real time and track the highest bids

[1248] Output: Real-time updated bidding information, highest bidder

[1249] How it works: Bid information is processed in real time using AWS Lambda, and users are notified via Firebase Cloud Messaging whenever the highest bid is updated.

[1250] Step 5: Providing investment advice

[1251] After the bidding closes, investment advice will be provided to the highest bidder.

[1252] Input: Maximum bid amount and highest bidder information

[1253] Data processing: Send notifications to the highest bidder and provide investment advice

[1254] Output: Advice given

[1255] Specific operation: The server confirms that the bidding has ended and notifies the highest bidder via Firebase Cloud Messaging to provide investment advice.

[1256] Step 6: Implementation and feedback of investment advice

[1257] The highest bidder makes an investment based on the investment advice obtained and feeds back the results to the server.

[1258] Input: Investment execution results

[1259] Data processing: Investment execution results are saved in a database and used to generate next-time advice.

[1260] Output: Feedback investment result data

[1261] Specific operation: The user makes an investment based on the investment advice, and sends the results to the server via the app. The server stores the results and uses them to generate the next investment advice.

[1262] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1263] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system uses artificial intelligence to generate investment advice based on the investment goals and risk tolerance entered by the user, and provides that advice through a bidding process. It also incorporates an emotion engine that recognizes the user's emotions, making it possible to tailor the investment advice according to the user's emotions.

[1264] User Registration and Login

[1265] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[1266] Collaboration with Investment Buddy AI

[1267] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1268] Use of emotion engine

[1269] While the user is using the platform, the emotion engine recognizes the user's emotions. The emotion engine can use facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[1270] Generating and providing investment advice

[1271] The server sends the emotion data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates appropriate investment advice taking into account both the investment profile and the emotion data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[1272] Launch of bidding system

[1273] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[1274] Determination and notification of highest bidder

[1275] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1276] Use and implementation of investment advice

[1277] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[1278] Specific examples

[1279] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate subsequent advice.

[1280] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[1281] The processing flow will be explained below.

[1282] Step 1:

[1283] A user opens a website or application and clicks the login button with their PayPay account.

[1284] Step 2:

[1285] The terminal sends the entered user information to PayPay's authentication system.

[1286] Step 3:

[1287] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[1288] Step 4:

[1289] The terminal sends the received token to the server.

[1290] Step 5:

[1291] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[1292] Step 6:

[1293] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[1294] Step 7:

[1295] The terminal transmits this investment profile information to the server.

[1296] Step 8:

[1297] The server generates an investment profile based on the input information and sends that data to the Investment Buddy AI.

[1298] Step 9:

[1299] Based on the investment profile received, the Investment Buddy AI generates initial investment advice and returns it to the server.

[1300] Step 10:

[1301] The server stores the investment advice received from the investment buddy AI in a database.

[1302] Step 11:

[1303] The server notifies all users that new investment advice has been generated.

[1304] Step 12:

[1305] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[1306] Step 13:

[1307] The emotion engine recognizes the user's emotions by capturing the user's face through the camera and analyzing the emotions.

[1308] Step 14:

[1309] The emotion engine analyzes the text entered by the user and evaluates its emotion.

[1310] Step 15:

[1311] The terminal transmits the user's emotion data to the server.

[1312] Step 16:

[1313] The server sends the emotional data to the investment buddy AI, instructing it to adjust its investment advice.

[1314] Step 17:

[1315] The investment buddy AI takes into account the emotional data, adjusts existing investment advice or generates new advice, and returns it to the server.

[1316] Step 18:

[1317] The server stores the updated investment advice in the database and notifies all users again.

[1318] Step 19:

[1319] The server initiates a bidding session for investment advice and sets a bidding period.

[1320] Step 20:

[1321] The user inputs the amount he or she wishes to pay for the displayed investment advice and makes a bid.

[1322] Step 21:

[1323] The terminal transmits the user's bid amount to the server.

[1324] Step 22:

[1325] The server compares it with the current maximum bid and updates the new maximum bid.

[1326] Step 23:

[1327] The server repeats this process until the bidding period ends.

[1328] Step 24:

[1329] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[1330] Step 25:

[1331] The server generates a notification to the highest bidder.

[1332] Step 26:

[1333] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[1334] Step 27:

[1335] The user reviews the investment advice they have received and decides whether to act on it.

[1336] Step 28:

[1337] The terminal provides an interface for adjusting the investment portfolio based on the investment advice.

[1338] Step 29:

[1339] Enter the investment actions taken by the user into the system.

[1340] Step 30:

[1341] The device sends the execution details to the server.

[1342] Step 31:

[1343] The server stores the investment data executed by the user in a database to help generate future advice.

[1344] Example 2

[1345] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1346] Current investment advice systems generate advice mechanically, taking into account a user's individual investment goals and risk tolerance while ignoring emotional influences. This makes it difficult to provide flexible and appropriate advice that reflects the user's emotional state. It is also difficult to obtain investment advice fairly through a competitive bidding system. This leads to problems such as a decline in the quality of investment advice and a decline in user satisfaction.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1348] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by a user; means for linking with artificial intelligence that generates investment advice based on the input information; means for collecting and recognizing emotional data of the user; means for adjusting the investment advice taking the emotional data into consideration; means for obtaining the investment advice through competitive bidding with other users; means for determining a highest bidder based on the bidding results and providing the investment advice to the highest bidder; and means for tracking the results of the investment advice and using them to generate the next piece of advice. This makes it possible to provide flexible and appropriate investment advice that reflects the user's emotional state, and to obtain and implement investment advice through a fair bidding system.

[1349] "Investment goal" refers to the specific investment results or target values ​​that the user wants to achieve.

[1350] "Risk tolerance" indicates the range or level of risk that a user can tolerate.

[1351] "Artificial intelligence" refers to the technology that enables computer systems to mimic human intelligence in problem-solving and decision-making.

[1352] "Emotion data" refers to data that indicates the user's emotional state analyzed based on facial expressions, text input, etc.

[1353] "Investment Advice" means investment recommendations or instructions generated based on a user's investment goals, risk tolerance, and sentiment data.

[1354] A "bidding system" is a system in which multiple users conduct bidding procedures to competitively obtain investment advice.

[1355] A "highest bidder" is a user who submits the highest bid in the bidding system.

[1356] A "digital payment system" is a system for making monetary payments electronically.

[1357] "Investment Data" refers to data including investment actions taken by a user and past investment history.

[1358] An "investment profile" is comprehensive investment information that integrates a user's investment goals, risk tolerance, investment period, etc.

[1359] "Bidding results" refers to the results showing the bid amounts submitted in the bidding system and the final decision on bidders based on those bid amounts.

[1360] An "investment action" is a specific investment operation or behavior that a user performs based on investment advice.

[1361] MODE FOR CARRYING OUT THE INVENTION

[1362] The present invention relates to a system that enables users to competitively obtain effective investment advice and to efficiently carry out investment activities. A specific implementation method of this system will be described below.

[1363] User Registration and Login

[1364] A user opens a website or application and first logs in with their account. The user can be authenticated using a digital payment system. The server stores the user's information in a database and starts a session if authentication is successful.

