System

Abstract

An object of a system according to an embodiment is to enable daily utilization of a voice dialogue function of a generated AI.SOLUTION: A system according to an embodiment includes a dedicated button, a generation AI, and a discount service. The dedicated button is installed on the smartphone. The generation AI is activated by pressing a dedicated button. The discount service is provided through a specific carrier.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies do not adequately provide the means to utilize the voice dialogue capabilities of generative AI on a daily basis, and there is room for improvement.

[0005] The system according to the embodiment aims to enable the voice dialogue function of the generation AI to be utilized on a daily basis. [Means for solving the problem]

[0006] The system according to the embodiment includes a dedicated button, a generation AI, and a discount service. The dedicated button is installed on a smartphone. The generation AI is activated by pressing the dedicated button. The discount service is provided through a specific telecommunications carrier. [Effects of the Invention]

[0007] The system according to the embodiment enables the voice dialogue function of the generation AI to be utilized on a daily basis. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A smartphone system according to an embodiment of the present invention is a system that has been improved to enable the voice dialogue function of a generation AI to be utilized on a daily basis, and that provides discount services for contracts with a specific telecommunications carrier. As a result, the smartphone system can utilize the voice dialogue function of a generation AI on a daily basis and provide discount services for contracts with a specific telecommunications carrier.

[0029] A smartphone system according to an embodiment includes a dedicated button, a generation AI, and a discount service. The dedicated button is installed on a smartphone. For example, the dedicated button may be located on the side or front of the smartphone. Pressing the dedicated button activates the generation AI. The generation AI accepts voice input from the user. For example, when a user asks, "What's the weather like today?", the generation AI responds, "It's sunny today." The discount service is provided through a specific telecommunications carrier. For example, if a user simultaneously subscribes to a line contract with telecommunications carrier A and a paid service provided by the generation AI, the monthly fee is discounted by 10%. This allows the smartphone system to routinely utilize the voice dialogue function of the generation AI and provide discount services for contracts made through a specific telecommunications carrier.

[0030] The dedicated button allows the generation AI to refer to the user's past interaction history and instantly provide the most relevant information. When the dedicated button is pressed, the generation AI analyzes the user's past interaction history and instantly provides the most relevant information. For example, a user who has frequently asked about weather information in the past will be provided with the latest weather information. When the dedicated button is pressed, the generation AI also refers to the user's past search history and provides related information. For example, a user who has previously searched for restaurant information will be provided with information about nearby restaurants. When the dedicated button is pressed, the generation AI also provides news and topics that the user may be interested in based on the user's past interaction history. For example, a user who has frequently asked about sports news in the past will be provided with the latest sports news. This allows the generation AI to provide highly relevant information based on the user's past interaction history.

[0031] The dedicated button allows the generation AI to generate responses that take into account the user's current situation. When the dedicated button is pressed and held, the generation AI obtains the user's current location information and provides information on nearby restaurants and cafes. For example, if the user is at a train station, it will suggest restaurants around the station. When the dedicated button is pressed and held, the generation AI also references the user's calendar information and provides reminders and traffic information for upcoming appointments. For example, it will notify the location and start time of the next meeting. When the dedicated button is pressed and held, the generation AI also takes into account the user's current situation and generates an appropriate response. For example, if the user is at home, it will suggest housework advice or recipes. This allows the generation AI to provide appropriate responses based on the user's current situation.

[0032] The dedicated button allows the generating AI to switch to different modes and provide responses appropriate to the mode. Double-clicking the dedicated button switches the generating AI to work mode, providing work-related information and task management. For example, prompting you to check your meeting schedule or email. Double-clicking the dedicated button also switches the generating AI to private mode, providing information related to relaxation and entertainment. For example, it suggests movies and suggests music to play. Double-clicking the dedicated button also switches the generating AI to exercise mode, providing fitness-related information and training plans. For example, it suggests running courses and records exercise. This allows the device to provide appropriate responses according to the different modes.

