System

Abstract

An object of a system according to an embodiment is to provide motivation for a user to specifically imagine a goal or a dream and act toward the goal or the dream.SOLUTION: A system includes a reception unit, a generation unit, an interaction unit, and an advertisement unit. The reception unit inputs a goal or a dream of the user. The generation part generates a future diary on the basis of the information input by the reception part. The dialogue unit performs communication between the user and the dialogue unit in the future based on the diary generated by the generation unit. The advertisement part inserts a company advertisement based on the information obtained by the interaction part.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies have had the problem of not providing users with a concrete image of their goals and dreams and motivating them to take action toward them.

[0005] The system according to the embodiment aims to provide users with a concrete image of their goals and dreams, and to motivate them to take action towards them. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a generation unit, a dialogue unit, and an advertising unit. The reception unit inputs the user's goals or dreams. The generation unit generates a future diary based on the information input by the reception unit. The dialogue unit communicates between the user and their future self based on the diary generated by the generation unit. The advertising unit inserts corporate advertisements based on the information obtained by the dialogue unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide users with a concrete image of their goals and dreams, and motivate them to take action towards them. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

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

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

[0028] (Example 1) A system according to an embodiment of the present invention allows a user to input goals and dreams, and generates a diary entry of a future in which those dreams have come true. This system allows the user to communicate with their future self, allowing them to recognize the happiness of their dream having come true. The system also allows the user to ask their future self about the process leading up to the realization of their dream and what they did. Furthermore, as a business, this system can earn advertising revenue by inserting corporate advertisements into the process required to achieve a goal. This allows the system to allow users to concretely imagine a future in which their dreams have come true, and increases their motivation to achieve that dream. Furthermore, since companies can earn advertising revenue, it has the potential to be a successful business.

[0029] A system according to an embodiment includes a reception unit, a generation unit, a dialogue unit, and an advertising unit. The reception unit inputs a user's goals or dreams. For example, the user can input a goal such as "I want to start my own company in five years." The generation unit uses a generation AI to generate a future diary entry based on the information input by the reception unit. For example, the generation AI imagines the situation of the user's future self based on the user's goals and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as "Today is the anniversary of the founding of my company, and I received many congratulatory messages from customers." The dialogue unit allows the user and their future self to communicate based on the diary entry generated by the generation unit. For example, the user can ask their future self a question such as "What preparations did you make to start a company?" The advertising unit inserts company advertisements based on the information obtained by the dialogue unit. For example, it can display advertisements for companies related to the process of starting a company, where necessary documents and procedures are explained. In this way, the system according to an embodiment allows the user to input the user's goals and dreams, generate a future diary entry based on the input, and communicate with the user and their future self.

[0030] The generation unit can generate a future diary entry based on the user's goals and dreams. The generation unit uses the generation AI to generate a future diary entry based on the user's goals and dreams. For example, the generation AI imagines what situation the user will be in in the future based on the user's goals, and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as, "Today is the anniversary of my company's founding, and I received congratulatory messages from many customers." In this way, by generating a future diary entry based on the user's goals and dreams, the user can imagine a concrete future.

[0031] The dialogue unit allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did. The dialogue unit allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did. For example, the user can ask their future self a question such as "What preparations did you make to start a company?" This allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did.

[0032] The advertising section can display corporate advertisements related to the process required to achieve a goal. The advertising section can display corporate advertisements related to the process required to achieve a goal. For example, in the process of establishing a company, it can display corporate advertisements related to the section explaining the necessary documents and procedures. In this way, advertising revenue can be earned by displaying corporate advertisements related to the process required to achieve a goal.

[0033] The generation unit may include an analysis unit that analyzes the user's past behavioral history or interests. The generation unit includes an analysis unit that analyzes the user's past behavioral history or interests. For example, the analysis unit may analyze the user's website browsing history, purchase history, social media activity, etc. to identify the user's interests. The analysis unit may also analyze the user's past behavioral patterns and predict their interests. This allows for the generation of more accurate future diaries by analyzing the user's past behavioral history and interests.

[0034] The advertising unit may include a protection unit that protects the user's privacy. For example, the protection unit may provide privacy protection measures such as data encryption, anonymization, and access restriction. This protects the user's privacy, allowing the user to use the system with peace of mind.

[0035] The reception unit can analyze the user's past input history of goals and dreams and select the optimal input method. The reception unit analyzes the user's past input history of goals and dreams and selects the optimal input method. For example, if the user has preferred text input in the past, text input can be preferentially suggested. Also, if the user has frequently used voice input in the past, voice input can be preferentially suggested. Furthermore, if the user has used images in the past to input their goals, image input can be preferentially suggested. In this way, the optimal input method can be suggested based on the user's past input history.

[0036] The reception unit can filter the input of goals and dreams based on the user's current living situation and areas of interest. The reception unit can filter the input of goals and dreams based on the user's current living situation and areas of interest. For example, if the user has goals related to their current job, related goals and dreams can be preferentially suggested. Also, if the user has goals related to their hobby, related goals and dreams can be preferentially suggested. Furthermore, if the user has goals related to their family life, related goals and dreams can be preferentially suggested. This makes it possible to suggest optimal goals and dreams based on the user's current living situation and areas of interest.

[0037] The reception unit can select the optimum input means depending on the input method of the user when inputting goals and dreams. The reception unit can select the optimum input means depending on the input method of the user when inputting goals and dreams. For example, if the user selects voice input, the goal or dream can be input using voice recognition technology. Also, if the user selects text input, the goal or dream can be input using keyboard input. Furthermore, if the user selects image input, the goal or dream can be input using image recognition technology. This makes it possible to provide the optimum input means depending on the input method of the user.

[0038] When inputting goals and dreams, the reception unit can prioritize inputting highly relevant goals and dreams in consideration of the user's geographical location information. When inputting goals and dreams, the reception unit prioritizes inputting highly relevant goals and dreams in consideration of the user's geographical location information. For example, if the user lives in an urban area, it can prioritize inputting goals and dreams that can be achieved in the city. Also, if the user lives in the countryside, it can prioritize inputting goals and dreams that can be achieved in a natural environment. Furthermore, if the user lives overseas, it can prioritize inputting goals and dreams that can be achieved in that area. This makes it possible to suggest optimal goals and dreams based on the user's geographical location information.

[0039] When a goal or dream is input, the reception unit can analyze the user's social media activity and input related goals or dreams. When a goal or dream is input, the reception unit can analyze the user's social media activity and input related goals or dreams. For example, goals or dreams related to themes that the user frequently mentions on social media can be input. Related goals or dreams can also be input based on the activities of the user's friends on social media. Furthermore, related goals or dreams can be input by analyzing the content of the user's social media posts. This makes it possible to suggest optimal goals and dreams based on the user's social media activity.

[0040] The reception unit can customize the input method by reflecting the user's past feedback when inputting goals or dreams. The reception unit customizes the input method by reflecting the user's past feedback when inputting goals or dreams. For example, if the user has preferred voice input in the past, the reception unit can preferentially suggest voice input. Also, if the user has frequently used text input in the past, the reception unit can preferentially suggest text input. Furthermore, if the user has used images in the past to input goals, the reception unit can preferentially suggest image input. This makes it possible to provide the optimal input method based on the user's past feedback.

[0041] When generating a future diary, the generation unit can adjust the level of detail of the diary based on the importance of the goal or dream. When generating a future diary, the generation unit adjusts the level of detail of the diary based on the importance of the goal or dream. For example, a detailed future diary can be generated for a goal or dream with high importance. Also, a concise future diary can be generated for a goal or dream with low importance. Furthermore, a future diary with an appropriate level of detail can be generated for a goal or dream with medium importance. This makes it possible to generate a future diary with an optimal level of detail depending on the importance of the goal or dream.