[1365] Collaboration with Investment Buddy AI

[1366] Users input their investment goals, risk tolerance, and investment period into the terminal. The terminal sends this information to the server. The server generates an investment profile based on this data and sends that data to the Investment Buddy AI. The Investment Buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1367] Use of emotion engine

[1368] While the user is using the platform, the emotion engine recognizes the user's emotions. Specifically, it uses facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[1369] Generating and providing investment advice

[1370] The server sends the emotional data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates optimal investment advice taking into account both the investment profile and the emotional data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[1371] Launch of bidding system

[1372] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process is repeated until the bidding period ends.

[1373] Determination and notification of highest bidder

[1374] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1375] Use and implementation of investment advice

[1376] The user checks the investment advice he / she has received and takes an investment action based on it. The terminal sends the investment action taken by the user to the server. The server stores this investment data in a database and uses it for future investment advice generation.

[1377] Specific examples

[1378] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this information to the server, which passes it on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen, and User B bids 2,500 yen, with User B ultimately being determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[1379] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[1380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1381] Step 1:

[1382] A user opens a website or application and registers. The user enters information such as their name, email address, and password. This information is collected as input data on the device and sent to the server. The server stores this data in a database, completing the user registration.

[1383] Step 2:

[1384] The user logs in with an existing account. The login information (email address, password) is sent from the terminal to the server. The server compares it with the information in the database and starts a session if authentication is successful. The input is the login information and the output is a session ID.

[1385] Step 3:

[1386] The user inputs their investment goal (e.g., 10% annual return), risk tolerance (e.g., medium), and investment period (e.g., 5 years) into the terminal. This information is sent from the terminal to the server. The server generates an investment profile for the user based on this data. The input is the investment goal, and the output is the investment profile.

[1387] Step 4:

[1388] The server sends the generated investment profile to the investment buddy AI. The investment buddy AI analyzes the investment profile and generates appropriate investment advice. The generated investment advice is sent back to the server. The investment profile is the input, and the investment advice is the output.

[1389] Step 5:

[1390] When a user uses the system, the device uses facial recognition technology to capture the user's facial expressions and analyze emotional data in real time. The text entered by the user is also analyzed. This emotional data is sent to the server. The input is facial recognition data and text data, and the output is emotional data.

[1391] Step 6:

[1392] The server provides the emotional data obtained from the emotion engine to the Investment Buddy AI. The Investment Buddy AI adjusts investment advice taking this emotional data into account. For example, if the user's emotion is judged to be "anxiety," advice to reduce risk is generated. The input is emotional data, and the output is adjusted investment advice.

[1393] Step 7:

[1394] The server stores the adjusted investment advice in a database and notifies all users of it. The terminal provides an interface that displays the investment advice to users. The input is the adjusted investment advice, and the output is notification information.

[1395] Step 8:

[1396] The server starts a bidding session for each investment advice. The user inputs the amount they are willing to pay, which is sent from their terminal to the server. The server compares each bid and updates the maximum bid. The input is the bid amount, and the output is the current maximum bid.

[1397] Step 9:

[1398] When the bidding period ends, the server checks the final bidding results and determines the highest bidder. The terminal displays a notification to the highest bidder saying "Investment advice is now available." The input is bidding data, and the output is the final bidding result and notification.

[1399] Step 10:

[1400] The user checks the investment advice they receive and takes an investment action based on it. The terminal sends the user's investment action to the server. The server stores this data in a database and uses it to generate future advice. The input is investment action data, and the output is updated database information.

[1401] Through the above processing steps, users can obtain flexible and appropriate investment advice based on their individual investment goals and risk tolerance, and can make investments under fair competition.

[1402] (Application example 2)

[1403] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1404] Conventional investment systems lack a competitive method for users to obtain individually optimized investment advice, and do not provide investment advice that takes into account the user's emotions. This creates a problem in that the investment advice does not reflect the user's psychological state when making investment decisions. Furthermore, there is a lack of a method for optimizing and competitively obtaining investment educational content according to individual needs.

[1405] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1406] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through a competitive bidding process with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate the next piece of advice; means for recognizing the user's emotions and adjusting the investment advice in accordance with the emotions; and means for generating optimal educational content based on the user's emotional data and investment profile and providing the right to view the educational content through a bidding process. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and competitive optimization is also introduced into the method of providing educational content.

[1407] "Investment goal" refers to the specific profit or outcome that a user aims to achieve when making an investment.

[1408] "Risk tolerance" refers to the level of risk a user can accept in an investment.

[1409] "Artificial intelligence" refers to technology and programs that perform advanced calculations and analysis based on user input data to generate appropriate investment advice.

[1410] "Bidding" refers to a system in which multiple users submit amounts that indicate their willingness to pay to obtain specific investment advice, and the person who submits the highest amount receives the advice.

[1411] "Emotion recognition" is a technology that evaluates a user's psychological state and emotions through facial recognition technology and text analysis, and acquires that data.

[1412] "Educational Content" means educational information or instructional materials designed to enhance a user's investment knowledge or experience.

[1413] "Viewing rights" refers to the right of a specific user to view specific educational content.

[1414] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which users input their investment goals, risk tolerance, investment period, etc., and artificial intelligence generates optimal investment advice based on that information and provides that advice in a bidding format. It is also possible to recognize users' emotions and adjust the investment advice accordingly. Detailed embodiments of the system are described below.

[1415] The server first provides a means for users to input their investment goals and risk tolerance. Users input this information from devices such as smartphones or PCs and send it to the server. In this case, investment goals refer to the specific profits or results that the user aims to achieve, and risk tolerance refers to the level of risk the user is willing to accept in investments.

[1416] The server works with an artificial intelligence (AI) that generates investment advice based on the information sent by the user. This AI performs advanced calculations and analysis based on the data input by the user to generate appropriate investment advice.

[1417] Furthermore, an emotion engine for emotion recognition recognizes the user's emotions while the user is using the platform. Emotion recognition is a technology that evaluates the user's mental state and emotions through facial recognition technology and text analysis, and acquires the data. For this purpose, the smartphone's camera and various sensors are used. Specific examples include OpenCV (for facial recognition), TextBlob (text emotion analysis), and EmotionRecognitionEngine (for emotion recognition).

[1418] The server sends this emotional data to the investment buddy AI, which then generates optimal investment advice by taking into account both the investment profile and the emotional data. This generated advice is stored in a database and offered to users in a competitive bidding format. In a bidding format, multiple users submit the amount they are willing to pay to obtain a particular investment advice, and the person who submits the highest amount receives the advice.

[1419] Additionally, educational content is generated based on users' emotional data and investment profiles. Educational content refers to educational information and instructional materials to improve users' investment knowledge and experience. Viewing rights are also offered through a bidding process, and users participate by entering the amount they are willing to pay.

[1420] The server determines the highest bidder based on the bidding results and notifies the user. The highest bidder can then use the investment advice and educational content they have won to help them with their actual investment activities. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and introduces competitive optimization into the method of providing educational content.

[1421] For example, consider the following prompt:

[1422] "Recommend investment education content to a user with a medium risk tolerance who aims for a 10% annual return. The user's current emotion is 'anxious.' Based on this information, generate optimized investment education content and initiate a viewing rights bidding session tailored to that content."