[0033] The dedicated button allows the generation AI to work with smart home devices to operate home appliances and set environmental settings. When the dedicated button is pressed, the generation AI works with smart home devices to turn lights on and off and adjust brightness. For example, it can instruct the device to dim the lights in the living room. When the dedicated button is pressed, the generation AI also works with smart home devices to change the air conditioner's temperature setting and operation mode. For example, it can adjust the room temperature to a comfortable temperature. When the dedicated button is pressed, the generation AI also works with smart home devices to play music or change the TV channel. For example, it can instruct the device to play relaxing music. This allows the generation AI to work with smart home devices to operate home appliances and set environmental settings.

[0034] The discount service dynamically changes based on the user's usage history and behavioral patterns, making it possible to provide optimal discounts. The discount service analyzes the user's usage history and applies discounts to frequently used services. For example, a user who frequently uses the voice dialogue function is provided with a discount for that function. The discount service also analyzes the user's behavioral patterns and applies discounts to services used during specific times of the day or on specific days of the week. For example, a user who frequently uses the voice dialogue function on weekday evenings is provided with a discount for that time of day. The discount service also provides personalized discounts based on the user's usage history and behavioral patterns. For example, a user who frequently uses a specific function is provided with a discount for that function. This makes it possible to provide optimal discounts based on the user's usage history and behavioral patterns.

[0035] Discount services can be increased in stages depending on the user's contract period and frequency of use. Discount services increase the discount rate in stages depending on the user's contract period. For example, a 5% discount is offered to users with a one-year contract, and a 10% discount is offered to users with a two-year contract. Discount services also increase the discount rate in stages depending on the user's frequency of use. For example, a 5% discount is offered to users who use the service more than 10 times a month, and a 10% discount is offered to users who use the service more than 20 times a month. Discount services also increase the discount rate in stages by combining the user's contract period and frequency of use. For example, a 15% discount is offered to users who use the service more than 20 times a month on a one-year contract. This allows the discount to be increased in stages depending on the user's contract period and frequency of use.

[0036] Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. Discount services are applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on the first month's fee. Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on the monthly fee for the duration of the contract. Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on a specific service. This allows discounts to be applied when switching between different telecommunications carriers, thereby expanding user options.

[0037] The discount service varies depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. The discount service varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a 5% discount is provided to users who use it more than 10 times a month, and a 10% discount is provided to users who use it more than 20 times a month. The discount service also varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a 5% discount is provided to users who use it more than 5 times a week, and a 10% discount is provided to users who use it more than 10 times a week. The discount service also varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a special discount is provided to users who use it daily. This allows the discount to vary depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently.

[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 smartphone system can also be equipped with health management functions. For example, by pressing a dedicated button, the AI ​​generator can monitor the user's health condition and provide appropriate advice. It can record the user's steps and heart rate, and if it detects a lack of exercise, it can send a notification encouraging them to exercise. It can also record meals and provide advice on nutritional balance. It can also analyze sleep quality and make suggestions for improvement. This can support the user's health management.

[0040] The smartphone system can also be equipped with educational support functions. For example, by pressing a dedicated button, the generative AI analyzes the user's learning history and provides appropriate learning content. It can suggest review or new learning content based on what the user has learned in the past. It can also monitor the user's learning progress and provide advice on how to achieve goals. Furthermore, it can provide relevant learning resources based on the user's interests. This can effectively support the user's learning.

[0041] The smartphone system can also be equipped with travel support functions. For example, by pressing a dedicated button, the generation AI can support the user's travel plans. It can suggest optimal travel destinations and tourist spots based on the user's current location and past travel history. It can also support reservations for transportation and accommodation during the trip. It can also provide weather information and local event information at the travel destination, making the user's trip more comfortable. This can effectively support the user's travel plans.

