System

Abstract

One or more example embodiments also provide a system that may provide a prompt for effectively using a generated AI and enable a user to conveniently use the generated AI.SOLUTION: A system includes a prompt introduction part, a log-in part, a reward part, a purchase and sale part, and an advertisement part. The prompt introduction unit introduces a prompt necessary for use of the generated AI. The login unit manages login with a user account. The reward unit gives a reward according to the number of uses of the prompt or the number of page views. The trading section manages trading of prompt ideas. The advertisement unit publishes an advertisement.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 for users to find prompts to effectively utilize generative AI, preventing them from making full use of the AI.

[0005] The system according to the embodiment aims to provide prompts for effectively utilizing the generated AI, thereby enabling users to conveniently utilize the generated AI. [Means for solving the problem]

[0006] The system according to the embodiment includes a prompt introduction unit, a login unit, a reward unit, a buying and selling unit, and an advertising unit. The prompt introduction unit introduces prompts necessary for utilizing the generative AI. The login unit manages logins with user accounts. The reward unit provides rewards based on the number of prompts used and the number of page views. The buying and selling unit manages the buying and selling of prompt ideas. The advertising unit places advertisements. [Effects of the Invention]

[0007] The system according to the embodiment can provide prompts for effectively utilizing the generated AI, allowing the user to conveniently utilize the generated AI. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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 web service according to an embodiment of the present invention is a system that introduces a set of prompts necessary for utilizing generative AI. This system helps people who are not yet able to effectively use generative AI to use it more conveniently. As a result, the web service provides a set of prompts for utilizing generative AI, and can help users effectively utilize generative AI.

[0029] A web service according to an embodiment includes a prompt introduction unit, a login unit, a reward unit, a buying and selling unit, and an advertising unit. The prompt introduction unit introduces prompts necessary for utilizing the generation AI. For example, the prompt introduction unit introduces prompts for planning a trip or prompts that assist in creating business emails. The prompt introduction unit also provides instructions for the generation AI to generate appropriate responses. The login unit manages logins using user accounts. For example, the login unit manages logins using accounts such as YID, SBID, and LINE. The login unit can also provide a login function using LINEID. The reward unit provides rewards based on the number of prompt usages and page views. For example, the reward unit pays rewards to posters when a posted prompt is used by many users. The reward unit can also provide a point system or cash rewards. The buying and selling unit manages the buying and selling of prompt ideas. For example, the buying and selling unit manages users' sales of prompt ideas to other users. The buying and selling unit can also allow the SB to receive a certain amount of sales commissions. The advertising unit places advertisements. For example, the advertising unit displays advertisements related to a page of a prompt collection. The advertising unit can also post banner ads, text ads, and video ads. This allows the web service according to the embodiment to support the utilization of generative AI and enable users to post, introduce, and buy and sell prompts. For example, users can find prompts for utilizing generative AI and share knowledge and ideas through the posting and buying and selling of prompts.

[0030] The prompt introduction unit can track the usage history of prompts and develop an algorithm that automatically recommends the most effective prompts. For example, the prompt introduction unit stores the usage history of prompts in a database and develops an algorithm that automatically recommends the most effective prompts based on that data. For example, the prompts are ranked based on frequency of use and user ratings. This makes it possible to recommend the most effective prompts based on the usage history.

[0031] The prompt introduction unit can add a function to automatically optimize the content of the prompt and convert it into a form that is most suitable for the user's purpose. For example, the prompt introduction unit develops a system that analyzes the content of the prompt and automatically converts it into a form that is most suitable for the user's purpose. For example, the prompt for a business email can be customized to suit a specific industry or job type. This allows the prompt content to be optimized for the user's purpose.

[0032] The prompt introduction unit can add multimodal prompts, including images and audio data, to the prompt collection, allowing the generation AI to be utilized based on visual and audio information as well. For example, the prompt introduction unit can add image and audio data to the prompt collection, allowing the generation AI to be utilized based on visual and audio information. For example, it can provide images and audio explanations related to the prompt. This allows the generation AI to be utilized using visual and audio information.

[0033] The prompt introduction unit can collect prompts created by experts in different industries and fields, allowing the user to select prompts from a variety of perspectives. The prompt introduction unit can, for example, collect prompts created by experts in different industries and fields, allowing the user to select prompts from a variety of perspectives. For example, it can provide prompts related to technology, design, and marketing. This allows the user to select prompts from a variety of perspectives.