[1423] In this way, the system of the present invention realizes the generation and provision of investment advice and educational content based on user input data and emotional data.

[1424] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1425] Step 1:

[1426] Users input their investment goals, risk tolerance, and investment period from a device such as a smartphone or PC. The device then sends this information to the server. The input here is text data, and the output is user profile data that is passed to the server.

[1427] Step 2:

[1428] The server passes the received user profile data to an artificial intelligence (Investment Buddy AI) that generates investment advice. The Investment Buddy AI generates an investment profile for the user based on this data and generates appropriate investment advice. The input here is the user profile data, and the output is investment advice.

[1429] Step 3:

[1430] While a user is using the platform, the device's camera and sensors are used to capture the user's facial expressions and input text in real time. The device then passes the collected data to an emotion engine, which analyzes the user's emotions. The input here is image and text data, and the output is emotion data.

[1431] Step 4:

[1432] The server sends the user's emotional data and investment advice to the investment buddy AI, which then regenerates optimized investment advice that takes the user's psychological state into account. The investment buddy AI then takes the user's emotional data into account and generates advice to reduce risk, etc. The input here is the emotional data and investment advice, and the output is the adjusted investment advice.

[1433] Step 5:

[1434] The server stores the generated adjusted investment advice in a database and provides it to users in the form of a bid. Users submit bids for the presented investment advice through their terminals. The bids are made through a digital payment system, and the output is bid amount data.

[1435] Step 6:

[1436] Once the bidding period ends, the server starts the process of determining the highest bidder. The input is the bid amount data of each user, and the output is the highest bidder information. The server notifies the highest bidder of the bidding result.

[1437] Step 7:

[1438] The highest bidder confirms the investment advice and reflects it in their actual investment activities. The terminal sends the investment actions taken by the user to the server. The input here is the user's investment action data, and the output is the updated investment data.

[1439] Step 8:

[1440] The server stores the user's investment action data in a database and uses it to generate investment advice from the next time onwards. The input here is the updated investment data, and the output is the optimized data used to generate the next investment advice.

[1441] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1442] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1443] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1444] [Fourth embodiment]

[1445] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1446] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1447] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1448] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1449] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1451] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1452] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1453] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1454] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1455] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1456] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1457] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1458] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[1459] User Registration and Login

[1460] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[1461] Collaboration with Investment Buddy AI

[1462] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1463] Generating and providing investment advice

[1464] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[1465] Launch of bidding system

[1466] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[1467] Determination and notification of highest bidder

[1468] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1469] Use and implementation of investment advice

[1470] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[1471] Specific examples

[1472] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[1473] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[1474] The processing flow will be explained below.

[1475] Step 1:

[1476] A user opens a website or application and clicks the login button with their PayPay account.

[1477] Step 2:

[1478] The terminal sends the entered user information to PayPay's authentication system.

[1479] Step 3:

[1480] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[1481] Step 4:

[1482] The terminal sends the received token to the server.

[1483] Step 5:

[1484] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[1485] Step 6:

[1486] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[1487] Step 7:

[1488] The terminal transmits the input investment profile information to the server.

[1489] Step 8:

[1490] The server generates an investment profile based on this information and sends the data to the Investment Buddy AI for collaboration.

[1491] Step 9:

[1492] Based on the investment profile received, the Investment Buddy AI generates appropriate investment advice (e.g., a portfolio of 70% stocks and 30% bonds) and returns it to the server.

[1493] Step 10:

[1494] The server stores the investment advice received from the investment buddy AI in a database.

[1495] Step 11:

[1496] The server notifies all users that new investment advice has been generated.

[1497] Step 12:

[1498] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[1499] Step 13:

[1500] The server initiates a bidding session for investment advice and sets a bidding period.

[1501] Step 14:

[1502] The user enters a bid amount for the displayed investment advice and makes a bid.

[1503] Step 15:

[1504] The terminal transmits the user's bid amount to the server.

[1505] Step 16:

[1506] The server compares it with the current maximum bid and updates the new maximum bid.

[1507] Step 17:

[1508] The server repeats this process until the bidding period ends.

[1509] Step 18:

[1510] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[1511] Step 19:

[1512] The server generates a notification to the highest bidder.

[1513] Step 20:

[1514] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[1515] Step 21:

[1516] The user reviews the investment advice they have received and decides whether to act on it.

[1517] Step 22:

[1518] The terminal provides an interface for the user to adjust the investment portfolio based on the investment advice.

[1519] Step 23:

[1520] Enter the investment actions taken by the user into the system.

[1521] Step 24:

[1522] The device sends the execution details to the server.

[1523] Step 25:

[1524] The server stores the investment data executed by the user in a database to help generate future advice.

[1525] Example 1

[1526] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1527] Conventional investment advice systems make it difficult for users to efficiently obtain and implement optimal investment advice. They also lack the ability to improve the quality of investment advice or provide individualized advice tailored to users' risk tolerance. Furthermore, they face the problem of being unable to consistently obtain investment advice competitively and track its effectiveness.

[1528] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1529] In this invention, the server includes means for inputting investment goals and risk tolerance determined by a user, means for linking with artificial intelligence that generates investment advice based on the input information, means for obtaining the investment advice through competitive bidding with other users, means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder, means for tracking the results of implementing the investment advice and using them to generate next advice, means for notifying the highest bidder, means for generating an investment profile, and means for saving the investment advice. This enables users to obtain optimal investment advice that takes into account their individual investment goals and risk tolerance through transparent and fair competition and to track its effectiveness.

[1530] "User" refers to an individual or corporation that uses the System to obtain investment advice.

[1531] "Investment goal" refers to the target investment return or asset growth that a user wishes to achieve.

[1532] "Risk tolerance" refers to the degree of risk a user is willing to accept in an investment.

[1533] "Input means" refers to an interface that allows a user to input information such as investment goals and risk tolerance.

[1534] "Artificial intelligence" refers to automated systems that use computer programs to generate investment advice based on user input data.

[1535] "Means for collaboration" refers to the means by which the server communicates with the artificial intelligence to generate investment advice.

[1536] "Means of obtaining through bidding" refers to the process by which a user obtains investment advice by making competitive bids with other users.

[1537] "Means for determining the highest bidder" refers to the means for identifying the bidder who offers the highest amount after the bidding period has ended.

[1538] "Means of providing investment advice" refers to the means of providing the generated investment advice to the highest bidder.

[1539] The "means for tracking execution results" refers to a means for recording the results of investment actions taken by a user based on investment advice, and for using the results to generate future advice.

[1540] "Means of Notification" means the method for sending notification to the highest bidder.

[1541] "Investment profile" refers to profile data generated based on information such as a user's investment goals, risk tolerance, and investment period.

[1542] "Means for storing" refers to a method for storing the generated investment advice in a storage device such as a database.

[1543] This invention relates to a system that enables users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which artificial intelligence generates investment advice based on the investment goals and risk tolerance entered by the user, and the advice is provided in a bidding format.

[1544] System Configuration

[1545] The system consists of the following hardware and software components:

[1546] User terminal (terminal): A device that can connect to the Internet (such as a PC, smartphone, or tablet).