[0042] The smartphone system can also be equipped with emergency response functions. For example, by pressing and holding a dedicated button, the generation AI can automatically send a notification to emergency contacts. If the user is in a dangerous situation, an emergency message including location information can be sent. The generation AI can also monitor the user's health and, if it detects an abnormality, send a notification urging emergency response. Furthermore, in the event of a disaster, it can provide information on evacuation routes and shelters to ensure the user's safety. This effectively supports user safety.

[0043] The smartphone system can also be equipped with a personal finance management function. For example, by pressing a dedicated button, the AI ​​generator can manage the user's income and expenses and provide appropriate advice. It can analyze the user's spending history and make suggestions for saving. It can also set a savings target and monitor progress toward achieving it. It can also provide investment advice and risk management suggestions to improve the user's financial situation. This can effectively support the user's personal finances.

[0044] The processing flow of the first embodiment will be briefly explained below.

[0045] Step 1: The dedicated button is installed on the smartphone. For example, the dedicated button is placed on the side or front of the smartphone. Step 2: Pressing the dedicated button activates the generation AI. The generation AI accepts the user's voice input. For example, if the user asks, "What's the weather like today?" the generation AI will respond, "Today's weather is sunny." Step 3: Discount services are provided through specific carriers. For example, if you sign up for a line contract with carrier A and a paid service from Generator AI at the same time, you will receive a 10% discount on your monthly fee.

[0046] (Example 2) A smartphone system according to an embodiment of the present invention is a system that has been improved to enable the voice dialogue function of a generation AI to be utilized on a daily basis, and that provides discount services for contracts with a specific telecommunications carrier. As a result, the smartphone system can utilize the voice dialogue function of a generation AI on a daily basis and provide discount services for contracts with a specific telecommunications carrier.

[0047] A smartphone system according to an embodiment includes a dedicated button, a generation AI, and a discount service. The dedicated button is installed on a smartphone. For example, the dedicated button may be located on the side or front of the smartphone. Pressing the dedicated button activates the generation AI. The generation AI accepts voice input from the user. For example, when a user asks, "What's the weather like today?", the generation AI responds, "It's sunny today." The discount service is provided through a specific telecommunications carrier. For example, if a user simultaneously subscribes to a line contract with telecommunications carrier A and a paid service provided by the generation AI, the monthly fee is discounted by 10%. This allows the smartphone system to routinely utilize the voice dialogue function of the generation AI and provide discount services for contracts made through a specific telecommunications carrier.

[0048] The dedicated button allows the generation AI to refer to the user's past interaction history and instantly provide the most relevant information. When the dedicated button is pressed, the generation AI analyzes the user's past interaction history and instantly provides the most relevant information. For example, a user who has frequently asked about weather information in the past will be provided with the latest weather information. When the dedicated button is pressed, the generation AI also refers to the user's past search history and provides related information. For example, a user who has previously searched for restaurant information will be provided with information about nearby restaurants. When the dedicated button is pressed, the generation AI also provides news and topics that the user may be interested in based on the user's past interaction history. For example, a user who has frequently asked about sports news in the past will be provided with the latest sports news. This allows the generation AI to provide highly relevant information based on the user's past interaction history.

[0049] The dedicated button allows the generation AI to generate responses that take into account the user's current situation. When the dedicated button is pressed and held, the generation AI obtains the user's current location information and provides information on nearby restaurants and cafes. For example, if the user is at a train station, it will suggest restaurants around the station. When the dedicated button is pressed and held, the generation AI also references the user's calendar information and provides reminders and traffic information for upcoming appointments. For example, it will notify the location and start time of the next meeting. When the dedicated button is pressed and held, the generation AI also takes into account the user's current situation and generates an appropriate response. For example, if the user is at home, it will suggest housework advice or recipes. This allows the generation AI to provide appropriate responses based on the user's current situation.