[0042] The generation unit can apply different generation algorithms depending on the category of goals or dreams when generating a future diary entry. The generation unit applies different generation algorithms depending on the category of goals or dreams when generating a future diary entry. For example, a business simulation algorithm can be applied to business-related goals. A health simulation algorithm can also be applied to health-related goals. Furthermore, a hobby simulation algorithm can also be applied to hobby-related goals. This makes it possible to apply the optimal generation algorithm depending on the category of goals or dreams.

[0043] When generating a future diary, the generation unit can improve the accuracy of generation by referring to the user's past behavioral history. When generating a future diary, the generation unit can improve the accuracy of generation by referring to the user's past behavioral history. For example, the generation unit can analyze the user's past behavioral history to make the content of the future diary more realistic. It can also construct a future diary scenario by referring to the user's past behavioral patterns. Furthermore, it can also generate a success scenario for the future diary based on the user's past successful experiences. This makes it possible to improve the accuracy of the future diary based on the user's past behavioral history.

[0044] The generation unit can determine the generation priority based on the submission time of the goal or dream when generating a future diary. The generation unit determines the generation priority based on the submission time of the goal or dream when generating a future diary. For example, if the submission time of the goal or dream is close, the goal or dream is generated with priority. Also, if the submission time of the goal or dream is far away, the goal or dream can be generated later. Furthermore, if the submission time of the goal or dream is medium, the goal or dream can be generated with moderate priority. In this way, a future diary can be generated with optimal priority based on the submission time of the goal or dream.

[0045] The generation unit can adjust the order of generation based on the relevance of goals and dreams when generating a future diary entry. The generation unit can adjust the order of generation based on the relevance of goals and dreams when generating a future diary entry. For example, highly relevant goals and dreams can be generated with priority. Also, goals and dreams with low relevance can be generated later. Furthermore, goals and dreams with medium relevance can be generated with moderate priority. In this way, future diaries can be generated in the optimal order based on the relevance of goals and dreams.

[0046] The generation unit can adjust the use of technical terminology when generating a future diary entry according to the user's level of expertise. The generation unit adjusts the use of technical terminology when generating a future diary entry according to the user's level of expertise. For example, if the user has technical expertise, a future diary entry that uses a lot of technical terminology can be generated. Also, if the user does not have technical expertise, a future diary entry that avoids technical terminology can be generated. Furthermore, if the user has medium level of expertise, a future diary entry that uses technical terminology moderately can be generated. This allows a future diary entry to be generated using optimal technical terminology according to the user's level of expertise.

[0047] The dialogue unit can adjust the level of detail of the dialogue based on the content of the dialogue with the future self during the dialogue. The dialogue unit can adjust the level of detail of the dialogue based on the content of the dialogue with the future self during the dialogue. For example, if the future self provides specific advice, a detailed dialogue can be conducted. Also, if the future self provides concise advice, a concise dialogue can be conducted. Furthermore, if the future self provides medium-level advice, a dialogue with a moderate level of detail can be conducted. This allows a dialogue with an optimal level of detail to be conducted based on the content of the dialogue with the future self.

[0048] The dialogue unit can improve the accuracy of the dialogue by referring to the user's past dialogue history during the dialogue. The dialogue unit can improve the accuracy of the dialogue by referring to the user's past dialogue history during the dialogue. For example, the dialogue unit can analyze the user's past dialogue history to make the dialogue content with the future self more realistic. It can also construct a dialogue scenario with the future self by referring to the user's past dialogue patterns. It can also generate a dialogue scenario with the future self based on the user's past successful experiences. This makes it possible to improve the accuracy of the dialogue based on the user's past dialogue history.

[0049] The dialogue unit can customize dialogue content based on the user's current living situation during dialogue. The dialogue unit customizes dialogue content based on the user's current living situation during dialogue. For example, if the user is busy with work, advice on efficient time management can be provided. Also, if the user places importance on family life, advice on enriching family life can be provided. Furthermore, if the user is interested in health, advice on health management can be provided. In this way, optimal dialogue content can be provided based on the user's current living situation.

[0050] The dialogue unit can determine the priority of dialogue based on the content of the dialogue with the future self during the dialogue. The dialogue unit can determine the priority of dialogue based on the content of the dialogue with the future self during the dialogue. For example, a dialogue that provides important advice can be given priority. A dialogue that provides simple advice can also be postponed. Furthermore, a dialogue that provides medium-level advice can be given moderate priority. This allows a dialogue to be carried out with optimal priority based on the content of the dialogue with the future self.

[0051] The dialogue unit can analyze the user's social media activity during a dialogue and provide related dialogue content. The dialogue unit can analyze the user's social media activity during a dialogue and provide related dialogue content. For example, the dialogue unit can provide dialogue content related to topics that the user frequently mentions on social media. The dialogue unit can also provide related dialogue content by referring to the activities of the user's friends on social media. Furthermore, the dialogue unit can analyze the content posted by the user on social media and provide related dialogue content. This makes it possible to provide optimal dialogue content based on the user's social media activity.

[0052] The dialogue unit can customize the dialogue content by reflecting the user's past feedback during the dialogue. The dialogue unit customizes the dialogue content by reflecting the user's past feedback during the dialogue. For example, the dialogue unit can preferentially suggest dialogue styles that the user has used favorably in the past. It can also eliminate dialogue styles that the user has avoided in the past. Furthermore, it can provide optimal dialogue content based on the user's past feedback. This makes it possible to provide optimal dialogue content based on the user's past feedback.

[0053] The advertising unit may adjust the level of detail of an advertisement based on the process required to achieve a goal when displaying the advertisement. The advertising unit may adjust the level of detail of an advertisement based on the process required to achieve a goal when displaying the advertisement. For example, an advertisement related to an important process may be displayed in detail. An advertisement related to a simple process may be displayed briefly. Furthermore, an advertisement related to a medium process may be displayed with moderate level of detail. This allows the advertisement to be displayed with an optimal level of detail based on the process required to achieve a goal.

[0054] The advertising unit can improve the accuracy of advertisements by referring to the user's past advertising history when displaying advertisements. The advertising unit can improve the accuracy of advertisements by referring to the user's past advertising history when displaying advertisements. For example, the advertising unit analyzes the user's past ad click history and displays relevant advertisements. It can also display advertisements that are likely to interest the user by referring to the user's past advertising viewing history. Furthermore, it can display optimal advertisements based on the user's past advertising response history. This makes it possible to display optimal advertisements based on the user's past advertising history.

[0055] The advertising unit can customize the advertisement content based on the user's current living situation when displaying the advertisement. The advertising unit customizes the advertisement content based on the user's current living situation when displaying the advertisement. For example, if the user is busy at work, an advertisement related to efficient time management can be displayed. Also, if the user places importance on family life, an advertisement related to enriching family life can be displayed. Furthermore, if the user is interested in health, an advertisement related to health management can be displayed. In this way, optimal advertisement content can be provided based on the user's current living situation.

[0056] The advertising unit can prioritize displaying highly relevant advertisements in consideration of the user's geographical location information when displaying advertisements. The advertising unit can prioritize displaying highly relevant advertisements in consideration of the user's geographical location information when displaying advertisements. For example, if the user lives in an urban area, advertisements for services available in the city can be prioritized. Also, if the user lives in a rural area, advertisements for services available in natural environments can be prioritized. Furthermore, if the user lives overseas, advertisements for services available in that area can be prioritized. This allows optimal advertisements to be displayed based on the user's geographical location information.