[1547] Server: A server for hosting back-end systems, including databases, application servers, and artificial intelligence models.

[1548] Investment Buddy AI (artificial intelligence): A generative AI model that generates investment advice based on input data from users.

[1549] User Registration and Login

[1550] A user opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[1551] Collaboration with Investment Buddy AI

[1552] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1553] Generating and providing investment advice

[1554] The server stores the investment advice received from the Investment Buddy AI in a database. The generated advice is notified to all users, and the terminal prepares an interface to display the advice to the user.

[1555] Launch of bidding system

[1556] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[1557] Determination and notification of highest bidder

[1558] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1559] Use and implementation of investment advice

[1560] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[1561] Specific examples

[1562] For example, a user sets an investment goal of "aiming for a 10% annual return," inputs a risk tolerance of "medium," and an investment period of "5 years." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of "70% stocks, 30% bonds." The server records this advice in a database and starts a bidding session. For example, User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who then uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[1563] Prompt Sentence Examples

[1564] "Provide investment advice for those with a moderate risk tolerance, aiming for a 10% annual return."

[1565] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results of implementation, the accuracy of future advice can be improved.

[1566] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1567] Step 1:

[1568] A user accesses a website or application, opens the login screen, and enters their account information (username and password).

[1569] Input: Username, Password

[1570] Output: Login request

[1571] Specific operation: The user opens a login screen in a browser or application and enters their username and password in the designated form.

[1572] Step 2:

[1573] The device sends the user's login information (username and password) to the server.

[1574] Input: Username, Password

[1575] Output: HTTP POST request

[1576] Specific operation: The terminal sends the login information to the server using an HTTP POST request.

[1577] Step 3:

[1578] The server checks the login information against existing user information in the database, and if it matches, it issues a session ID as a successful authentication.

[1579] Input: Username, Password

[1580] Output: Authentication result (success / failure), session ID (if successful)

[1581] What happens: The server performs a database query to compare the login information with its records in the database, and if there is a match, generates a session ID.

[1582] Step 4:

[1583] The server returns the authentication result to the terminal, and if authentication is successful, the dashboard screen is displayed.

[1584] Input: Authentication result, session ID (if successful)

[1585] Output: Login success message, dashboard screen

[1586] Specific operation: The server returns the authentication result to the terminal as an HTTP response, and the terminal displays a login success message and the dashboard screen.

[1587] Step 5:

[1588] The user enters their investment goals, risk tolerance, and investment period.

[1589] Inputs: Investment goal, risk tolerance, investment period

[1590] Output: Investment information input request

[1591] Specific operation: The user enters information such as investment goals, risk tolerance, and investment period into a specified form.

[1592] Step 6:

[1593] The terminal transmits the user's investment information to the server.

[1594] Inputs: Investment goal, risk tolerance, investment period

[1595] Output: HTTP POST request

[1596] Specific operation: The terminal sends investment information to the server using an HTTP POST request.

[1597] Step 7:

[1598] The server generates an investment profile based on the user's investment information and sends that data to the investment buddy AI.

[1599] Inputs: Investment goal, risk tolerance, investment period

[1600] Output: Investment profile, API request

[1601] Specific operation: The server processes the investment information, creates an investment profile, and sends it to the investment buddy AI via an API request.

[1602] Step 8:

[1603] The Investment Buddy AI generates investment advice based on the investment profile received and sends the results back to the server.

[1604] Input: Investment Profile

[1605] Output: Investment advice

[1606] Specific operation: The Investment Buddy AI uses a generative AI model to analyze the investment profile, generate optimal investment advice, and send it back to the server via an API request.

[1607] Step 9:

[1608] The server stores the investment advice received from the investment buddy AI in a database and notifies the user.

[1609] Input: Investment advice

[1610] Output: Database records, advice notifications

[1611] Specific operation: The server stores the investment advice in a database and notifies all users of the advice.

[1612] Step 10:

[1613] The terminal provides an interface for displaying investment advice to the user.

[1614] Input:Advice Notice

[1615] Output: Advice display screen

[1616] Specific operation: The terminal generates and displays an HTML page for displaying the investment advice content on the user interface.

[1617] Step 11:

[1618] The server initiates a bidding session for investment advice and sets a bidding period.

[1619] Input: Investment advice

[1620] Output: Start of bidding session, bidding period setting

[1621] Specific operation: The server starts a bidding session and sends information setting the bidding period to the terminal.

[1622] Step 12:

[1623] The user enters the amount they would like to pay for the investment advice displayed and makes a bid.

[1624] Input: Bid amount

[1625] Output: Bid request

[1626] Specific operation: The user enters a bid amount and clicks the bid button.

[1627] Step 13:

[1628] The terminal transmits the user's bid amount to the server.

[1629] Input: Bid amount

[1630] Output: Send bid data

[1631] Specific operation: The terminal sends the bid data to the server using an HTTP POST request.

[1632] Step 14:

[1633] The server keeps updating the highest bids and checks the final results at the end of the bidding period.

[1634] Input: Bidding data

[1635] Output: Highest bid, final result

[1636] Specific operation: The server processes the bid data, stores it in the database, updates the highest bid, and confirms the final result at the end of the bidding period.

[1637] Step 15:

[1638] The server ultimately determines the highest bidder and records it in a database.

[1639] Input: Bid Results

[1640] Output: Highest bidder determination data

[1641] Specific Actions: The server identifies the highest bidder and records it in a database.

[1642] Step 16:

[1643] The terminal displays a notification to the highest bidder saying "Investment Advice Now Available."

[1644] Input: Highest bidder determination data

[1645] Output: Notification message

[1646] Specific operation: The terminal displays a notification to the highest bidder.

[1647] Step 17:

[1648] Review the investment advice you receive and adjust your investment portfolio accordingly.

[1649] Input: Investment advice

[1650] Output: Adjusted investment portfolio

[1651] Specific behavior: A user views investment advice and sets up a portfolio.

[1652] Step 18:

[1653] The terminal transmits the investment actions performed by the user to the server.

[1654] Input: Investment action data

[1655] Output: Investment action sending data

[1656] Specific operation: The terminal uses an HTTP POST request to send investment action data to the server.

[1657] Step 19:

[1658] The server stores the received investment action data in a database for use in later investment advice generation.

[1659] Input: Investment action submission data

[1660] Output: Database record

[1661] Specific operation: The server stores the received data in a database and uses it to generate advice next time.

[1662] (Application example 1)

[1663] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1664] In investment activities, there is a need for a means by which users can quickly and fairly obtain appropriate and effective investment advice. There is also a need for a mechanism to improve the accuracy of advice by reflecting the results of the implementation of competitively obtained advice in the generation of the next piece of advice. Furthermore, there is a need for a system that allows for real-time notifications of bidding information and investment advice, immediate implementation of the advice obtained, and feedback of the results.

[1665] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1666] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through competitive bidding with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate subsequent advice; means for notifying the user of the bidding information and advice in real time; and means for implementing the investment advice obtained by the user and providing feedback on the investment results. This allows users to quickly obtain and implement optimal investment advice under transparent and fair competition. Furthermore, by reflecting the results, the accuracy of subsequent advice can be improved.

