System

Abstract

An object of the system according to the embodiment is to clarify individual desires at the end of life and make a selection while enjoying the desires.SOLUTION: A system includes a selection unit, a generation unit, and a proposal unit. The selection unit selects a desired content from the options for each category. The generation unit creates a my ending wish based on the wish content selected by the selection unit. The proposal unit proposes a new article or service based on the my ending wish created by the creation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, it was difficult to clarify individual wishes and make enjoyable choices when it came to end-of-life planning.

[0005] The system of the embodiment aims to clarify individual wishes in end-of-life planning and enable people to make choices while having fun. [Means for solving the problem]

[0006] The system according to the embodiment includes a selection unit, a generation unit, and a suggestion unit. The selection unit selects desired content from options for each category. The generation unit creates a My Ending wish based on the desired content selected by the selection unit. The suggestion unit suggests a new product or service based on the My Ending wish created by the generation unit. [Effects of the Invention]

[0007] The system of the embodiment allows people to clarify their individual wishes when preparing for the end of their lives and make choices while having fun. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The end-of-life planning wish tool according to an embodiment of the present invention is a system that allows users to clarify their ending road while enjoying the process, including their wishes. This system allows users to select their wishes from options in each category, create their own personalized ending wishes, and a generating AI will suggest new products and services. This allows users to clarify their ending road while enjoying the process, including their wishes, and entrust their wishes to future generations.

[0029] An end-of-life planning preference tool according to an embodiment includes a selection unit, a generation unit, and a suggestion unit. The selection unit selects desired content from options for each category. For example, a user can clarify their wishes by selecting options from categories such as funeral style, inheritance distribution, and memorial service. The generation unit creates a personalized ending preference based on the desired content selected by the selection unit. For example, the generation AI organizes and documents the desired content based on the desired content selected by the user. The suggestion unit suggests new products or services based on the personalized ending preference created by the generation unit. For example, the generation AI provides information and services regarding natural burials based on the desired content of the user. As a result, the end-of-life planning preference tool according to an embodiment allows a user to clarify their desired content while enjoying the road to their end, and entrust their wishes to future generations.

[0030] The selection unit allows the generation AI to propose individually customized options based on the user's past selection history. For example, the selection unit stores the user's past selections in a database, and the generation AI proposes new options based on that history. For example, a user who previously requested a simple funeral will be presented with new options related to simple funerals. The selection unit also analyzes the user's past selection history, and the generation AI proposes individually customized options. For example, a user who previously requested a natural burial will be proposed with new services and options related to natural burials. The selection unit also allows the generation AI to propose individually customized options in real time based on the user's selection history. For example, a user who previously made a selection after discussing it with the entire family will be presented with new options that the whole family can enjoy. In this way, by proposing customized options based on the user's past selection history, it is possible to provide more personalized preferences.

[0031] The selection unit can analyze the user's lifestyle and values, and the generation AI can provide options based on that. For example, the selection unit collects the user's lifestyle and values ​​from questionnaires and profile information, and the generation AI suggests options based on that. For example, an eco-conscious user can be presented with environmentally friendly funeral options. The selection unit can also analyze the user's lifestyle and values, and the generation AI can provide options based on that. For example, a user who values ​​time with family can be suggested a memorial service that the entire family can participate in. The selection unit can also analyze the user's values, and the generation AI can provide options based on that. For example, a user who values ​​tradition can be presented with options based on traditional ceremonies and customs. This allows the user to select more appropriate options by providing options based on their lifestyle and values.

[0032] The generation unit allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays a scenario of the funeral flow or estate distribution in diagrams or charts. The generation unit also allows the generation AI to create a detailed scenario based on the user's selections and present it visually. For example, the generation unit visually displays a memorial service schedule and attendee list. The generation unit also allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays an overall picture of the desired ending in mind map format. In this way, by visually presenting a detailed scenario based on the user's selections, the user can more easily understand their wishes.