[0057] The advertising unit can analyze the user's social media activity and display relevant advertisements when displaying advertisements. The advertising unit can analyze the user's social media activity and display relevant advertisements when displaying advertisements. For example, advertisements related to topics that the user frequently mentions on social media can be displayed. Relevant advertisements can also be displayed based on the activities of the user's friends on social media. Furthermore, relevant advertisements can be displayed by analyzing the content of the user's social media posts. This makes it possible to display optimal advertisements based on the user's social media activity.

[0058] The advertising unit can customize the advertisement content by reflecting the user's past feedback when displaying the advertisement. The advertising unit customizes the advertisement content by reflecting the user's past feedback when displaying the advertisement. For example, the advertising unit can preferentially display the style of advertisement that the user liked to click on in the past. It can also eliminate the style of advertisement that the user avoided in the past. Furthermore, it can provide optimal advertisement content based on the user's past feedback. This makes it possible to provide optimal advertisement content based on the user's past feedback.

[0059] The analysis unit can optimize the analysis algorithm by referring to past analysis data during analysis. The analysis unit can optimize the analysis algorithm by referring to past analysis data during analysis. For example, the analysis unit selects an optimal analysis algorithm based on past analysis data. The accuracy of the analysis algorithm can also be improved by referring to past analysis data. Furthermore, the analysis unit can analyze past analysis data and adjust the parameters of the analysis algorithm. This makes it possible to apply the optimal analysis algorithm based on past analysis data.

[0060] During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. For example, if the user's behavioral history fluctuates frequently, the update frequency of the analysis data can be increased. Also, if the user's behavioral history is stable, the update frequency of the analysis data can be reduced. Furthermore, the change pattern of the user's behavioral history can be analyzed and an optimal update frequency can be set. This allows the analysis data to be updated at an optimal update frequency based on fluctuations in the user's behavioral history.

[0061] The analysis unit can analyze the user's past behavioral history and interests during analysis. The analysis unit analyzes the user's past behavioral history and interests during analysis. For example, the analysis unit analyzes the user's past behavioral history and identifies interests. It can also analyze the user's past behavioral patterns and predict interests. It can also analyze the user's interests based on the user's past search history. This allows for optimal analysis based on the user's past behavioral history and interests.

[0062] During analysis, the analysis unit can weight the analysis data based on the time when the goal or dream was submitted. During analysis, the analysis unit weights the analysis data based on the time when the goal or dream was submitted. For example, if the time when the goal or dream was submitted is close, a high weight can be assigned to the data. Also, if the time when the goal or dream was submitted is far away, a low weight can be assigned to the data. Furthermore, if the time when the goal or dream was submitted is medium, a moderate weight can be assigned to the data. This allows the analysis data to be processed with optimal weighting based on the time when the goal or dream was submitted.

[0063] The analysis unit can adjust the analysis algorithm by reflecting user feedback during analysis. The analysis unit can adjust the analysis algorithm by reflecting user feedback during analysis. For example, the analysis unit adjusts the parameters of the analysis algorithm based on user feedback. The analysis unit can also improve the accuracy of the analysis algorithm by reflecting user feedback. Furthermore, the analysis algorithm can be selected by referring to user feedback. This makes it possible to apply the optimal analysis algorithm based on user feedback.

[0064] During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. For example, if the user's behavioral history fluctuates frequently, the update frequency of the analysis data can be increased. Also, if the user's behavioral history is stable, the update frequency of the analysis data can be reduced. Furthermore, the change pattern of the user's behavioral history can be analyzed and an optimal update frequency can be set. This allows the analysis data to be updated at an optimal update frequency based on fluctuations in the user's behavioral history.

[0065] The protection unit can select the optimal protection method by referring to the user's past behavioral history when protecting privacy. The protection unit selects the optimal protection method by referring to the user's past behavioral history when protecting privacy. For example, the protection unit analyzes the user's past behavioral history and selects the optimal privacy protection method. The strength of privacy protection can also be adjusted by referring to the user's past behavioral patterns. Furthermore, the protection unit can suggest the optimal protection method based on the user's past privacy settings. This makes it possible to provide the optimal privacy protection method based on the user's past behavioral history.

[0066] The protection unit can customize protection measures based on the user's current living situation during privacy protection. The protection unit customizes protection measures based on the user's current living situation during privacy protection. For example, if the user is busy at work, efficient privacy protection measures can be provided. Also, if the user places importance on home life, privacy protection measures suitable for home life can be provided. Furthermore, if the user is interested in health, privacy protection measures suitable for health management can be provided. In this way, optimal privacy protection measures can be provided based on the user's current living situation.

[0067] The protection unit can customize the protection method by reflecting the user's past feedback during privacy protection. The protection unit customizes the protection method by reflecting the user's past feedback during privacy protection. For example, the protection unit can preferentially suggest privacy protection methods that the user has used favorably in the past. It can also eliminate privacy protection methods that the user has avoided in the past. Furthermore, it can provide the optimal privacy protection method based on the user's past feedback. In this way, it is possible to provide the optimal privacy protection method based on the user's past feedback.

[0068] The protection unit can select an optimal protection method in consideration of the user's geographical location information when protecting privacy. The protection unit selects an optimal protection method in consideration of the user's geographical location information when protecting privacy. For example, if the user lives in an urban area, a privacy protection method suitable for an urban environment can be provided. Also, if the user lives in a rural area, a privacy protection method suitable for a natural environment can be provided. Furthermore, if the user lives overseas, a privacy protection method suitable for that area can be provided. In this way, an optimal privacy protection method can be provided based on the user's geographical location information.

[0069] The protection unit can analyze the user's social media activities and suggest protection measures during privacy protection. The protection unit can analyze the user's social media activities and suggest protection measures during privacy protection. For example, the protection unit can suggest privacy protection measures related to topics that the user frequently mentions on social media. The protection unit can also suggest related privacy protection measures based on the activities of the user's friends on social media. Furthermore, the protection unit can analyze the content of the user's social media posts and suggest related privacy protection measures. This makes it possible to provide optimal privacy protection measures based on the user's social media activities.

[0070] The protection unit can customize the protection method by reflecting the user's past feedback during privacy protection. The protection unit customizes the protection method by reflecting the user's past feedback during privacy protection. For example, the protection unit can preferentially suggest privacy protection methods that the user has used favorably in the past. It can also eliminate privacy protection methods that the user has avoided in the past. Furthermore, it can provide the optimal privacy protection method based on the user's past feedback. In this way, it is possible to provide the optimal privacy protection method based on the user's past feedback.

[0071] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0072] The reception unit can analyze the user's input and suggest the skills and knowledge necessary to achieve their goals and dreams. For example, if a user inputs, "I want to start my own company in five years," the reception unit can suggest the legal knowledge and management skills necessary to start a company. If a user inputs, "I want to complete a marathon," the reception unit can suggest appropriate training plans and nutritional management knowledge. Furthermore, if a user inputs, "I want to learn a new language," the reception unit can suggest effective learning methods and resources. This allows the user to specifically grasp the skills and knowledge necessary to achieve their goals and dreams.

[0073] The generation unit can generate a timeline that specifically shows the steps to achieving the user's goals and dreams. For example, if the user inputs, "I want to start my own company in five years," the generation unit generates a timeline that shows each step until the company is founded. Also, if the user inputs, "I want to complete a marathon," a timeline that shows the progress of training can be generated. Furthermore, if the user inputs, "I want to learn a new language," a timeline that shows the progress of learning can be generated. This allows the user to grasp the specific steps toward achieving their goals and dreams.