[1667] A "user" is a person who uses the system to input investment goals and risk tolerance, competitively obtain investment advice, and then implement it.

[1668] An "investment goal" is a target value that indicates a specific outcome of an investment set by a user.

[1669] "Risk tolerance" indicates the degree of investment risk that a user can accept.

[1670] "Artificial intelligence" is a technology that generates optimal investment advice based on the investment goals and risk tolerance entered by the user.

[1671] "Bidding" is the process by which multiple users competitively offer prices to obtain investment advice.

[1672] A "high bidder" is a user who offers the highest price during the bidding process.

[1673] "Investment advice" is advice or suggestions generated by artificial intelligence to assist users in their investment activities.

[1674] "Execution results" is data showing the results and outcomes of the investment activities that the user carried out based on the investment advice.

[1675] "Real-time notification" is a function that instantly notifies users of bidding information and investment advice.

[1676] "Feedback" is a process of collecting the results of the user's investment advice and reflecting them in the next generation of advice.

[1677] MODE FOR CARRYING OUT THE INVENTION

[1678] This invention is a system that allows users to competitively obtain and implement investment advice generated based on their investment goals and risk tolerance. This system allows users to purchase investment advice through a bidding process, and provides feedback on the results of the implementation of the advice to help generate the next piece of advice.

[1679] System Program

[1680] To implement this system, the following programs are used:

[1681] Program processing and hardware / software used

[1682] 1. User Registration and Login:

[1683] Users log in to the electronic payment app and create their own investment account. Authentication is performed using Firebase Authentication, and user data is stored in the Firebase Realtime Database.

[1684] 2. Enter your investment goals and risk tolerance:

[1685] Users enter their investment goals and risk tolerance within the app, and this information is sent to a server via the electronic payment app's backend (e.g., Google Cloud Functions).

[1686] 3. Investment advice generation:

[1687] The server receives investment goals and risk tolerance, and works with an artificial intelligence model (e.g., GPT-4) to generate appropriate investment advice, which is then stored in a database.

[1688] 4. Operation of the bidding system:

[1689] Investment advice is provided to users in the form of a bid. The bidding process is run using the AWS Lambda reference architecture, and bid information is sent in real time via Firebase Cloud Messaging. Users enter their bid amount, and the user who submits the highest bid becomes the highest bidder.

[1690] 5. Providing Investment Advice:

[1691] Once bidding closes, the highest bidder will be offered investment advice, and this notification will also be sent in real time via Firebase Cloud Messaging.

[1692] 6. Implementation and feedback of investment advice:

[1693] The highest bidder will make an investment based on the investment advice and provide feedback on the results to the app. The investment results will be sent back to the server and used to generate the next investment advice.

[1694] Specific examples

[1695] For example, User A logs into an electronic payment app, sets an investment goal of "aiming for an 8% annual return," and enters a risk tolerance of "high." The Investment Buddy AI then proposes a portfolio consisting of 80% stocks and 20% cryptocurrencies. This advice is provided in a bidding format, with User B being the highest bidder at 4,000 yen and obtaining this advice. User B then executes the investment through the electronic payment app and provides feedback on the results to the app.

[1696] Prompt Sentence Examples

[1697] "The user's investment goal is an 8% annual return, and their risk tolerance is high. Please suggest an optimal portfolio."

[1698] This system allows users to quickly obtain and implement optimal investment advice through transparent and fair competition. Furthermore, by reflecting the results, the accuracy of future advice can be improved.

[1699] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1700] Step 1: User Registration and Login

[1701] The user accesses the electronic payment app and creates an account.

[1702] Input: Username, email address, password, and other authentication information

[1703] Data processing: Validate credentials using Firebase Authentication and create user accounts

[1704] Output: Authentication token and user account information stored in Firebase Realtime Database.

[1705] What happens: When a user logs into your app, the server verifies the credentials entered and starts a session.

[1706] Step 2: Enter your investment goals and risk tolerance

[1707] Users enter their investment goals and risk tolerance into a form within the app.

[1708] Inputs: Investment goal (e.g., 8% annual return), risk tolerance (e.g., high)

[1709] Data processing: Convert the input information into JSON format and send it to the server via Google Cloud Functions

[1710] Output: Investment profile stored on the server

[1711] Specific operation: A request is sent from the terminal to the server, and the server stores the investment goals and risk tolerance in a database.

[1712] Step 3: Investment advice generation

[1713] The server then works with a generative AI model (GPT-4) based on the investment profile it receives.

[1714] Input: Investment goals and risk tolerance stored on the server

[1715] Data processing: Send prompts to the generative AI model to generate appropriate investment advice

[1716] Output: Generated investment advice saved in a database

[1717] Specific operation: The server sends the prompt statement "The user's investment goal is an 8% annual return and their risk tolerance is high. Please suggest the optimal portfolio." to the generative AI model and saves the advice obtained as a response.

[1718] Step 4: Operate the bidding system

[1719] Investment advice is provided in a bidding format, with multiple users making competitive bids.

[1720] Input: Bid amounts from multiple users

[1721] Data Processing: Bid amounts updated in real time and track the highest bids

[1722] Output: Real-time updated bidding information, highest bidder

[1723] How it works: Bid information is processed in real time using AWS Lambda, and users are notified via Firebase Cloud Messaging whenever the highest bid is updated.

[1724] Step 5: Providing investment advice

[1725] After the bidding closes, investment advice will be provided to the highest bidder.

[1726] Input: Maximum bid amount and highest bidder information

[1727] Data processing: Send notifications to the highest bidder and provide investment advice

[1728] Output: Advice given

[1729] Specific operation: The server confirms that the bidding has ended and notifies the highest bidder via Firebase Cloud Messaging to provide investment advice.

[1730] Step 6: Implementation and feedback of investment advice

[1731] The highest bidder makes an investment based on the investment advice obtained and feeds back the results to the server.

[1732] Input: Investment execution results

[1733] Data processing: Investment execution results are saved in a database and used to generate next-time advice.

[1734] Output: Feedback investment result data

[1735] Specific operation: The user makes an investment based on the investment advice, and sends the results to the server via the app. The server stores the results and uses them to generate the next investment advice.

[1736] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1737] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system uses artificial intelligence to generate investment advice based on the investment goals and risk tolerance entered by the user, and provides that advice through a bidding process. It also incorporates an emotion engine that recognizes the user's emotions, making it possible to tailor the investment advice according to the user's emotions.

[1738] User Registration and Login

[1739] A user first opens a website or application and logs in with their account. This authentication can be done, for example, using a digital payment system. The server stores the user's information in a database and starts a session if the authentication is successful.

[1740] Collaboration with Investment Buddy AI

[1741] The user inputs their investment goals, risk tolerance, and investment period. The terminal sends this information to the server. The server generates an investment profile based on this information and sends the data to the investment buddy AI. The investment buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1742] Use of emotion engine

[1743] While the user is using the platform, the emotion engine recognizes the user's emotions. The emotion engine can use facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[1744] Generating and providing investment advice

[1745] The server sends the emotion data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates appropriate investment advice taking into account both the investment profile and the emotion data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[1746] Launch of bidding system

[1747] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process repeats until the bidding period ends.