[0034] The login unit can use generation AI to analyze the user's past usage history at the time of login and recommend individually optimized prompts. For example, the login unit will develop a system that uses generation AI to analyze the user's past usage history at the time of login and recommend individually optimized prompts. For example, the prompts will be customized based on past frequency of use and evaluations. This will make it possible to recommend optimal prompts based on the user's past usage history.

[0035] The login unit can add a function to automatically filter prompts according to the user's expertise and interests based on the login information. The login unit develops a system that automatically filters prompts according to the user's expertise and interests based on, for example, the login information. For example, the login unit customizes prompts based on the user's profile information. This makes it possible to filter prompts according to the user's expertise and interests.

[0036] The login unit can improve user convenience by integrating different SNS accounts and enabling login from multiple platforms. The login unit develops a system that integrates different SNS accounts and enables login from multiple platforms, for example, integrating Facebook, Twitter, and Google accounts. This enables login from multiple platforms and improves user convenience.

[0037] The login unit can provide a customized dashboard based on the user's profile information at the time of login. The login unit develops a system that provides a customized dashboard based on the user's profile information at the time of login, for example. For example, the login unit displays a prompt based on the user's interests and concerns. This makes it possible to provide a customized dashboard based on the user's profile information.

[0038] The reward unit can introduce a system that tracks the usage of prompts in real time and dynamically adjusts rewards according to the frequency of use and effectiveness. For example, the reward unit develops a system that tracks the usage of prompts in real time and dynamically adjusts rewards according to the frequency of use and effectiveness. For example, a high reward is provided for a prompt that is used frequently. This allows the reward to be dynamically adjusted according to the usage of the prompt.

[0039] The reward unit can automatically evaluate the quality of posted prompts and provide bonus rewards for high-quality prompts. The reward unit, for example, develops a system that automatically evaluates the quality of posted prompts and provides bonus rewards for high-quality prompts. For example, the reward unit evaluates prompts based on user ratings and frequency of use. This makes it possible to provide bonus rewards for high-quality prompts.

[0040] The reward unit can add a function that allows prompt posters to receive feedback from other users and promote the improvement of prompts. For example, the reward unit develops a system that adds a function that allows prompt posters to receive feedback from other users and promotes the improvement of prompts. For example, the reward unit improves prompts based on user comments and ratings. This makes it possible to promote the improvement of prompts by receiving feedback from other users.

[0041] The rewards department may develop a system that provides rewards for different categories or uses to encourage prompt submissions in specific fields. For example, the rewards department may provide different rewards for technical, design, and marketing prompts to encourage prompt submissions in specific fields.

[0042] The buying and selling unit can automatically evaluate the quality of prompts being bought and sold, and set premium prices for high-quality prompts. The buying and selling unit, for example, develops a system that automatically evaluates the quality of prompts being bought and sold, and sets premium prices for high-quality prompts. For example, the system evaluates prompts based on user ratings and frequency of use. This allows premium prices to be set for high-quality prompts.

[0043] The buying and selling department can expand the buying and selling of prompt ideas internationally and enable the trading of prompts in different languages ​​and cultural spheres. For example, the buying and selling department develops a system that expands the buying and selling of prompt ideas internationally and enables the trading of prompts in different languages ​​and cultural spheres. For example, the system can support multiple languages ​​such as English, French, and Chinese. This allows the trading of prompts in different languages ​​and cultural spheres.

[0044] The Buying and Selling Department can introduce bundle sales or subscription models when buying and selling prompt ideas, providing users with a variety of purchasing options. For example, the Buying and Selling Department can introduce bundle sales when buying and selling prompt ideas, and develop a system for selling multiple prompts as a set. For example, prompts related to a specific theme can be sold together. This allows users to have a variety of purchasing options.

[0045] The advertising department can use generation AI to customize the content of advertisements based on the user's interests and concerns, thereby maximizing advertising effectiveness. For example, the advertising department develops a system that uses generation AI to customize the content of advertisements based on the user's interests and concerns. For example, the advertising department personalizes advertisements based on the user's browsing history and search history. This makes it possible to maximize advertising effectiveness based on the user's interests and concerns.