[0033] The generation unit allows the generation AI to automatically generate relevant legal documents and procedures based on the user's selections. The generation unit, for example, automatically generates relevant legal documents and procedures based on the user's selections. For example, it automatically generates a will or an estate distribution contract. The generation unit also simplifies procedures by having the generation AI automatically generate relevant legal documents based on the user's selections. For example, it automatically generates documents necessary for funeral arrangements. The generation unit also automatically generates relevant legal documents and procedures based on the user's selections. For example, it automatically generates a memorial service contract and participant list. This simplifies procedures by automatically generating relevant legal documents and procedures based on the user's selections.

[0034] The suggestion unit allows the generation AI to automatically research and suggest new related products and services based on the user's selections. For example, the suggestion unit automatically researches and suggests new related products and services based on the user's selections. For example, the latest natural burial services are suggested to a user who desires a natural burial. The suggestion unit also allows the generation AI to research and suggest new products and services based on the user's selections. For example, the latest eco-funeral services are suggested to a user who desires eco-friendly funeral options. The suggestion unit also allows the generation AI to automatically research and suggest new related products and services based on the user's selections. For example, the latest family-friendly services are suggested to a user who desires a memorial service that the whole family can enjoy. In this way, new products and services are researched and suggested based on the user's selections, thereby providing new options that meet the user's wishes.

[0035] The suggestion unit allows the generation AI to propose new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a memorial service using virtual reality. The suggestion unit may also propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a funeral service that can be attended online. The suggestion unit may also propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose an inheritance distribution support service using AI. This allows the user to be provided with the latest options by proposing new services that incorporate market trends and the latest technology.

[0036] The suggestion unit can incorporate elements related to the user's hobbies and interests into suggestions for new products and services. For example, the suggestion unit incorporates elements related to the user's hobbies and interests into suggestions for new products and services. For example, for a user who likes music, the suggestion unit suggests a memorial service that plays favorite songs. The suggestion unit also takes the user's hobbies and interests into consideration and incorporates entertainment elements into suggestions for new products and services. For example, for a user who likes movies, the suggestion unit suggests a service that recreates favorite movie scenes. The suggestion unit also incorporates elements related to the user's interests into suggestions for new products and services. For example, for a user who likes traveling, the suggestion unit suggests memorial services at travel destinations. In this way, by incorporating elements related to the user's hobbies and interests into suggestions, it is possible to provide the user with attractive options.

[0037] The suggestion unit can have the AI ​​generator propose new products and services based on different cultures and religions, enabling selection from a global perspective. For example, the suggestion unit proposes services based on religious rituals such as Buddhism, Christianity, and Islam. The suggestion unit can also propose funeral and memorial services from different cultures as new products and services, allowing users to select from a global perspective. For example, the suggestion unit can propose services based on Mexico's "Day of the Dead" and Japan's "Obon." The suggestion unit can also propose new products and services based on different religions and cultures, allowing users to choose from a variety of options. For example, the suggestion unit can propose Hindu cremation ceremonies and Jewish funeral ceremonies. This allows the system to provide users with a variety of options by proposing new products and services based on different cultures and religions.

[0038] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0039] The selection unit can also monitor the user's health condition and suggest appropriate options based on that. For example, if the user is elderly, it will suggest a funeral style that places less physical strain on the user. The selection unit also analyzes the user's health condition in real time and provides appropriate options. For example, if the user has a chronic illness, it will suggest a memorial service that takes that chronic illness into consideration. The selection unit also takes the user's health condition into consideration, and the generation AI suggests options that take health into consideration. For example, if the user is undergoing rehabilitation, it will suggest a memorial service at a rehabilitation facility. This allows the user to select more appropriate options by providing options based on their health condition.

[0040] The selection unit can also have the generation AI suggest memorial services at travel destinations based on the user's past travel history. For example, it can suggest funeral or memorial services at places the user has visited in the past. The selection unit can also analyze the user's travel history, and the generation AI can suggest new options at travel destinations. For example, it can suggest memorial services at tourist spots the user likes. The selection unit can also have the generation AI suggest memorial services at travel destinations in real time based on the user's travel history. For example, it can suggest natural burials at places the user has visited in the past. This allows the user to provide more personalized desired services by suggesting customized options based on their travel history.