[1748] Determination and notification of highest bidder

[1749] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1750] Use and implementation of investment advice

[1751] The user reviews the investment advice and adjusts their investment portfolio accordingly. The terminal transmits the investment actions taken by the user to the server, which stores this investment data in a database for future investment advice generation.

[1752] Specific examples

[1753] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this to the server, which passes the information to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen and User B bids 2,500 yen, and User B is ultimately determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate subsequent advice.

[1754] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[1755] The processing flow will be explained below.

[1756] Step 1:

[1757] A user opens a website or application and clicks the login button with their PayPay account.

[1758] Step 2:

[1759] The terminal sends the entered user information to PayPay's authentication system.

[1760] Step 3:

[1761] PayPay's authentication system verifies the authentication information, generates a token, and returns it to the terminal.

[1762] Step 4:

[1763] The terminal sends the received token to the server.

[1764] Step 5:

[1765] The server checks whether the token is valid, and if so, saves the user information in the database and starts a session.

[1766] Step 6:

[1767] The user enters their investment goals (e.g., "Aim for a 10% annual return"), risk tolerance, investment period, etc.

[1768] Step 7:

[1769] The terminal transmits this investment profile information to the server.

[1770] Step 8:

[1771] The server generates an investment profile based on the input information and sends that data to the Investment Buddy AI.

[1772] Step 9:

[1773] Based on the investment profile received, the Investment Buddy AI generates initial investment advice and returns it to the server.

[1774] Step 10:

[1775] The server stores the investment advice received from the investment buddy AI in a database.

[1776] Step 11:

[1777] The server notifies all users that new investment advice has been generated.

[1778] Step 12:

[1779] The terminal prepares an interface for displaying the contents of the investment advice to the user.

[1780] Step 13:

[1781] The emotion engine recognizes the user's emotions by capturing the user's face through the camera and analyzing the emotions.

[1782] Step 14:

[1783] The emotion engine analyzes the text entered by the user and evaluates its emotion.

[1784] Step 15:

[1785] The terminal transmits the user's emotion data to the server.

[1786] Step 16:

[1787] The server sends the emotional data to the investment buddy AI, instructing it to adjust its investment advice.

[1788] Step 17:

[1789] The investment buddy AI takes into account the emotional data, adjusts existing investment advice or generates new advice, and returns it to the server.

[1790] Step 18:

[1791] The server stores the updated investment advice in the database and notifies all users again.

[1792] Step 19:

[1793] The server initiates a bidding session for investment advice and sets a bidding period.

[1794] Step 20:

[1795] The user inputs the amount he or she wishes to pay for the displayed investment advice and makes a bid.

[1796] Step 21:

[1797] The terminal transmits the user's bid amount to the server.

[1798] Step 22:

[1799] The server compares it with the current maximum bid and updates the new maximum bid.

[1800] Step 23:

[1801] The server repeats this process until the bidding period ends.

[1802] Step 24:

[1803] After the bidding period ends, the server checks the final bidding status and determines the highest bidder.

[1804] Step 25:

[1805] The server generates a notification to the highest bidder.

[1806] Step 26:

[1807] The terminal displays a notification to the user, informing them that "Investment advice is now available."

[1808] Step 27:

[1809] The user reviews the investment advice they have received and decides whether to act on it.

[1810] Step 28:

[1811] The terminal provides an interface for adjusting the investment portfolio based on the investment advice.

[1812] Step 29:

[1813] Enter the investment actions taken by the user into the system.

[1814] Step 30:

[1815] The device sends the execution details to the server.

[1816] Step 31:

[1817] The server stores the investment data executed by the user in a database to help generate future advice.

[1818] Example 2

[1819] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1820] Current investment advice systems generate advice mechanically, taking into account a user's individual investment goals and risk tolerance while ignoring emotional influences. This makes it difficult to provide flexible and appropriate advice that reflects the user's emotional state. It is also difficult to obtain investment advice fairly through a competitive bidding system. This leads to problems such as a decline in the quality of investment advice and a decline in user satisfaction.

[1821] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1822] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by a user; means for linking with artificial intelligence that generates investment advice based on the input information; means for collecting and recognizing emotional data of the user; means for adjusting the investment advice taking the emotional data into consideration; means for obtaining the investment advice through competitive bidding with other users; means for determining a highest bidder based on the bidding results and providing the investment advice to the highest bidder; and means for tracking the results of the investment advice and using them to generate the next piece of advice. This makes it possible to provide flexible and appropriate investment advice that reflects the user's emotional state, and to obtain and implement investment advice through a fair bidding system.

[1823] "Investment goal" refers to the specific investment results or target values ​​that the user wants to achieve.

[1824] "Risk tolerance" indicates the range or level of risk that a user can tolerate.

[1825] "Artificial intelligence" refers to the technology that enables computer systems to mimic human intelligence in problem-solving and decision-making.

[1826] "Emotion data" refers to data that indicates the user's emotional state analyzed based on facial expressions, text input, etc.

[1827] "Investment Advice" means investment recommendations or instructions generated based on a user's investment goals, risk tolerance, and sentiment data.

[1828] A "bidding system" is a system in which multiple users conduct bidding procedures to competitively obtain investment advice.

[1829] A "highest bidder" is a user who submits the highest bid in the bidding system.

[1830] A "digital payment system" is a system for making monetary payments electronically.

[1831] "Investment Data" refers to data including investment actions taken by a user and past investment history.

[1832] An "investment profile" is comprehensive investment information that integrates a user's investment goals, risk tolerance, investment period, etc.

[1833] "Bidding results" refers to the results showing the bid amounts submitted in the bidding system and the final decision on bidders based on those bid amounts.

[1834] An "investment action" is a specific investment operation or behavior that a user performs based on investment advice.

[1835] MODE FOR CARRYING OUT THE INVENTION

[1836] The present invention relates to a system that enables users to competitively obtain effective investment advice and to efficiently carry out investment activities. A specific implementation method of this system will be described below.

[1837] User Registration and Login

[1838] A user opens a website or application and first logs in with their account. The user can be authenticated using a digital payment system. The server stores the user's information in a database and starts a session if authentication is successful.

[1839] Collaboration with Investment Buddy AI

[1840] Users input their investment goals, risk tolerance, and investment period into the terminal. The terminal sends this information to the server. The server generates an investment profile based on this data and sends that data to the Investment Buddy AI. The Investment Buddy AI generates investment advice based on the received investment profile and sends it back to the server.

[1841] Use of emotion engine

[1842] While the user is using the platform, the emotion engine recognizes the user's emotions. Specifically, it uses facial recognition technology and text analysis. The device captures video of the user's face and evaluates their emotions in real time. It can also analyze emotions from the text the user types.

[1843] Generating and providing investment advice

[1844] The server sends the emotional data obtained from the emotion engine to the investment buddy AI. The investment buddy AI generates optimal investment advice taking into account both the investment profile and the emotional data. The generated advice is stored in a database and notified to all users. The terminal prepares an interface to display the content to the user.

[1845] Launch of bidding system

[1846] The server starts a bidding session for investment advice and sets the bidding period. The user submits a bid by entering the amount they are willing to pay for the displayed investment advice. The terminal sends the user's bid to the server, which updates the highest bid. This process is repeated until the bidding period ends.