[0074] The advertising department can suggest products and services related to the user's goals and dreams. For example, if a user inputs "I want to start a company," advertisements for business books and online courses can be displayed. If a user inputs "I want to complete a marathon," advertisements for running shoes and training wear can be displayed. Furthermore, if a user inputs "I want to learn a new language," advertisements for language learning apps and learning materials can be displayed. This allows users to learn about products and services that can help them achieve their goals and dreams.

[0075] The generation unit can generate a future diary entry by referring to the user's past successes. For example, the generation unit analyzes the user's past goals and successes and generates the future diary entry based on the results. The generation unit can also include encouraging messages in the future diary entry by taking into account the difficulties and setbacks the user has experienced in the past. Furthermore, the generation unit can make the contents of the future diary entry more realistic by referring to the user's past behavioral patterns. This allows the user to have a concrete image of how to achieve future goals and dreams by utilizing their past successes.

[0076] The reception unit analyzes the user's input and can suggest resources and support necessary to achieve their goals and dreams. For example, if a user inputs, "I want to start my own company in five years," the reception unit can suggest resources from business consultants and legal advisors. If a user inputs, "I want to complete a marathon," the reception unit can also suggest support from trainers and nutritionists. Furthermore, if a user inputs, "I want to learn a new language," the reception unit can also suggest resources from language schools and online tutors. This allows the user to specifically understand the resources and support necessary to achieve their goals and dreams.

[0077] The processing flow of the first embodiment will be briefly explained below.

[0078] Step 1: The reception unit inputs the user's goal or dream. For example, the user can input a goal such as "I want to start my own company in five years." Step 2: The generation unit uses the generation AI to generate a future diary entry based on the information entered by the reception unit. For example, the generation AI imagines the situation the user will be in in the future based on the user's goals, and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as, "Today is the anniversary of my company's founding, and I have received congratulatory messages from many customers." Step 3: The dialogue unit communicates between the user and their future self based on the diary created by the generation unit. For example, the user can ask their future self questions such as, "What preparations did you make to start a company?" Step 4: The advertising section inserts company advertisements based on the information obtained by the dialogue section. For example, in the process of establishing a company, advertisements for companies related to the required documents and procedures can be displayed.

[0079] (Example 2) A system according to an embodiment of the present invention allows a user to input goals and dreams, and generates a diary entry of a future in which those dreams have come true. This system allows the user to communicate with their future self, allowing them to recognize the happiness of their dream having come true. The system also allows the user to ask their future self about the process leading up to the realization of their dream and what they did. Furthermore, as a business, this system can earn advertising revenue by inserting corporate advertisements into the process required to achieve a goal. This allows the system to allow users to concretely imagine a future in which their dreams have come true, and increases their motivation to achieve that dream. Furthermore, since companies can earn advertising revenue, it has the potential to be a successful business.

[0080] A system according to an embodiment includes a reception unit, a generation unit, a dialogue unit, and an advertising unit. The reception unit inputs a user's goals or dreams. For example, the user can input a goal such as "I want to start my own company in five years." The generation unit uses a generation AI to generate a future diary entry based on the information input by the reception unit. For example, the generation AI imagines the situation of the user's future self based on the user's goals and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as "Today is the anniversary of the founding of my company, and I received many congratulatory messages from customers." The dialogue unit allows the user and their future self to communicate based on the diary entry generated by the generation unit. For example, the user can ask their future self a question such as "What preparations did you make to start a company?" The advertising unit inserts company advertisements based on the information obtained by the dialogue unit. For example, it can display advertisements for companies related to the process of starting a company, where necessary documents and procedures are explained. In this way, the system according to an embodiment allows the user to input the user's goals and dreams, generate a future diary entry based on the input, and communicate with the user and their future self.

[0081] The generation unit can generate a future diary entry based on the user's goals and dreams. The generation unit uses the generation AI to generate a future diary entry based on the user's goals and dreams. For example, the generation AI imagines what situation the user will be in in the future based on the user's goals, and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as, "Today is the anniversary of my company's founding, and I received congratulatory messages from many customers." In this way, by generating a future diary entry based on the user's goals and dreams, the user can imagine a concrete future.

[0082] The dialogue unit allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did. The dialogue unit allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did. For example, the user can ask their future self a question such as "What preparations did you make to start a company?" This allows the user to ask questions to their future self and ask about the process leading up to their dream coming true or what they did.

[0083] The advertising section can display corporate advertisements related to the process required to achieve a goal. The advertising section can display corporate advertisements related to the process required to achieve a goal. For example, in the process of establishing a company, it can display corporate advertisements related to the section explaining the necessary documents and procedures. In this way, advertising revenue can be earned by displaying corporate advertisements related to the process required to achieve a goal.

[0084] The generation unit may include an analysis unit that analyzes the user's past behavioral history or interests. The generation unit includes an analysis unit that analyzes the user's past behavioral history or interests. For example, the analysis unit may analyze the user's website browsing history, purchase history, social media activity, etc. to identify the user's interests. The analysis unit may also analyze the user's past behavioral patterns and predict their interests. This allows for the generation of more accurate future diaries by analyzing the user's past behavioral history and interests.

[0085] The advertising unit may include a protection unit that protects the user's privacy. For example, the protection unit may provide privacy protection measures such as data encryption, anonymization, and access restriction. This protects the user's privacy, allowing the user to use the system with peace of mind.

[0086] The reception unit can estimate the user's emotions and adjust the timing for inputting goals and dreams based on the estimated user emotions. The reception unit can estimate the user's emotions and adjust the timing for inputting goals and dreams based on the estimated user emotions. For example, if the user is feeling stressed, the reception unit can prompt the user to input goals and dreams during a time when the user can relax. Also, if the user is excited, the reception unit can utilize that emotion to prompt the user to input goals and dreams immediately. Furthermore, if the user is tired, the reception unit can prompt the user to input goals and dreams after a break. This allows the user to input goals and dreams at the optimal timing according to the user's emotions.

[0087] The reception unit can analyze the user's past input history of goals and dreams and select the optimal input method. The reception unit analyzes the user's past input history of goals and dreams and selects the optimal input method. For example, if the user has preferred text input in the past, text input can be preferentially suggested. Also, if the user has frequently used voice input in the past, voice input can be preferentially suggested. Furthermore, if the user has used images in the past to input their goals, image input can be preferentially suggested. In this way, the optimal input method can be suggested based on the user's past input history.

[0088] The reception unit can filter the input of goals and dreams based on the user's current living situation and areas of interest. The reception unit can filter the input of goals and dreams based on the user's current living situation and areas of interest. For example, if the user has goals related to their current job, related goals and dreams can be preferentially suggested. Also, if the user has goals related to their hobby, related goals and dreams can be preferentially suggested. Furthermore, if the user has goals related to their family life, related goals and dreams can be preferentially suggested. This makes it possible to suggest optimal goals and dreams based on the user's current living situation and areas of interest.

[0089] The reception unit can select the optimum input means depending on the input method of the user when inputting goals and dreams. The reception unit can select the optimum input means depending on the input method of the user when inputting goals and dreams. For example, if the user selects voice input, the goal or dream can be input using voice recognition technology. Also, if the user selects text input, the goal or dream can be input using keyboard input. Furthermore, if the user selects image input, the goal or dream can be input using image recognition technology. This makes it possible to provide the optimum input means depending on the input method of the user.

[0090] The reception unit can estimate the user's emotions and determine the priority of the goals and dreams to be input based on the estimated user's emotions. The reception unit can estimate the user's emotions and determine the priority of the goals and dreams to be input based on the estimated user's emotions. For example, if the user is feeling stressed, the reception unit can prioritize inputting goals and dreams that will help them relax. Also, if the user is excited, the reception unit can prioritize inputting challenging goals and dreams by utilizing that emotion. Furthermore, if the user is tired, the reception unit can prioritize inputting goals and dreams that are easy to achieve. In this way, the reception unit can prioritize inputting optimal goals and dreams according to the user's emotions.