[0041] The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes music, the selection unit can present a funeral option that plays their favorite songs. The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes movies, the selection unit can suggest a memorial service that recreates a scene from their favorite movie. The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes traveling, the selection unit can suggest a memorial service at their travel destination. This allows the user to select more appropriate options by providing options based on their hobbies and interests.

[0042] The generation unit can also have the generation AI create a scenario that incorporates relevant cultural background and historical elements based on the user's selections. For example, the generation unit creates a scenario that explains the historical background related to the funeral style selected by the user. The generation unit also has the generation AI create a scenario that incorporates cultural background and historical elements based on the user's selections and visually present it. For example, the generation unit displays cultural elements related to the memorial service selected by the user in diagrams and charts. The generation unit also has the generation AI create a scenario that incorporates cultural background and historical elements based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays an overall picture of the ending desired by the user, along with the cultural background, in mind map format. This makes it easier for the user to understand their wishes by visually presenting a scenario that incorporates cultural background and historical elements based on the user's selections.

[0043] The suggestion unit can also have the generation AI automatically research and suggest new related products and services based on the user's selections. For example, it can suggest the latest services related to the funeral style selected by the user. The suggestion unit can also have the generation AI automatically research and suggest new products and services based on the user's selections. For example, it can suggest the latest options related to the memorial service selected by the user. The suggestion unit can also automatically research and suggest new products and services based on the user's selections. For example, it can suggest the latest services related to the ending wishes selected by the user. In this way, by researching and suggesting new products and services based on the user's selections, it is possible to provide new options that match the user's wishes.

[0044] The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest services that incorporate the latest technology for the funeral style selected by the user. The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest options that incorporate the latest technology for the memorial service selected by the user. The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest services that incorporate the latest technology for the ending preference selected by the user. In this way, by suggesting new services that incorporate market trends and the latest technology, the user can be provided with the latest options.

[0045] The processing flow of the first embodiment will be briefly explained below.

[0046] Step 1: The selection unit selects desired content from options for each category. For example, users can select options from categories such as funeral style, distribution of inheritance, and memorial service to clarify their wishes. Step 2: The generation unit creates a personalized ending based on the desired content selected by the selection unit. For example, the generation AI organizes and documents the desired content based on the desired content selected by the user. Step 3: The suggestion unit proposes new products or services based on the My Ending wishes created by the generation unit. For example, the generation AI may provide information and services related to natural burials based on the user's wishes.

[0047] (Example 2) The end-of-life planning wish tool according to an embodiment of the present invention is a system that allows users to clarify their ending road while enjoying the process, including their wishes. This system allows users to select their wishes from options in each category, create their own personalized ending wishes, and a generating AI will suggest new products and services. This allows users to clarify their ending road while enjoying the process, including their wishes, and entrust their wishes to future generations.

[0048] An end-of-life planning preference tool according to an embodiment includes a selection unit, a generation unit, and a suggestion unit. The selection unit selects desired content from options for each category. For example, a user can clarify their wishes by selecting options from categories such as funeral style, inheritance distribution, and memorial service. The generation unit creates a personalized ending preference based on the desired content selected by the selection unit. For example, the generation AI organizes and documents the desired content based on the desired content selected by the user. The suggestion unit suggests new products or services based on the personalized ending preference created by the generation unit. For example, the generation AI provides information and services regarding natural burials based on the desired content of the user. As a result, the end-of-life planning preference tool according to an embodiment allows a user to clarify their desired content while enjoying the road to their end, and entrust their wishes to future generations.