[0046] The advertising department can introduce a system that tracks click rates and conversion rates of advertisements in real time and automatically optimizes effective advertisements. The advertising department, for example, develops a system that tracks click rates and conversion rates of advertisements in real time and automatically optimizes effective advertisements. For example, advertisements with high click rates are preferentially displayed. This makes it possible to track click rates and conversion rates of advertisements in real time and automatically optimize effective advertisements.

[0047] The advertising department can sell advertising space in an auction format, allowing advertisers to acquire advertising space through competitive bidding. The advertising department, for example, develops a system that sells advertising space in an auction format, allowing advertisers to acquire advertising space through competitive bidding. For example, advertisers set bid prices, and the highest bidder acquires the advertising space. This allows advertising space to be sold in an auction format, allowing advertisers to acquire advertising space through competitive bidding.

[0048] The advertising unit can diversify the types of advertisements and introduce new ad formats that attract users' attention, such as video advertisements and interactive advertisements. The advertising unit, for example, develops a system that diversifies the types of advertisements and introduces new ad formats that attract users' attention, such as video advertisements and interactive advertisements. For example, the advertising unit displays video advertisements and interactive advertisements. This allows the advertising unit to diversify the types of advertisements and introduce new ad formats that attract users' attention.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The prompt introduction unit can automatically suggest highly relevant prompts based on the user's past search history. For example, if the user has searched for many travel-related prompts in the past, new travel-related prompts will be displayed preferentially. Also, if the user shows interest in a particular topic, prompts related to that topic can be introduced intensively. Furthermore, by analyzing the user's search history and suggesting unused prompts, new ideas and perspectives can be provided.

[0051] The prompt introduction unit can provide region-specific prompts based on the user's geographic location information. For example, if the user is in a specific city, the prompt introduction unit can present prompts containing tourist information and event information related to that city. Providing prompts based on the local culture and customs also allows the user to obtain information rooted in the region. Furthermore, the geographic location information can be used to provide region-specific special offers and campaign information.

[0052] The prompt introduction unit can prioritize unused prompts based on the user's past prompt usage history. For example, it can analyze prompts the user has used in the past and display highly relevant prompts that the user has not yet used. Also, if the user is biased toward a particular category, it can provide new perspectives and ideas by suggesting prompts from other categories. Furthermore, suggesting unused prompts can attract the user's interest and create new usage opportunities.

[0053] The prompt introduction section can display relevant news articles and blog posts along with the prompt based on the user's interests. For example, if a user searches for a business-related prompt, it can display the latest business news and expert blog posts. Alternatively, if a user searches for a travel-related prompt, it can provide travel guides and reviews of tourist spots. Furthermore, the related news and blog posts can help the user better understand and utilize the prompt.

[0054] The prompt introduction unit can continuously improve the content of prompts based on user feedback. For example, when a user provides ratings or comments on a prompt, the prompt can be improved based on that feedback. The prompt introduction unit can also improve the overall quality of the prompts by analyzing user feedback and identifying common areas for improvement. Furthermore, by providing prompts that reflect user feedback, user satisfaction can be increased.

[0055] The processing flow of the first embodiment will be briefly explained below.

[0056] Step 1: The prompt introduction section introduces prompts necessary for utilizing the generative AI. For example, it introduces prompts for planning a trip or for assisting in writing a business email. It also provides instructions for the generative AI to generate appropriate responses. Step 2: The login section manages logins using the user's account. For example, it manages logins using accounts such as YID, SBID, and LINE. It is also possible to provide a login function using LINEID. Step 3: The rewards department rewards users based on the number of prompts used or page views. For example, if a user posts a prompt and many users use it, the user is rewarded. It can also provide a points system or cash rewards. Step 4: The trading unit manages the buying and selling of prompt ideas. For example, it manages that users sell prompt ideas to other users. In addition, SB can receive a certain amount of sales commission. Step 5: The advertising department places ads. For example, they display ads related to the prompt page. They can also place banner ads, text ads, and video ads.

[0057] (Example 2) A web service according to an embodiment of the present invention is a system that introduces a set of prompts necessary for utilizing generative AI. This system helps people who are not yet able to effectively use generative AI to use it more conveniently. As a result, the web service provides a set of prompts for utilizing generative AI, and can help users effectively utilize generative AI.