[0091] When inputting goals and dreams, the reception unit can prioritize inputting highly relevant goals and dreams in consideration of the user's geographical location information. When inputting goals and dreams, the reception unit prioritizes inputting highly relevant goals and dreams in consideration of the user's geographical location information. For example, if the user lives in an urban area, it can prioritize inputting goals and dreams that can be achieved in the city. Also, if the user lives in the countryside, it can prioritize inputting goals and dreams that can be achieved in a natural environment. Furthermore, if the user lives overseas, it can prioritize inputting goals and dreams that can be achieved in that area. This makes it possible to suggest optimal goals and dreams based on the user's geographical location information.

[0092] When a goal or dream is input, the reception unit can analyze the user's social media activity and input related goals or dreams. When a goal or dream is input, the reception unit can analyze the user's social media activity and input related goals or dreams. For example, goals or dreams related to themes that the user frequently mentions on social media can be input. Related goals or dreams can also be input based on the activities of the user's friends on social media. Furthermore, related goals or dreams can be input by analyzing the content of the user's social media posts. This makes it possible to suggest optimal goals and dreams based on the user's social media activity.

[0093] The reception unit can customize the input method by reflecting the user's past feedback when inputting goals or dreams. The reception unit customizes the input method by reflecting the user's past feedback when inputting goals or dreams. For example, if the user has preferred voice input in the past, the reception unit can preferentially suggest voice input. Also, if the user has frequently used text input in the past, the reception unit can preferentially suggest text input. Furthermore, if the user has used images in the past to input goals, the reception unit can preferentially suggest image input. This makes it possible to provide the optimal input method based on the user's past feedback.

[0094] The generation unit can estimate the user's emotions and adjust the way the future diary entry is expressed based on the estimated user's emotions. The generation unit can estimate the user's emotions and adjust the way the future diary entry is expressed based on the estimated user's emotions. For example, if the user is relaxed, a future diary entry that progresses at a leisurely pace can be generated. If the user is in a hurry, a concise future diary entry that focuses on the main points can be generated. Furthermore, if the user is excited, a future diary entry that adds visually stimulating effects can be generated. In this way, a future diary entry can be generated using an optimal expression method according to the user's emotions.

[0095] When generating a future diary, the generation unit can adjust the level of detail of the diary based on the importance of the goal or dream. When generating a future diary, the generation unit adjusts the level of detail of the diary based on the importance of the goal or dream. For example, a detailed future diary can be generated for a goal or dream with high importance. Also, a concise future diary can be generated for a goal or dream with low importance. Furthermore, a future diary with an appropriate level of detail can be generated for a goal or dream with medium importance. This makes it possible to generate a future diary with an optimal level of detail depending on the importance of the goal or dream.

[0096] The generation unit can apply different generation algorithms depending on the category of goals or dreams when generating a future diary entry. The generation unit applies different generation algorithms depending on the category of goals or dreams when generating a future diary entry. For example, a business simulation algorithm can be applied to business-related goals. A health simulation algorithm can also be applied to health-related goals. Furthermore, a hobby simulation algorithm can also be applied to hobby-related goals. This makes it possible to apply the optimal generation algorithm depending on the category of goals or dreams.

[0097] When generating a future diary, the generation unit can improve the accuracy of generation by referring to the user's past behavioral history. When generating a future diary, the generation unit can improve the accuracy of generation by referring to the user's past behavioral history. For example, the generation unit can analyze the user's past behavioral history to make the content of the future diary more realistic. It can also construct a future diary scenario by referring to the user's past behavioral patterns. Furthermore, it can also generate a success scenario for the future diary based on the user's past successful experiences. This makes it possible to improve the accuracy of the future diary based on the user's past behavioral history.

[0098] The generation unit can estimate the user's emotions and adjust the length of the future diary entry based on the estimated user's emotions. The generation unit can estimate the user's emotions and adjust the length of the future diary entry based on the estimated user's emotions. For example, if the user is relaxed, a longer future diary entry can be generated. Also, if the user is in a hurry, a shorter future diary entry can be generated. Furthermore, if the user is excited, a future diary entry with a visually stimulating effect can be generated. In this way, a future diary entry with an optimal length can be generated according to the user's emotions.

[0099] The generation unit can determine the generation priority based on the submission time of the goal or dream when generating a future diary. The generation unit determines the generation priority based on the submission time of the goal or dream when generating a future diary. For example, if the submission time of the goal or dream is close, the goal or dream is generated with priority. Also, if the submission time of the goal or dream is far away, the goal or dream can be generated later. Furthermore, if the submission time of the goal or dream is medium, the goal or dream can be generated with moderate priority. In this way, a future diary can be generated with optimal priority based on the submission time of the goal or dream.

[0100] The generation unit can adjust the order of generation based on the relevance of goals and dreams when generating a future diary entry. The generation unit can adjust the order of generation based on the relevance of goals and dreams when generating a future diary entry. For example, highly relevant goals and dreams can be generated with priority. Also, goals and dreams with low relevance can be generated later. Furthermore, goals and dreams with medium relevance can be generated with moderate priority. In this way, future diaries can be generated in the optimal order based on the relevance of goals and dreams.

[0101] The generation unit can adjust the use of technical terminology when generating a future diary entry according to the user's level of expertise. The generation unit adjusts the use of technical terminology when generating a future diary entry according to the user's level of expertise. For example, if the user has technical expertise, a future diary entry that uses a lot of technical terminology can be generated. Also, if the user does not have technical expertise, a future diary entry that avoids technical terminology can be generated. Furthermore, if the user has medium level of expertise, a future diary entry that uses technical terminology moderately can be generated. This allows a future diary entry to be generated using optimal technical terminology according to the user's level of expertise.

[0102] The dialogue unit can estimate the user's emotions and adjust the dialogue expression method based on the estimated user's emotions. The dialogue unit can estimate the user's emotions and adjust the dialogue expression method based on the estimated user's emotions. For example, if the user is relaxed, the dialogue can be conducted in a calm tone. If the user is in a hurry, the dialogue can be brief and to the point. Furthermore, if the user is excited, the dialogue can be conducted in a lively tone. In this way, the dialogue can be conducted in the most appropriate expression method depending on the user's emotions.

[0103] The dialogue unit can adjust the level of detail of the dialogue based on the content of the dialogue with the future self during the dialogue. The dialogue unit can adjust the level of detail of the dialogue based on the content of the dialogue with the future self during the dialogue. For example, if the future self provides specific advice, a detailed dialogue can be conducted. Also, if the future self provides concise advice, a concise dialogue can be conducted. Furthermore, if the future self provides medium-level advice, a dialogue with a moderate level of detail can be conducted. This allows a dialogue with an optimal level of detail to be conducted based on the content of the dialogue with the future self.

[0104] The dialogue unit can improve the accuracy of the dialogue by referring to the user's past dialogue history during the dialogue. The dialogue unit can improve the accuracy of the dialogue by referring to the user's past dialogue history during the dialogue. For example, the dialogue unit can analyze the user's past dialogue history to make the dialogue content with the future self more realistic. It can also construct a dialogue scenario with the future self by referring to the user's past dialogue patterns. It can also generate a dialogue scenario with the future self based on the user's past successful experiences. This makes it possible to improve the accuracy of the dialogue based on the user's past dialogue history.