[0049] The selection unit allows the generation AI to propose individually customized options based on the user's past selection history. For example, the selection unit stores the user's past selections in a database, and the generation AI proposes new options based on that history. For example, a user who previously requested a simple funeral will be presented with new options related to simple funerals. The selection unit also analyzes the user's past selection history, and the generation AI proposes individually customized options. For example, a user who previously requested a natural burial will be proposed with new services and options related to natural burials. The selection unit also allows the generation AI to propose individually customized options in real time based on the user's selection history. For example, a user who previously made a selection after discussing it with the entire family will be presented with new options that the whole family can enjoy. In this way, by proposing customized options based on the user's past selection history, it is possible to provide more personalized preferences.

[0050] The selection unit can analyze the user's lifestyle and values, and the generation AI can provide options based on that. For example, the selection unit collects the user's lifestyle and values ​​from questionnaires and profile information, and the generation AI suggests options based on that. For example, an eco-conscious user can be presented with environmentally friendly funeral options. The selection unit can also analyze the user's lifestyle and values, and the generation AI can provide options based on that. For example, a user who values ​​time with family can be suggested a memorial service that the entire family can participate in. The selection unit can also analyze the user's values, and the generation AI can provide options based on that. For example, a user who values ​​tradition can be presented with options based on traditional ceremonies and customs. This allows the user to select more appropriate options by providing options based on their lifestyle and values.

[0051] The selection unit can use the emotion estimation function to analyze the emotion a user has when selecting an option in real time, and prioritize presenting options that elicit positive emotions. For example, the selection unit uses the emotion estimation function to analyze the emotion a user has when selecting an option in real time, and prioritize presenting options that elicit positive emotions. For example, options that make the user smile are displayed preferentially. The selection unit also analyzes the user's emotions in real time, and the generation AI suggests options that elicit positive emotions. For example, options that make the user show a relaxed expression are displayed preferentially. The selection unit also uses the emotion estimation function to analyze the emotion a user has when selecting an option, and prioritize presenting options that elicit positive emotions. For example, options that the user is interested in are displayed preferentially. In this way, the user's emotions are analyzed in real time, and options that elicit positive emotions are displayed preferentially, thereby improving user satisfaction.

[0052] The generation unit allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays a scenario of the funeral flow or estate distribution in diagrams or charts. The generation unit also allows the generation AI to create a detailed scenario based on the user's selections and present it visually. For example, the generation unit visually displays a memorial service schedule and attendee list. The generation unit also allows the generation AI to create a detailed scenario based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays an overall picture of the desired ending in mind map format. In this way, by visually presenting a detailed scenario based on the user's selections, the user can more easily understand their wishes.

[0053] The generation unit allows the generation AI to automatically generate relevant legal documents and procedures based on the user's selections. The generation unit, for example, automatically generates relevant legal documents and procedures based on the user's selections. For example, it automatically generates a will or an estate distribution contract. The generation unit also simplifies procedures by having the generation AI automatically generate relevant legal documents based on the user's selections. For example, it automatically generates documents necessary for funeral arrangements. The generation unit also automatically generates relevant legal documents and procedures based on the user's selections. For example, it automatically generates a memorial service contract and participant list. This simplifies procedures by automatically generating relevant legal documents and procedures based on the user's selections.

[0054] The generation unit uses the emotion estimation function to analyze the emotions of the user when creating their wish, and the generation AI can suggest words and expressions that elicit positive emotions. For example, the generation unit uses the emotion estimation function to analyze the emotions of the user when creating their wish, and the generation AI suggests words and expressions that elicit positive emotions. For example, it suggests words that will make the user smile. The generation unit also analyzes the user's emotions in real time, and the generation AI suggests words and expressions that elicit positive emotions. For example, it suggests expressions that will relax the user. The generation unit also uses the emotion estimation function to analyze the emotions of the user when creating their wish, and the generation AI suggests words and expressions that elicit positive emotions. For example, it suggests words that will interest the user. In this way, by analyzing the user's emotions and suggesting words and expressions that elicit positive emotions, user satisfaction is improved.