[1847] Determination and notification of highest bidder

[1848] When the bidding period ends, the server checks the final bidding results and determines the highest bidder, and the terminal displays a notification to the highest bidder saying "Investment advice now available."

[1849] Use and implementation of investment advice

[1850] The user checks the investment advice he / she has received and takes an investment action based on it. The terminal sends the investment action taken by the user to the server. The server stores this investment data in a database and uses it for future investment advice generation.

[1851] Specific examples

[1852] For example, a user sets an investment goal of "aiming for a 10% annual return" and enters their risk tolerance as "medium." The device sends this information to the server, which passes it on to the Investment Buddy AI. Based on this information, the Investment Buddy AI proposes a portfolio of 70% stocks and 30% bonds. At this time, the emotion engine evaluates the user's emotions, and if it detects "anxiety," for example, it generates advice to increase the proportion of bonds to reduce risk. The server records this advice in a database and starts a bidding session. User A bids 2,000 yen, and User B bids 2,500 yen, with User B ultimately being determined to be the highest bidder. The device notifies User B, who uses the advice to make an investment. The execution results are sent to the server and used to generate future advice.

[1853] This system allows users to obtain and implement optimal investment advice through transparent and fair competition. In addition, by tracking the results and sentiment data, the accuracy of future advice can be improved.

[1854] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1855] Step 1:

[1856] A user opens a website or application and registers. The user enters information such as their name, email address, and password. This information is collected as input data on the device and sent to the server. The server stores this data in a database, completing the user registration.

[1857] Step 2:

[1858] The user logs in with an existing account. The login information (email address, password) is sent from the terminal to the server. The server compares it with the information in the database and starts a session if authentication is successful. The input is the login information and the output is a session ID.

[1859] Step 3:

[1860] The user inputs their investment goal (e.g., 10% annual return), risk tolerance (e.g., medium), and investment period (e.g., 5 years) into the terminal. This information is sent from the terminal to the server. The server generates an investment profile for the user based on this data. The input is the investment goal, and the output is the investment profile.

[1861] Step 4:

[1862] The server sends the generated investment profile to the investment buddy AI. The investment buddy AI analyzes the investment profile and generates appropriate investment advice. The generated investment advice is sent back to the server. The investment profile is the input, and the investment advice is the output.

[1863] Step 5:

[1864] When a user uses the system, the device uses facial recognition technology to capture the user's facial expressions and analyze emotional data in real time. The text entered by the user is also analyzed. This emotional data is sent to the server. The input is facial recognition data and text data, and the output is emotional data.

[1865] Step 6:

[1866] The server provides the emotional data obtained from the emotion engine to the Investment Buddy AI. The Investment Buddy AI adjusts investment advice taking this emotional data into account. For example, if the user's emotion is judged to be "anxiety," advice to reduce risk is generated. The input is emotional data, and the output is adjusted investment advice.

[1867] Step 7:

[1868] The server stores the adjusted investment advice in a database and notifies all users of it. The terminal provides an interface that displays the investment advice to users. The input is the adjusted investment advice, and the output is notification information.

[1869] Step 8:

[1870] The server starts a bidding session for each investment advice. The user inputs the amount they are willing to pay, which is sent from their terminal to the server. The server compares each bid and updates the maximum bid. The input is the bid amount, and the output is the current maximum bid.

[1871] Step 9:

[1872] When the bidding period ends, the server checks the final bidding results and determines the highest bidder. The terminal displays a notification to the highest bidder saying "Investment advice is now available." The input is bidding data, and the output is the final bidding result and notification.

[1873] Step 10:

[1874] The user checks the investment advice they receive and takes an investment action based on it. The terminal sends the user's investment action to the server. The server stores this data in a database and uses it to generate future advice. The input is investment action data, and the output is updated database information.

[1875] Through the above processing steps, users can obtain flexible and appropriate investment advice based on their individual investment goals and risk tolerance, and can make investments under fair competition.

[1876] (Application example 2)

[1877] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1878] Conventional investment systems lack a competitive method for users to obtain individually optimized investment advice, and do not provide investment advice that takes into account the user's emotions. This creates a problem in that the investment advice does not reflect the user's psychological state when making investment decisions. Furthermore, there is a lack of a method for optimizing and competitively obtaining investment educational content according to individual needs.

[1879] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1880] In this invention, the server includes: means for inputting investment goals and risk tolerance determined by the user; means for linking with artificial intelligence that generates investment advice based on the input information; means for obtaining the investment advice through a competitive bidding process with other users; means for determining the highest bidder based on the bidding results and providing the investment advice to the highest bidder; means for tracking the results of implementing the investment advice and using them to generate the next piece of advice; means for recognizing the user's emotions and adjusting the investment advice in accordance with the emotions; and means for generating optimal educational content based on the user's emotional data and investment profile and providing the right to view the educational content through a bidding process. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and competitive optimization is also introduced into the method of providing educational content.

[1881] "Investment goal" refers to the specific profit or outcome that a user aims to achieve when making an investment.

[1882] "Risk tolerance" refers to the level of risk a user can accept in an investment.

[1883] "Artificial intelligence" refers to technology and programs that perform advanced calculations and analysis based on user input data to generate appropriate investment advice.

[1884] "Bidding" refers to a system in which multiple users submit amounts that indicate their willingness to pay to obtain specific investment advice, and the person who submits the highest amount receives the advice.

[1885] "Emotion recognition" is a technology that evaluates a user's psychological state and emotions through facial recognition technology and text analysis, and acquires that data.

[1886] "Educational Content" means educational information or instructional materials designed to enhance a user's investment knowledge or experience.

[1887] "Viewing rights" refers to the right of a specific user to view specific educational content.

[1888] This invention relates to a system that allows users to competitively obtain effective investment advice and efficiently conduct investment activities. This system has a mechanism in which users input their investment goals, risk tolerance, investment period, etc., and artificial intelligence generates optimal investment advice based on that information and provides that advice in a bidding format. It is also possible to recognize users' emotions and adjust the investment advice accordingly. Detailed embodiments of the system are described below.

[1889] The server first provides a means for users to input their investment goals and risk tolerance. Users input this information from devices such as smartphones or PCs and send it to the server. In this case, investment goals refer to the specific profits or results that the user aims to achieve, and risk tolerance refers to the level of risk the user is willing to accept in investments.

[1890] The server works with an artificial intelligence (AI) that generates investment advice based on the information sent by the user. This AI performs advanced calculations and analysis based on the data input by the user to generate appropriate investment advice.

[1891] Furthermore, an emotion engine for emotion recognition recognizes the user's emotions while the user is using the platform. Emotion recognition is a technology that evaluates the user's mental state and emotions through facial recognition technology and text analysis, and acquires the data. For this purpose, the smartphone's camera and various sensors are used. Specific examples include OpenCV (for facial recognition), TextBlob (text emotion analysis), and EmotionRecognitionEngine (for emotion recognition).

[1892] The server sends this emotional data to the investment buddy AI, which then generates optimal investment advice by taking into account both the investment profile and the emotional data. This generated advice is stored in a database and offered to users in a competitive bidding format. In a bidding format, multiple users submit the amount they are willing to pay to obtain a particular investment advice, and the person who submits the highest amount receives the advice.