[0105] The dialogue unit can customize dialogue content based on the user's current living situation during dialogue. The dialogue unit customizes dialogue content based on the user's current living situation during dialogue. For example, if the user is busy with work, advice on efficient time management can be provided. Also, if the user places importance on family life, advice on enriching family life can be provided. Furthermore, if the user is interested in health, advice on health management can be provided. In this way, optimal dialogue content can be provided based on the user's current living situation.

[0106] The dialogue unit can estimate the user's emotions and adjust the length of the dialogue based on the estimated user's emotions. The dialogue unit can estimate the user's emotions and adjust the length of the dialogue based on the estimated user's emotions. For example, if the user is relaxed, the dialogue can be longer. If the user is in a hurry, the dialogue can be shorter. Furthermore, if the user is excited, the dialogue can be performed with visually stimulating effects added. This makes it possible to maintain the dialogue at an optimal length depending on the user's emotions.

[0107] The dialogue unit can determine the priority of dialogue based on the content of the dialogue with the future self during the dialogue. The dialogue unit can determine the priority of dialogue based on the content of the dialogue with the future self during the dialogue. For example, a dialogue that provides important advice can be given priority. A dialogue that provides simple advice can also be postponed. Furthermore, a dialogue that provides medium-level advice can be given moderate priority. This allows a dialogue to be carried out with optimal priority based on the content of the dialogue with the future self.

[0108] The dialogue unit can analyze the user's social media activity during a dialogue and provide related dialogue content. The dialogue unit can analyze the user's social media activity during a dialogue and provide related dialogue content. For example, the dialogue unit can provide dialogue content related to topics that the user frequently mentions on social media. The dialogue unit can also provide related dialogue content by referring to the activities of the user's friends on social media. Furthermore, the dialogue unit can analyze the content posted by the user on social media and provide related dialogue content. This makes it possible to provide optimal dialogue content based on the user's social media activity.

[0109] The dialogue unit can customize the dialogue content by reflecting the user's past feedback during the dialogue. The dialogue unit customizes the dialogue content by reflecting the user's past feedback during the dialogue. For example, the dialogue unit can preferentially suggest dialogue styles that the user has used favorably in the past. It can also eliminate dialogue styles that the user has avoided in the past. Furthermore, it can provide optimal dialogue content based on the user's past feedback. This makes it possible to provide optimal dialogue content based on the user's past feedback.

[0110] The advertising unit can estimate the user's emotions and adjust the advertisement display method based on the estimated user's emotions. The advertising unit can estimate the user's emotions and adjust the advertisement display method based on the estimated user's emotions. For example, if the user is relaxed, an advertisement can be displayed in a calm tone. If the user is in a hurry, an advertisement that is concise and to the point can be displayed. Furthermore, if the user is excited, an advertisement with a visually stimulating effect can be displayed. In this way, an advertisement can be displayed in an optimal display method according to the user's emotions.

[0111] The advertising unit may adjust the level of detail of an advertisement based on the process required to achieve a goal when displaying the advertisement. The advertising unit may adjust the level of detail of an advertisement based on the process required to achieve a goal when displaying the advertisement. For example, an advertisement related to an important process may be displayed in detail. An advertisement related to a simple process may be displayed briefly. Furthermore, an advertisement related to a medium process may be displayed with moderate level of detail. This allows the advertisement to be displayed with an optimal level of detail based on the process required to achieve a goal.

[0112] The advertising unit can improve the accuracy of advertisements by referring to the user's past advertising history when displaying advertisements. The advertising unit can improve the accuracy of advertisements by referring to the user's past advertising history when displaying advertisements. For example, the advertising unit analyzes the user's past ad click history and displays relevant advertisements. It can also display advertisements that are likely to interest the user by referring to the user's past advertising viewing history. Furthermore, it can display optimal advertisements based on the user's past advertising response history. This makes it possible to display optimal advertisements based on the user's past advertising history.

[0113] The advertising unit can customize the advertisement content based on the user's current living situation when displaying the advertisement. The advertising unit customizes the advertisement content based on the user's current living situation when displaying the advertisement. For example, if the user is busy at work, an advertisement related to efficient time management can be displayed. Also, if the user places importance on family life, an advertisement related to enriching family life can be displayed. Furthermore, if the user is interested in health, an advertisement related to health management can be displayed. In this way, optimal advertisement content can be provided based on the user's current living situation.

[0114] The advertising unit can estimate the user's emotions and determine the priority of advertisements based on the estimated user's emotions. The advertising unit can estimate the user's emotions and determine the priority of advertisements based on the estimated user's emotions. For example, if the user is relaxed, advertisements with calm tones can be preferentially displayed. Also, if the user is in a hurry, advertisements that are concise and to the point can be preferentially displayed. Furthermore, if the user is excited, advertisements with visually stimulating effects can be preferentially displayed. In this way, advertisements can be displayed with optimal priority according to the user's emotions.

[0115] The advertising unit can prioritize displaying highly relevant advertisements in consideration of the user's geographical location information when displaying advertisements. The advertising unit can prioritize displaying highly relevant advertisements in consideration of the user's geographical location information when displaying advertisements. For example, if the user lives in an urban area, advertisements for services available in the city can be prioritized. Also, if the user lives in a rural area, advertisements for services available in natural environments can be prioritized. Furthermore, if the user lives overseas, advertisements for services available in that area can be prioritized. This allows optimal advertisements to be displayed based on the user's geographical location information.

[0116] The advertising unit can analyze the user's social media activity and display relevant advertisements when displaying advertisements. The advertising unit can analyze the user's social media activity and display relevant advertisements when displaying advertisements. For example, advertisements related to topics that the user frequently mentions on social media can be displayed. Relevant advertisements can also be displayed based on the activities of the user's friends on social media. Furthermore, relevant advertisements can be displayed by analyzing the content of the user's social media posts. This makes it possible to display optimal advertisements based on the user's social media activity.

[0117] The advertising unit can customize the advertisement content by reflecting the user's past feedback when displaying the advertisement. The advertising unit customizes the advertisement content by reflecting the user's past feedback when displaying the advertisement. For example, the advertising unit can preferentially display the style of advertisement that the user liked to click on in the past. It can also eliminate the style of advertisement that the user avoided in the past. Furthermore, it can provide optimal advertisement content based on the user's past feedback. This makes it possible to provide optimal advertisement content based on the user's past feedback.

[0118] The analysis unit can estimate the user's emotions and select analysis data based on the estimated user's emotions. The analysis unit can estimate the user's emotions and select analysis data based on the estimated user's emotions. For example, if the user is relaxed, detailed analysis data can be selected. If the user is in a hurry, concise analysis data can be selected. Furthermore, if the user is excited, analysis data with added visually stimulating effects can be selected. This makes it possible to select optimal analysis data according to the user's emotions.

[0119] The analysis unit can optimize the analysis algorithm by referring to past analysis data during analysis. The analysis unit can optimize the analysis algorithm by referring to past analysis data during analysis. For example, the analysis unit selects an optimal analysis algorithm based on past analysis data. The accuracy of the analysis algorithm can also be improved by referring to past analysis data. Furthermore, the analysis unit can analyze past analysis data and adjust the parameters of the analysis algorithm. This makes it possible to apply the optimal analysis algorithm based on past analysis data.

[0120] During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. For example, if the user's behavioral history fluctuates frequently, the update frequency of the analysis data can be increased. Also, if the user's behavioral history is stable, the update frequency of the analysis data can be reduced. Furthermore, the change pattern of the user's behavioral history can be analyzed and an optimal update frequency can be set. This allows the analysis data to be updated at an optimal update frequency based on fluctuations in the user's behavioral history.