[0055] The suggestion unit allows the generation AI to automatically research and suggest new related products and services based on the user's selections. For example, the suggestion unit automatically researches and suggests new related products and services based on the user's selections. For example, the latest natural burial services are suggested to a user who desires a natural burial. The suggestion unit also allows the generation AI to research and suggest new products and services based on the user's selections. For example, the latest eco-funeral services are suggested to a user who desires eco-friendly funeral options. The suggestion unit also allows the generation AI to automatically research and suggest new related products and services based on the user's selections. For example, the latest family-friendly services are suggested to a user who desires a memorial service that the whole family can enjoy. In this way, new products and services are researched and suggested based on the user's selections, thereby providing new options that meet the user's wishes.

[0056] The suggestion unit allows the generation AI to propose new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a memorial service using virtual reality. The suggestion unit may also propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose a funeral service that can be attended online. The suggestion unit may also propose a new service that incorporates market trends and the latest technology based on the user's selections. For example, the suggestion unit may propose an inheritance distribution support service using AI. This allows the user to be provided with the latest options by proposing new services that incorporate market trends and the latest technology.

[0057] The suggestion unit can use the emotion estimation function to analyze the emotions a user has when discovering a new product or service, and make suggestions that elicit positive emotions. For example, the suggestion unit uses the emotion estimation function to analyze the emotions a user has when discovering a new product or service, and make suggestions that elicit positive emotions. For example, it prioritizes suggestions for services that the user has shown interest in. The suggestion unit also analyzes the user's emotions in real time, and the generation AI suggests new products and services that elicit positive emotions. For example, it suggests services that will make the user smile. The suggestion unit also uses the emotion estimation function to analyze the emotions a user has when discovering a new product or service, and make suggestions that elicit positive emotions. For example, it suggests services that will relax the user. In this way, by analyzing the user's emotions and making suggestions that elicit positive emotions, user satisfaction is improved.

[0058] The suggestion unit can incorporate elements related to the user's hobbies and interests into suggestions for new products and services. For example, the suggestion unit incorporates elements related to the user's hobbies and interests into suggestions for new products and services. For example, for a user who likes music, the suggestion unit suggests a memorial service that plays favorite songs. The suggestion unit also takes the user's hobbies and interests into consideration and incorporates entertainment elements into suggestions for new products and services. For example, for a user who likes movies, the suggestion unit suggests a service that recreates favorite movie scenes. The suggestion unit also incorporates elements related to the user's interests into suggestions for new products and services. For example, for a user who likes traveling, the suggestion unit suggests memorial services at travel destinations. In this way, by incorporating elements related to the user's hobbies and interests into suggestions, it is possible to provide the user with attractive options.

[0059] The suggestion unit can have the AI ​​generator propose new products and services based on different cultures and religions, enabling selection from a global perspective. For example, the suggestion unit proposes services based on religious rituals such as Buddhism, Christianity, and Islam. The suggestion unit can also propose funeral and memorial services from different cultures as new products and services, allowing users to select from a global perspective. For example, the suggestion unit can propose services based on Mexico's "Day of the Dead" and Japan's "Obon." The suggestion unit can also propose new products and services based on different religions and cultures, allowing users to choose from a variety of options. For example, the suggestion unit can propose Hindu cremation ceremonies and Jewish funeral ceremonies. This allows the system to provide users with a variety of options by proposing new products and services based on different cultures and religions.

[0060] The suggestion unit uses the emotion estimation function to analyze the emotions of all family members, and the AI ​​generation system can propose new products and services that everyone can agree on. For example, the suggestion unit uses the emotion estimation function to analyze the emotions of all family members in real time, and the AI ​​generation system can propose new products and services that everyone can agree on. For example, it can propose services that make all family members smile. The suggestion unit also analyzes the emotions of all family members, and the AI ​​generation system can propose new products and services that everyone can agree on. For example, it can propose services that make all family members look relaxed. The suggestion unit also uses the emotion estimation function to analyze the emotions of all family members, and the AI ​​generation system can propose new products and services that everyone can agree on. For example, it can propose services that all family members are interested in. In this way, by analyzing the emotions of all family members and proposing new products and services that everyone can agree on, it is possible to provide options that satisfy the whole family.