[1893] Additionally, educational content is generated based on users' emotional data and investment profiles. Educational content refers to educational information and instructional materials to improve users' investment knowledge and experience. Viewing rights are also offered through a bidding process, and users participate by entering the amount they are willing to pay.

[1894] The server determines the highest bidder based on the bidding results and notifies the user. The highest bidder can then use the investment advice and educational content they have won to help them with their actual investment activities. This makes it possible to provide optimal investment advice that reflects the user's psychological state, and introduces competitive optimization into the method of providing educational content.

[1895] For example, consider the following prompt:

[1896] "Recommend investment education content to a user with a medium risk tolerance who aims for a 10% annual return. The user's current emotion is 'anxious.' Based on this information, generate optimized investment education content and initiate a viewing rights bidding session tailored to that content."

[1897] In this way, the system of the present invention realizes the generation and provision of investment advice and educational content based on user input data and emotional data.

[1898] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1899] Step 1:

[1900] Users input their investment goals, risk tolerance, and investment period from a device such as a smartphone or PC. The device then sends this information to the server. The input here is text data, and the output is user profile data that is passed to the server.

[1901] Step 2:

[1902] The server passes the received user profile data to an artificial intelligence (Investment Buddy AI) that generates investment advice. The Investment Buddy AI generates an investment profile for the user based on this data and generates appropriate investment advice. The input here is the user profile data, and the output is investment advice.

[1903] Step 3:

[1904] While a user is using the platform, the device's camera and sensors are used to capture the user's facial expressions and input text in real time. The device then passes the collected data to an emotion engine, which analyzes the user's emotions. The input here is image and text data, and the output is emotion data.

[1905] Step 4:

[1906] The server sends the user's emotional data and investment advice to the investment buddy AI, which then regenerates optimized investment advice that takes the user's psychological state into account. The investment buddy AI then takes the user's emotional data into account and generates advice to reduce risk, etc. The input here is the emotional data and investment advice, and the output is the adjusted investment advice.

[1907] Step 5:

[1908] The server stores the generated adjusted investment advice in a database and provides it to users in the form of a bid. Users submit bids for the presented investment advice through their terminals. The bids are made through a digital payment system, and the output is bid amount data.

[1909] Step 6:

[1910] Once the bidding period ends, the server starts the process of determining the highest bidder. The input is the bid amount data of each user, and the output is the highest bidder information. The server notifies the highest bidder of the bidding result.

[1911] Step 7:

[1912] The highest bidder confirms the investment advice and reflects it in their actual investment activities. The terminal sends the investment actions taken by the user to the server. The input here is the user's investment action data, and the output is the updated investment data.

[1913] Step 8:

[1914] The server stores the user's investment action data in a database and uses it to generate investment advice from the next time onwards. The input here is the updated investment data, and the output is the optimized data used to generate the next investment advice.

[1915] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1916] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1917] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1918] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1919] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1920] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1921] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1922] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1923] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1924] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1925] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1926] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1927] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1928] 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.

[1929] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1930] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1931] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1932] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1933] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1934] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1935] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1936] The following is further disclosed regarding the above embodiment.

[1937] (Claim 1)

[1938] a means for inputting user-defined investment goals and risk tolerance;

[1939] A means for linking with an artificial intelligence that generates investment advice based on the input information;

[1940] means for acquiring the investment advice through competitive bidding with other users;

[1941] means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder;

[1942] A means for tracking the results of the investment advice and using the results to generate next advice;

[1943] A system including:

[1944] (Claim 2)

[1945] 2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

[1946] (Claim 3)

[1947] The system of claim 1, wherein the artificial intelligence that generates the investment advice uses the user's past investment data.

[1948] "Example 1"

[1949] (Claim 1)

[1950] a means for inputting user-defined investment goals and risk tolerance;

[1951] A means for linking with an artificial intelligence that generates investment advice based on the input information;

[1952] means for acquiring the investment advice through competitive bidding with other users;

[1953] means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder;

[1954] A means for tracking the results of the investment advice and using the results to generate next advice;

[1955] means for notifying said highest bidder;

[1956] means for generating an investment profile;

[1957] a means of storing investment advice;

[1958] A system including:

[1959] (Claim 2)

[1960] 2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

[1961] (Claim 3)

[1962] The system of claim 1, wherein the artificial intelligence that generates the investment advice uses the user's past investment data.

[1963] "Application Example 1"

[1964] (Claim 1)

[1965] a means for inputting user-defined investment goals and risk tolerance;

[1966] A means for linking with an artificial intelligence that generates investment advice based on the input information;

[1967] means for acquiring the investment advice through competitive bidding with other users;

[1968] means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder;

[1969] A means for tracking the results of the investment advice and using the results to generate next advice;

[1970] means for notifying the bidding information and advice in real time;

[1971] A means for implementing the investment advice obtained by the user and providing feedback on the investment results;

[1972] A system including:

[1973] (Claim 2)

[1974] 2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

[1975] (Claim 3)

[1976] The system of claim 1, wherein the artificial intelligence that generates the investment advice uses the user's past investment data.

[1977] "Example 2: Combining Emotion Engines"

[1978] (Claim 1)

[1979] a means for inputting user-defined investment goals and risk tolerance;

[1980] A means for linking with an artificial intelligence that generates investment advice based on the input information;

[1981] means for collecting and recognizing emotion data of the user;

[1982] means for adjusting investment advice in consideration of said sentiment data;

[1983] means for acquiring the investment advice through competitive bidding with other users;

[1984] means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder;

[1985] A means for tracking the results of the investment advice and using the results to generate next advice;

[1986] A system including:

[1987] (Claim 2)

[1988] 2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

[1989] (Claim 3)

[1990] The system of claim 1, wherein the artificial intelligence that generates the investment advice uses the user's past investment data.

[1991] "Application example 2 when combining emotion engines"

[1992] (Claim 1)

[1993] a means for inputting user-defined investment goals and risk tolerance;

[1994] A means for linking with an artificial intelligence that generates investment advice based on the input information;

[1995] means for acquiring the investment advice in a competitive bidding format with other users;

[1996] means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder;

[1997] A means for tracking the results of the investment advice and using the results to generate next advice;

[1998] means for recognizing user emotions and adjusting investment advice in response to said emotions;

[1999] means for generating optimal educational content based on the user's emotional data and investment profile, and providing viewing rights for the educational content in a bidding format;

[2000] A system including:

[2001] (Claim 2)

[2002] 2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

[2003] (Claim 3)

[2004] The system of claim 1, wherein the artificial intelligence that generates the investment advice uses the user's past investment data. [Explanation of symbols]

[2005] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting user-defined investment goals and risk tolerance; A means for linking with an artificial intelligence that generates investment advice based on the input information; means for acquiring the investment advice through competitive bidding with other users; means for determining a highest bidder based on bidding results and providing the investment advice to the highest bidder; A means for tracking the results of the investment advice and using the results to generate next advice; A system including:

2. The system of claim 1, wherein the payment method used in the bidding is a digital payment system.

3. The system of claim 1 , wherein the artificial intelligence that generates the investment advice uses the user's past investment data.

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