[0121] The analysis unit can analyze the user's past behavioral history and interests during analysis. The analysis unit analyzes the user's past behavioral history and interests during analysis. For example, the analysis unit analyzes the user's past behavioral history and identifies interests. It can also analyze the user's past behavioral patterns and predict interests. It can also analyze the user's interests based on the user's past search history. This allows for optimal analysis based on the user's past behavioral history and interests.

[0122] The analysis unit can estimate the user's emotions and adjust the frequency of analysis based on the estimated user's emotions. The analysis unit can estimate the user's emotions and adjust the frequency of analysis based on the estimated user's emotions. For example, if the user is relaxed, the frequency of analysis can be increased. Also, if the user is in a hurry, the frequency of analysis can be decreased. Furthermore, if the user is excited, analysis can be performed with visually stimulating effects. This makes it possible to perform analysis at an optimal frequency according to the user's emotions.

[0123] During analysis, the analysis unit can weight the analysis data based on the time when the goal or dream was submitted. During analysis, the analysis unit weights the analysis data based on the time when the goal or dream was submitted. For example, if the time when the goal or dream was submitted is close, a high weight can be assigned to the data. Also, if the time when the goal or dream was submitted is far away, a low weight can be assigned to the data. Furthermore, if the time when the goal or dream was submitted is medium, a moderate weight can be assigned to the data. This allows the analysis data to be processed with optimal weighting based on the time when the goal or dream was submitted.

[0124] The analysis unit can adjust the analysis algorithm by reflecting user feedback during analysis. The analysis unit can adjust the analysis algorithm by reflecting user feedback during analysis. For example, the analysis unit adjusts the parameters of the analysis algorithm based on user feedback. The analysis unit can also improve the accuracy of the analysis algorithm by reflecting user feedback. Furthermore, the analysis algorithm can be selected by referring to user feedback. This makes it possible to apply the optimal analysis algorithm based on user feedback.

[0125] During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. During analysis, the analysis unit can analyze fluctuations in the user's behavioral history and adjust the update frequency of the analysis data. For example, if the user's behavioral history fluctuates frequently, the update frequency of the analysis data can be increased. Also, if the user's behavioral history is stable, the update frequency of the analysis data can be reduced. Furthermore, the change pattern of the user's behavioral history can be analyzed and an optimal update frequency can be set. This allows the analysis data to be updated at an optimal update frequency based on fluctuations in the user's behavioral history.

[0126] The protection unit can estimate the user's emotion and adjust the privacy protection method based on the estimated user's emotion. The protection unit can estimate the user's emotion and adjust the privacy protection method based on the estimated user's emotion. For example, if the user is relaxed, standard privacy protection can be provided. Also, if the user is nervous, enhanced privacy protection can be provided. Furthermore, if the user is excited, privacy protection that visually provides a sense of security can be provided. In this way, an optimal privacy protection method can be provided according to the user's emotion.

[0127] The protection unit can select the optimal protection method by referring to the user's past behavioral history when protecting privacy. The protection unit selects the optimal protection method by referring to the user's past behavioral history when protecting privacy. For example, the protection unit analyzes the user's past behavioral history and selects the optimal privacy protection method. The strength of privacy protection can also be adjusted by referring to the user's past behavioral patterns. Furthermore, the protection unit can suggest the optimal protection method based on the user's past privacy settings. This makes it possible to provide the optimal privacy protection method based on the user's past behavioral history.

[0128] The protection unit can customize protection measures based on the user's current living situation during privacy protection. The protection unit customizes protection measures based on the user's current living situation during privacy protection. For example, if the user is busy at work, efficient privacy protection measures can be provided. Also, if the user places importance on home life, privacy protection measures suitable for home life can be provided. Furthermore, if the user is interested in health, privacy protection measures suitable for health management can be provided. In this way, optimal privacy protection measures can be provided based on the user's current living situation.

[0129] The protection unit can customize the protection method by reflecting the user's past feedback during privacy protection. The protection unit customizes the protection method by reflecting the user's past feedback during privacy protection. For example, the protection unit can preferentially suggest privacy protection methods that the user has used favorably in the past. It can also eliminate privacy protection methods that the user has avoided in the past. Furthermore, it can provide the optimal privacy protection method based on the user's past feedback. In this way, it is possible to provide the optimal privacy protection method based on the user's past feedback.

[0130] The protection unit can estimate the user's emotion and determine the priority of privacy protection based on the estimated user's emotion. The protection unit can estimate the user's emotion and determine the priority of privacy protection based on the estimated user's emotion. For example, if the user is relaxed, standard privacy protection can be provided preferentially. Also, if the user is nervous, enhanced privacy protection can be provided preferentially. Furthermore, if the user is excited, privacy protection that visually provides a sense of security can be provided preferentially. In this way, privacy protection can be provided with an optimal priority according to the user's emotion.

[0131] The protection unit can select an optimal protection method in consideration of the user's geographical location information when protecting privacy. The protection unit selects an optimal protection method in consideration of the user's geographical location information when protecting privacy. For example, if the user lives in an urban area, a privacy protection method suitable for an urban environment can be provided. Also, if the user lives in a rural area, a privacy protection method suitable for a natural environment can be provided. Furthermore, if the user lives overseas, a privacy protection method suitable for that area can be provided. In this way, an optimal privacy protection method can be provided based on the user's geographical location information.

[0132] The protection unit can analyze the user's social media activities and suggest protection measures during privacy protection. The protection unit can analyze the user's social media activities and suggest protection measures during privacy protection. For example, the protection unit can suggest privacy protection measures related to topics that the user frequently mentions on social media. The protection unit can also suggest related privacy protection measures based on the activities of the user's friends on social media. Furthermore, the protection unit can analyze the content of the user's social media posts and suggest related privacy protection measures. This makes it possible to provide optimal privacy protection measures based on the user's social media activities.

[0133] The protection unit can customize the protection method by reflecting the user's past feedback during privacy protection. The protection unit customizes the protection method by reflecting the user's past feedback during privacy protection. For example, the protection unit can preferentially suggest privacy protection methods that the user has used favorably in the past. It can also eliminate privacy protection methods that the user has avoided in the past. Furthermore, it can provide the optimal privacy protection method based on the user's past feedback. In this way, it is possible to provide the optimal privacy protection method based on the user's past feedback. === Hard Collateral 1-1 === Each of the multiple elements including the above-mentioned reception unit, generation unit, dialogue unit, and advertising unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the reception device 38 of the smart device 14 and inputs the user's goals and dreams. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a future diary using a generation AI. The dialogue unit is realized by the control unit 46A of the smart device 14 and allows the user and their future self to communicate based on the generated diary. The advertising unit is realized by the specific processing unit 290 of the data processing device 12 and inserts corporate advertisements based on information obtained by the dialogue unit. === Hard Collateral 1-2 === Each of the multiple elements, including the above-mentioned reception unit, generation unit, dialogue unit, and advertising unit, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the smart glasses 214 and inputs the user's goals and dreams. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a future diary entry using a generation AI. The dialogue unit is realized by the control unit 46A of the smart glasses 214 and allows the user and their future self to communicate based on the generated diary entry. The advertising unit is realized by the specific processing unit 290 of the data processing device 12 and inserts corporate advertisements based on information obtained by the dialogue unit. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, generation unit, dialogue unit, and advertising unit is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the headset-type terminal 314 and inputs the user's goals and dreams. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a future diary entry using a generation AI. The dialogue unit is realized by the control unit 46A of the headset-type terminal 314 and allows the user and their future self to communicate based on the generated diary entry. The advertising unit is realized by the specific processing unit 290 of the data processing device 12 and inserts corporate advertisements based on information obtained by the dialogue unit. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, generation unit, dialogue unit, and advertising unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the robot 414 and inputs the user's goals and dreams. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates a future diary using a generation AI. The dialogue unit is realized by the control unit 46A of the robot 414 and allows the user and their future self to communicate based on the generated diary. The advertising unit is realized by the specific processing unit 290 of the data processing device 12 and inserts corporate advertisements based on information obtained by the dialogue unit.