[0061] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0062] The selection unit can also monitor the user's health condition and suggest appropriate options based on that. For example, if the user is elderly, it will suggest a funeral style that places less physical strain on the user. The selection unit also analyzes the user's health condition in real time and provides appropriate options. For example, if the user has a chronic illness, it will suggest a memorial service that takes that chronic illness into consideration. The selection unit also takes the user's health condition into consideration, and the generation AI suggests options that take health into consideration. For example, if the user is undergoing rehabilitation, it will suggest a memorial service at a rehabilitation facility. This allows the user to select more appropriate options by providing options based on their health condition.

[0063] The selection unit can also have the generation AI suggest memorial services at travel destinations based on the user's past travel history. For example, it can suggest funeral or memorial services at places the user has visited in the past. The selection unit can also analyze the user's travel history, and the generation AI can suggest new options at travel destinations. For example, it can suggest memorial services at tourist spots the user likes. The selection unit can also have the generation AI suggest memorial services at travel destinations in real time based on the user's travel history. For example, it can suggest natural burials at places the user has visited in the past. This allows the user to provide more personalized desired services by suggesting customized options based on their travel history.

[0064] The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes music, the selection unit can present a funeral option that plays their favorite songs. The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes movies, the selection unit can suggest a memorial service that recreates a scene from their favorite movie. The selection unit can also analyze the user's hobbies and interests, and the generation AI can provide options based on that. For example, for a user who likes traveling, the selection unit can suggest a memorial service at their travel destination. This allows the user to select more appropriate options by providing options based on their hobbies and interests.

[0065] The selection unit can also use the emotion estimation function to analyze the emotions the user feels when selecting an option in real time, and prioritize presenting options that avoid negative emotions. For example, it avoids options that make the user feel sad. The selection unit also analyzes the user's emotions in real time, and the generation AI suggests options that avoid negative emotions. For example, it avoids options that make the user feel stressed. The selection unit also uses the emotion estimation function to analyze the emotions the user feels when selecting an option, and prioritize presenting options that avoid negative emotions. For example, it avoids options that make the user feel anxious. In this way, by analyzing the user's emotions in real time and prioritizing presenting options that avoid negative emotions, user satisfaction is improved.

[0066] The generation unit can also have the generation AI create a scenario that takes emotions into consideration based on the user's selections and present it in a visually easy-to-understand format. For example, it can create a scenario that gives the user a sense of security. The generation unit can also have the generation AI create a scenario that takes emotions into consideration based on the user's selections and present it visually. For example, it can display a scenario that helps the user relax in the form of a diagram or chart. The generation unit can also create a scenario that takes emotions into consideration based on the user's selections and present it in a visually easy-to-understand format. For example, it can display an overall picture of the desired ending that leaves the user with positive emotions in the form of a mind map. In this way, by visually presenting a scenario that takes emotions into consideration based on the user's selections, it becomes easier for the user to understand what they want.

[0067] The generation unit can also have the generation AI create a scenario that incorporates relevant cultural background and historical elements based on the user's selections. For example, the generation unit creates a scenario that explains the historical background related to the funeral style selected by the user. The generation unit also has the generation AI create a scenario that incorporates cultural background and historical elements based on the user's selections and visually present it. For example, the generation unit displays cultural elements related to the memorial service selected by the user in diagrams and charts. The generation unit also has the generation AI create a scenario that incorporates cultural background and historical elements based on the user's selections and present it in a visually easy-to-understand format. For example, the generation unit displays an overall picture of the ending desired by the user, along with the cultural background, in mind map format. This makes it easier for the user to understand their wishes by visually presenting a scenario that incorporates cultural background and historical elements based on the user's selections.