[0058] A web service according to an embodiment includes a prompt introduction unit, a login unit, a reward unit, a buying and selling unit, and an advertising unit. The prompt introduction unit introduces prompts necessary for utilizing the generation AI. For example, the prompt introduction unit introduces prompts for planning a trip or prompts that assist in creating business emails. The prompt introduction unit also provides instructions for the generation AI to generate appropriate responses. The login unit manages logins using user accounts. For example, the login unit manages logins using accounts such as YID, SBID, and LINE. The login unit can also provide a login function using LINEID. The reward unit provides rewards based on the number of prompt usages and page views. For example, the reward unit pays rewards to posters when a posted prompt is used by many users. The reward unit can also provide a point system or cash rewards. The buying and selling unit manages the buying and selling of prompt ideas. For example, the buying and selling unit manages users' sales of prompt ideas to other users. The buying and selling unit can also allow the SB to receive a certain amount of sales commissions. The advertising unit places advertisements. For example, the advertising unit displays advertisements related to a page of a prompt collection. The advertising unit can also post banner ads, text ads, and video ads. This allows the web service according to the embodiment to support the utilization of generative AI and enable users to post, introduce, and buy and sell prompts. For example, users can find prompts for utilizing generative AI and share knowledge and ideas through the posting and buying and selling of prompts.

[0059] The prompt introduction unit uses generation AI to perform sentiment analysis on each prompt and can evaluate the effectiveness of the prompt based on the intensity and type of emotion. For example, the prompt introduction unit performs sentiment analysis on each prompt and quantifies the intensity and type of emotion based on the sentiment score. For example, emotions such as joy, sadness, and surprise are expressed numerically, and prompts with high specific sentiment scores are preferentially stored in the database. This allows the effectiveness of the prompt to be evaluated based on sentiment analysis.

[0060] The prompt introduction unit can track the usage history of prompts and develop an algorithm that automatically recommends the most effective prompts. For example, the prompt introduction unit stores the usage history of prompts in a database and develops an algorithm that automatically recommends the most effective prompts based on that data. For example, the prompts are ranked based on frequency of use and user ratings. This makes it possible to recommend the most effective prompts based on the usage history.

[0061] The prompt introduction unit can add a function to automatically optimize the content of the prompt and convert it into a form that is most suitable for the user's purpose. For example, the prompt introduction unit develops a system that analyzes the content of the prompt and automatically converts it into a form that is most suitable for the user's purpose. For example, the prompt for a business email can be customized to suit a specific industry or job type. This allows the prompt content to be optimized for the user's purpose.

[0062] The prompt introduction unit can add multimodal prompts, including images and audio data, to the prompt collection, allowing the generation AI to be utilized based on visual and audio information as well. For example, the prompt introduction unit can add image and audio data to the prompt collection, allowing the generation AI to be utilized based on visual and audio information. For example, it can provide images and audio explanations related to the prompt. This allows the generation AI to be utilized using visual and audio information.

[0063] The prompt introduction unit can collect prompts created by experts in different industries and fields, allowing the user to select prompts from a variety of perspectives. The prompt introduction unit can, for example, collect prompts created by experts in different industries and fields, allowing the user to select prompts from a variety of perspectives. For example, it can provide prompts related to technology, design, and marketing. This allows the user to select prompts from a variety of perspectives.

[0064] The login unit can use generation AI to analyze the user's past usage history at the time of login and recommend individually optimized prompts. For example, the login unit will develop a system that uses generation AI to analyze the user's past usage history at the time of login and recommend individually optimized prompts. For example, the prompts will be customized based on past frequency of use and evaluations. This will make it possible to recommend optimal prompts based on the user's past usage history.

[0065] The login unit can add a function to automatically filter prompts according to the user's expertise and interests based on the login information. The login unit develops a system that automatically filters prompts according to the user's expertise and interests based on, for example, the login information. For example, the login unit customizes prompts based on the user's profile information. This makes it possible to filter prompts according to the user's expertise and interests.

[0066] The login unit can use the emotion estimation function at the time of login to grasp the user's current emotional state and propose prompts accordingly. For example, the login unit will develop a system that uses the emotion estimation function at the time of login to grasp the user's current emotional state. For example, it will analyze the user's facial expressions and voice and calculate an emotion score. This will enable it to propose the optimal prompt according to the user's emotional state.