[0134] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0135] The reception unit can analyze the user's input and suggest the skills and knowledge necessary to achieve their goals and dreams. For example, if a user inputs, "I want to start my own company in five years," the reception unit can suggest the legal knowledge and management skills necessary to start a company. If a user inputs, "I want to complete a marathon," the reception unit can suggest appropriate training plans and nutritional management knowledge. Furthermore, if a user inputs, "I want to learn a new language," the reception unit can suggest effective learning methods and resources. This allows the user to specifically grasp the skills and knowledge necessary to achieve their goals and dreams.

[0136] The generation unit can generate a timeline that specifically shows the steps to achieving the user's goals and dreams. For example, if the user inputs, "I want to start my own company in five years," the generation unit generates a timeline that shows each step until the company is founded. Also, if the user inputs, "I want to complete a marathon," a timeline that shows the progress of training can be generated. Furthermore, if the user inputs, "I want to learn a new language," a timeline that shows the progress of learning can be generated. This allows the user to grasp the specific steps toward achieving their goals and dreams.

[0137] The dialogue unit allows the user to ask for emotional support from their future self. For example, if the user inputs "I feel anxious about starting a company," their future self can provide an encouraging message. If the user inputs "Marathon training is tough," their future self can provide a motivating message. Furthermore, if the user inputs "I feel like I'm giving up on learning a new language," their future self can provide a supportive message. This allows the user to work hard toward achieving their goals and dreams while receiving emotional support.

[0138] The advertising department can suggest products and services related to the user's goals and dreams. For example, if a user inputs "I want to start a company," advertisements for business books and online courses can be displayed. If a user inputs "I want to complete a marathon," advertisements for running shoes and training wear can be displayed. Furthermore, if a user inputs "I want to learn a new language," advertisements for language learning apps and learning materials can be displayed. This allows users to learn about products and services that can help them achieve their goals and dreams.

[0139] The generation unit can generate a future diary entry by referring to the user's past successes. For example, the generation unit analyzes the user's past goals and successes and generates the future diary entry based on the results. The generation unit can also include encouraging messages in the future diary entry by taking into account the difficulties and setbacks the user has experienced in the past. Furthermore, the generation unit can make the contents of the future diary entry more realistic by referring to the user's past behavioral patterns. This allows the user to have a concrete image of how to achieve future goals and dreams by utilizing their past successes.

[0140] The reception unit can estimate the user's emotions and customize the input content of goals and dreams based on the estimated user emotions. For example, if the user is feeling stressed, it can suggest relaxing goals and dreams. If the user is excited, it can also use that emotion to suggest challenging goals and dreams. Furthermore, if the user is tired, it can suggest goals and dreams that are easy to achieve. This allows the user to input optimal goals and dreams according to their emotions.

[0141] The generation unit can estimate the user's emotions and adjust the contents of future diary entries based on the estimated user emotions. For example, if the user is relaxed, a diary entry with calm content can be generated. If the user is excited, a diary entry with lively content can be generated. Furthermore, if the user is sad, a diary entry containing an encouraging message can be generated. In this way, a diary entry with optimal content can be generated according to the user's emotions.

[0142] The dialogue unit can estimate the user's emotions and adjust the tone of the dialogue based on the estimated user's emotions. For example, if the user is relaxed, the dialogue can be conducted in a calm tone. If the user is excited, the dialogue can be conducted in a lively tone. Furthermore, if the user is sad, the dialogue can be conducted in a comforting tone. This allows the dialogue to be conducted in an optimal tone depending on the user's emotions.

[0143] The advertising unit can estimate the user's emotions and adjust the content of the advertisement based on the estimated user's emotions. For example, if the user is relaxed, an advertisement with a calm tone can be displayed. If the user is excited, a visually stimulating advertisement can be displayed. Furthermore, if the user is sad, an advertisement containing an encouraging message can be displayed. In this way, it is possible to display an advertisement with optimal content according to the user's emotions.

[0144] The reception unit analyzes the user's input and can suggest resources and support necessary to achieve their goals and dreams. For example, if a user inputs, "I want to start my own company in five years," the reception unit can suggest resources from business consultants and legal advisors. If a user inputs, "I want to complete a marathon," the reception unit can also suggest support from trainers and nutritionists. Furthermore, if a user inputs, "I want to learn a new language," the reception unit can also suggest resources from language schools and online tutors. This allows the user to specifically understand the resources and support necessary to achieve their goals and dreams.

[0145] The processing flow of the second embodiment will be briefly explained below.

[0146] Step 1: The reception unit inputs the user's goal or dream. For example, the user can input a goal such as "I want to start my own company in five years." Step 2: The generation unit uses the generation AI to generate a future diary entry based on the information entered by the reception unit. For example, the generation AI imagines the situation the user will be in in the future based on the user's goals, and generates a diary entry that describes that situation in detail. For example, the generation AI generates a diary entry with content such as, "Today is the anniversary of my company's founding, and I have received congratulatory messages from many customers." Step 3: The dialogue unit communicates between the user and their future self based on the diary created by the generation unit. For example, the user can ask their future self questions such as, "What preparations did you make to start a company?" Step 4: The advertising section inserts company advertisements based on the information obtained by the dialogue section. For example, in the process of establishing a company, advertisements for companies related to the required documents and procedures can be displayed.

[0147] 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.

[0148] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0149] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0150] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0151] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0152] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0153] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0154] 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.

[0155] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0157] 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.

[0158] 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.

[0159] 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.

[0160] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0161] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0162] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0163] 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.

[0164] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0165] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0166] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0167] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0168] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0169] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0170] 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.

[0171] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0172] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0173] 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.

[0174] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0175] 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.

[0176] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0177] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0178] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0179] 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.

[0180] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0181] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0182] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0183] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0184] 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.

[0185] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0186] 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.

[0187] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0188] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0189] 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.

[0190] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0191] 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.

[0192] 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.

[0193] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0194] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0195] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0196] 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.

[0197] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0198] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0199] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0200] 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.

[0201] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0202] 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.

[0203] 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).

[0204] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0205] 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."

[0206] 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.

[0207] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0212] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0213] 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.

[0214] 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.

[0215] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0216] 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, in order to avoid confusion and to 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.

[0217] 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.

[0218] [Explanation of symbols]

[0219] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit for inputting a user's goals or dreams; a generation unit that generates a future diary based on the information input by the reception unit; a dialogue unit in which the user and his / her future self communicate with each other based on the diary created by the creation unit; an advertising unit that inserts a corporate advertisement based on the information obtained by the dialogue unit. A system characterized by:

2. The generation unit Generate future diary entries based on the user's goals and dreams 2. The system of claim 1.

3. The dialogue unit Users can ask their future selves questions and ask about the process or actions they took to make their dreams come true.

2. The system of claim 1.

4. The advertising department Displaying company advertisements related to the process required to achieve your goals 2. The system of claim 1.

5. The generation unit Equipped with an analysis unit that analyzes the user's past behavioral history or interests 2. The system of claim 1.

6. The advertising department Equipped with a protection section to protect user privacy 2. The system of claim 1.

7. The reception unit Estimate the user's emotions and adjust the timing of inputting goals and dreams based on the estimated emotions.

2. The system of claim 1.

8. The reception unit Analyze the user's past input history of goals and dreams and select the optimal input method 2. The system of claim 1.

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