[0068] The generation unit uses the emotion estimation function to analyze the emotions a user feels when creating their wish, and the generation AI can suggest words and expressions that avoid negative emotions. For example, it can suggest words that will not make the user feel sad. The generation unit also analyzes the user's emotions in real time, and the generation AI can suggest words and expressions that avoid negative emotions. For example, it can suggest expressions that will not make the user feel stressed. The generation unit also uses the emotion estimation function to analyze the emotions a user feels when creating their wish, and the generation AI can suggest words and expressions that avoid negative emotions. For example, it can suggest words that will not make the user feel anxious. In this way, by analyzing the user's emotions and suggesting words and expressions that avoid negative emotions, user satisfaction is improved.

[0069] The suggestion unit can also have the generation AI automatically research and suggest new related products and services based on the user's selections. For example, it can suggest the latest services related to the funeral style selected by the user. The suggestion unit can also have the generation AI automatically research and suggest new products and services based on the user's selections. For example, it can suggest the latest options related to the memorial service selected by the user. The suggestion unit can also automatically research and suggest new products and services based on the user's selections. For example, it can suggest the latest services related to the ending wishes selected by the user. In this way, by researching and suggesting new products and services based on the user's selections, it is possible to provide new options that match the user's wishes.

[0070] The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest services that incorporate the latest technology for the funeral style selected by the user. The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest options that incorporate the latest technology for the memorial service selected by the user. The suggestion unit can also have the generation AI suggest new services that incorporate market trends and the latest technology based on the user's selections. For example, the suggestion unit can suggest services that incorporate the latest technology for the ending preference selected by the user. In this way, by suggesting new services that incorporate market trends and the latest technology, the user can be provided with the latest options.

[0071] The suggestion unit can use the emotion estimation function to analyze the emotions a user feels when discovering a new product or service, and make suggestions to avoid negative emotions. For example, avoiding a service that makes the user feel anxious. The suggestion unit also analyzes the user's emotions in real time, and the AI ​​generates suggestions for new products and services that avoid negative emotions. For example, avoiding a service that makes the user feel stressed. The suggestion unit also uses the emotion estimation function to analyze the emotions a user feels when discovering a new product or service, and make suggestions to avoid negative emotions. For example, avoiding a service that makes the user feel sad. In this way, by analyzing the user's emotions and making suggestions to avoid negative emotions, user satisfaction is improved.

[0072] The processing flow of the second embodiment will be briefly explained below.

[0073] Step 1: The selection unit selects desired content from options for each category. For example, users can select options from categories such as funeral style, distribution of inheritance, and memorial service to clarify their wishes. Step 2: The generation unit creates a personalized ending based on the desired content selected by the selection unit. For example, the generation AI organizes and documents the desired content based on the desired content selected by the user. Step 3: The suggestion unit proposes new products or services based on the My Ending wishes created by the generation unit. For example, the generation AI may provide information and services related to natural burials based on the user's wishes.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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).

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0091] 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.

[0092] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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).

[0098] 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.

[0099] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0100] 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.

[0101] 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.

[0102] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0103] 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.

[0104] 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.

[0105] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0106] 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.

[0107] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0108] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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).

[0113] 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.

[0114] 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.

[0115] 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.

[0116] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0117] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0118] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0120] The specific processing unit 290 transmits the result of the specific processing to the 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.

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

[0122] The data processing system 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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."

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0140] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0141] 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 selection section for selecting desired content from options for each category; a generation unit that generates a desired ending based on the desired content selected by the selection unit; a proposal unit that proposes new products or services based on the My Ending wishes created by the creation unit. A system characterized by:

2. The selection unit Based on the user's past selection history, the generative AI proposes individually customized options.

2. The system of claim 1.

3. The selection unit The AI ​​analyzes the user's lifestyle and values ​​and generates the above options based on them.

2. The system of claim 1.

4. The selection unit The emotions of the user when selecting the option are analyzed in real time, and the option that elicits positive emotions is presented preferentially.

2. The system of claim 1.

5. The generation unit Based on the user's selections, the generative AI creates a detailed scenario and presents it in a visually easy-to-understand format.

2. The system of claim 1.

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