[0050] The dedicated button allows the generation AI to infer the user's emotions and provide a response that corresponds to their emotions. When the dedicated button is pressed, the generation AI analyzes the user's tone of voice and vocabulary to infer their emotions. For example, if the user is tired, it will suggest relaxing music or a meditation app. When the dedicated button is pressed, the generation AI also analyzes the user's facial expressions with a camera to infer their emotions. For example, if the user is sad, it will suggest words of encouragement or a fun video. When the dedicated button is pressed, the generation AI also infers their emotions based on the user's past dialogue history and behavioral patterns and provides an appropriate response. For example, if the user is feeling stressed, it will suggest relaxing music or relaxation methods. This allows the system to provide an appropriate response based on the user's emotions.

[0051] The dedicated button allows the generating AI to switch to different modes and provide responses appropriate to the mode. Double-clicking the dedicated button switches the generating AI to work mode, providing work-related information and task management. For example, prompting you to check your meeting schedule or email. Double-clicking the dedicated button also switches the generating AI to private mode, providing information related to relaxation and entertainment. For example, it suggests movies and suggests music to play. Double-clicking the dedicated button also switches the generating AI to exercise mode, providing fitness-related information and training plans. For example, it suggests running courses and records exercise. This allows the device to provide appropriate responses according to the different modes.

[0052] The dedicated button allows the generation AI to work with smart home devices to operate home appliances and set environmental settings. When the dedicated button is pressed, the generation AI works with smart home devices to turn lights on and off and adjust brightness. For example, it can instruct the device to dim the lights in the living room. When the dedicated button is pressed, the generation AI also works with smart home devices to change the air conditioner's temperature setting and operation mode. For example, it can adjust the room temperature to a comfortable temperature. When the dedicated button is pressed, the generation AI also works with smart home devices to play music or change the TV channel. For example, it can instruct the device to play relaxing music. This allows the generation AI to work with smart home devices to operate home appliances and set environmental settings.

[0053] The dedicated button allows the generation AI to estimate the user's emotions and suggest entertainment content that matches their emotions. When the dedicated button is pressed, the generation AI analyzes the user's tone of voice and vocabulary to estimate their emotions. For example, if the user is tired, it will suggest relaxing movies or games. When the dedicated button is pressed, the generation AI also analyzes the user's facial expressions with a camera to estimate their emotions. For example, if the user is sad, it will suggest fun movies or games. When the dedicated button is pressed, the generation AI also estimates their emotions based on the user's past dialogue history and behavioral patterns and provides appropriate entertainment content. For example, if the user is feeling stressed, it will suggest relaxing movies or games. This makes it possible to provide appropriate entertainment content based on the user's emotions.

[0054] The discount service dynamically changes based on the user's usage history and behavioral patterns, making it possible to provide optimal discounts. The discount service analyzes the user's usage history and applies discounts to frequently used services. For example, a user who frequently uses the voice dialogue function is provided with a discount for that function. The discount service also analyzes the user's behavioral patterns and applies discounts to services used during specific times of the day or on specific days of the week. For example, a user who frequently uses the voice dialogue function on weekday evenings is provided with a discount for that time of day. The discount service also provides personalized discounts based on the user's usage history and behavioral patterns. For example, a user who frequently uses a specific function is provided with a discount for that function. This makes it possible to provide optimal discounts based on the user's usage history and behavioral patterns.

[0055] Discount services can be increased in stages depending on the user's contract period and frequency of use. Discount services increase the discount rate in stages depending on the user's contract period. For example, a 5% discount is offered to users with a one-year contract, and a 10% discount is offered to users with a two-year contract. Discount services also increase the discount rate in stages depending on the user's frequency of use. For example, a 5% discount is offered to users who use the service more than 10 times a month, and a 10% discount is offered to users who use the service more than 20 times a month. Discount services also increase the discount rate in stages by combining the user's contract period and frequency of use. For example, a 15% discount is offered to users who use the service more than 20 times a month on a one-year contract. This allows the discount to be increased in stages depending on the user's contract period and frequency of use.

[0056] A discount service can be provided as a reward to elicit positive emotions by estimating a user's emotions. The discount service analyzes a user's emotions and provides a discount as a reward to elicit positive emotions. For example, if a user is satisfied, an additional discount is provided the next time the user uses the service. The discount service also analyzes a user's emotions in real time and provides a discount as a reward to elicit positive emotions. For example, if a user is happy, a discount coupon is provided on the spot. The discount service also builds a system that analyzes a user's emotions and provides a discount as a reward to elicit positive emotions. For example, if a user expresses gratitude, an additional discount is provided the next time the user uses the service. In this way, a discount can be provided as a reward to elicit positive emotions based on the user's emotions.

[0057] Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. Discount services are applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on the first month's fee. Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on the monthly fee for the duration of the contract. Discount services are also applied when switching between different telecommunications carriers, thereby expanding user options. For example, a user switching from another telecommunications carrier receives a discount on a specific service. This allows discounts to be applied when switching between different telecommunications carriers, thereby expanding user options.

[0058] The discount service varies depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. The discount service varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a 5% discount is provided to users who use it more than 10 times a month, and a 10% discount is provided to users who use it more than 20 times a month. The discount service also varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a 5% discount is provided to users who use it more than 5 times a week, and a 10% discount is provided to users who use it more than 10 times a week. The discount service also varies the discount rate depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently. For example, a special discount is provided to users who use it daily. This allows the discount to vary depending on the frequency of use of the generation AI, and can provide larger discounts to users who use it frequently.

[0059] A discount service can estimate a user's emotions and provide rewards according to the emotions. The discount service analyzes a user's emotions and provides gift cards or points as rewards according to the emotions. For example, if a user is happy, a gift card that can be used the next time the user uses the service is provided. The discount service also analyzes a user's emotions in real time and provides gift cards or points as rewards according to the emotions. For example, if a user is satisfied, points are awarded on the spot. The discount service also builds a system that analyzes a user's emotions and provides gift cards or points as rewards according to the emotions. For example, if a user expresses gratitude, points that can be used the next time the user uses the service are provided. In this way, rewards can be provided based on the user's emotions, and user satisfaction can be improved.

[0060] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0061] The smartphone system can also be equipped with health management functions. For example, by pressing a dedicated button, the AI ​​generator can monitor the user's health condition and provide appropriate advice. It can record the user's steps and heart rate, and if it detects a lack of exercise, it can send a notification encouraging them to exercise. It can also record meals and provide advice on nutritional balance. It can also analyze sleep quality and make suggestions for improvement. This can support the user's health management.

[0062] The smartphone system can also be equipped with educational support functions. For example, by pressing a dedicated button, the generative AI analyzes the user's learning history and provides appropriate learning content. It can suggest review or new learning content based on what the user has learned in the past. It can also monitor the user's learning progress and provide advice on how to achieve goals. Furthermore, it can provide relevant learning resources based on the user's interests. This can effectively support the user's learning.

[0063] The smartphone system can also be equipped with travel support functions. For example, by pressing a dedicated button, the generation AI can support the user's travel plans. It can suggest optimal travel destinations and tourist spots based on the user's current location and past travel history. It can also support reservations for transportation and accommodation during the trip. It can also provide weather information and local event information at the travel destination, making the user's trip more comfortable. This can effectively support the user's travel plans.

[0064] The smartphone system can also be equipped with emergency response functions. For example, by pressing and holding a dedicated button, the generation AI can automatically send a notification to emergency contacts. If the user is in a dangerous situation, an emergency message including location information can be sent. The generation AI can also monitor the user's health and, if it detects an abnormality, send a notification urging emergency response. Furthermore, in the event of a disaster, it can provide information on evacuation routes and shelters to ensure the user's safety. This effectively supports user safety.

[0065] The smartphone system can also be equipped with a personal finance management function. For example, by pressing a dedicated button, the AI ​​generator can manage the user's income and expenses and provide appropriate advice. It can analyze the user's spending history and make suggestions for saving. It can also set a savings target and monitor progress toward achieving it. It can also provide investment advice and risk management suggestions to improve the user's financial situation. This can effectively support the user's personal finances.

[0066] The smartphone system can also estimate the user's emotions and provide health management advice based on the user's emotions. For example, if the user is feeling stressed, the system can suggest relaxing exercise or meditation. If the user is tired, the system can provide advice on appropriate rest and nutrition. Furthermore, if the user is feeling positive, the system can suggest a healthy lifestyle to maintain that emotion. This allows the system to support health management based on the user's emotions.

[0067] The smartphone system can also estimate the user's emotions and provide learning support tailored to their emotions. For example, if the user is lacking concentration, it can suggest ways to study effectively in a short amount of time. If the user is losing motivation, it can send encouraging messages or share successful experiences. Furthermore, if the user is feeling positive, it can use those emotions to set new learning goals and provide support to help them achieve them. This allows for effective learning support based on the user's emotions.

[0068] The smartphone system can also estimate the user's emotions and suggest travel plans based on the user's emotions. For example, if the user is looking for relaxation, quiet resorts and hot springs can be suggested. If the user is looking for adventure, travel destinations where active activities can be enjoyed can be suggested. Furthermore, if the user is looking for a cultural experience, plans to visit historical tourist sites and art museums can be suggested. This makes it possible to provide optimal travel plans based on the user's emotions.

[0069] The smartphone system can also estimate the user's emotions and provide appropriate emergency responses based on their emotions. For example, if the user is panicking, it can suggest breathing exercises or relaxation techniques to calm them down. If the user is feeling anxious, it can provide reassuring messages and support. Furthermore, if the user is in a dangerous situation, it can quickly send a notification to emergency contacts. This allows appropriate emergency responses to be taken based on the user's emotions.

[0070] The smartphone system can also estimate the user's emotions and provide emotionally appropriate personal finance management. For example, if the user is feeling stressed, the system can suggest spending plans and saving methods that will help them relax. If the user is feeling positive, the system can use those emotions to provide investment advice and risk management suggestions. Furthermore, if the user is feeling anxious, the system can provide financial plans and support to give them peace of mind. This allows for effective personal finance management based on the user's emotions.

[0071] The processing flow of the second embodiment will be briefly explained below.

[0072] Step 1: The dedicated button is installed on the smartphone. For example, the dedicated button is placed on the side or front of the smartphone. Step 2: Pressing the dedicated button activates the generation AI. The generation AI accepts the user's voice input. For example, if the user asks, "What's the weather like today?" the generation AI will respond, "Today's weather is sunny." Step 3: Discount services are provided through specific carriers. For example, if you sign up for a line contract with carrier A and a paid service from Generator AI at the same time, you will receive a 10% discount on your monthly fee.

[0073] 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.

[0074] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0075] 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.

[0076] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0077] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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).

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0090] 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.

[0091] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0092] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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).

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0105] 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.

[0106] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0118] 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.

[0119] 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.

[0120] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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).

[0126] 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.

[0127] 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."

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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]

[0140] 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 dedicated button on the smartphone, A generation AI that is activated by pressing the dedicated button; Discount services provided through specific telecommunications carriers; A system characterized by:

2. The dedicated button is The generative AI references the user's past interaction history and instantly provides the most relevant information.

2. The system of claim 1.

3. The dedicated button is The generative AI generates a response that takes into account the user's current situation.

2. The system of claim 1.

4. The dedicated button is The generative AI infers the user's emotions and provides responses according to those emotions.

2. The system of claim 1.

5. The dedicated button is The generated AI switches between different modes and provides responses depending on the mode.

2. The system of claim 1.

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