[0067] The login unit can improve user convenience by integrating different SNS accounts and enabling login from multiple platforms. The login unit develops a system that integrates different SNS accounts and enables login from multiple platforms, for example, integrating Facebook, Twitter, and Google accounts. This enables login from multiple platforms and improves user convenience.

[0068] The login unit can provide a customized dashboard based on the user's profile information at the time of login. The login unit develops a system that provides a customized dashboard based on the user's profile information at the time of login, for example. For example, the login unit displays a prompt based on the user's interests and concerns. This makes it possible to provide a customized dashboard based on the user's profile information.

[0069] The login unit can use the emotion estimation function to analyze the user's emotions at the time of login and display a welcome message to elicit positive emotions. The login unit, for example, develops a system that uses the emotion estimation function to analyze the user's emotions at the time of login. For example, the login unit analyzes the user's facial expressions and voice and calculates an emotion score. This makes it possible to display a positive welcome message according to the user's emotions.

[0070] The reward unit can introduce a system that tracks the usage of prompts in real time and dynamically adjusts rewards according to the frequency of use and effectiveness. For example, the reward unit develops a system that tracks the usage of prompts in real time and dynamically adjusts rewards according to the frequency of use and effectiveness. For example, a high reward is provided for a prompt that is used frequently. This allows the reward to be dynamically adjusted according to the usage of the prompt.

[0071] The reward unit can automatically evaluate the quality of posted prompts and provide bonus rewards for high-quality prompts. The reward unit, for example, develops a system that automatically evaluates the quality of posted prompts and provides bonus rewards for high-quality prompts. For example, the reward unit evaluates prompts based on user ratings and frequency of use. This makes it possible to provide bonus rewards for high-quality prompts.

[0072] The reward unit can add a function that allows prompt posters to receive feedback from other users and promote the improvement of prompts. For example, the reward unit develops a system that adds a function that allows prompt posters to receive feedback from other users and promotes the improvement of prompts. For example, the reward unit improves prompts based on user comments and ratings. This makes it possible to promote the improvement of prompts by receiving feedback from other users.

[0073] The rewards department may develop a system that provides rewards for different categories or uses to encourage prompt submissions in specific fields. For example, the rewards department may provide different rewards for technical, design, and marketing prompts to encourage prompt submissions in specific fields.

[0074] The reward unit can use the emotion estimation function to analyze the user's emotional response to the posted prompt and provide additional rewards for prompts that elicit a positive response. The reward unit, for example, develops a system that uses the emotion estimation function to analyze the user's emotional response to the posted prompt. For example, the reward unit analyzes the user's facial expressions and voice and calculates an emotion score. This makes it possible to provide additional rewards for prompts that elicit a positive response.

[0075] The buying and selling department uses a generation AI to perform sentiment analysis on prompts to be bought and sold, and can prioritize displaying prompts with high emotional value. The buying and selling department will develop a system that, for example, performs sentiment analysis on prompts to be bought and sold, and prioritizes displaying prompts with high emotional value. For example, it will rank prompts based on the user's sentiment score. This will enable prompts with high emotional value to be prioritized.

[0076] The buying and selling unit can automatically evaluate the quality of prompts being bought and sold, and set premium prices for high-quality prompts. The buying and selling unit, for example, develops a system that automatically evaluates the quality of prompts being bought and sold, and sets premium prices for high-quality prompts. For example, the system evaluates prompts based on user ratings and frequency of use. This allows premium prices to be set for high-quality prompts.

[0077] The buying and selling department can expand the buying and selling of prompt ideas internationally and enable the trading of prompts in different languages ​​and cultural spheres. For example, the buying and selling department develops a system that expands the buying and selling of prompt ideas internationally and enables the trading of prompts in different languages ​​and cultural spheres. For example, the system can support multiple languages ​​such as English, French, and Chinese. This allows the trading of prompts in different languages ​​and cultural spheres.

[0078] The Buying and Selling Department can introduce bundle sales or subscription models when buying and selling prompt ideas, providing users with a variety of purchasing options. For example, the Buying and Selling Department can introduce bundle sales when buying and selling prompt ideas, and develop a system for selling multiple prompts as a set. For example, prompts related to a specific theme can be sold together. This allows users to have a variety of purchasing options.

[0079] The buying and selling unit can use the emotion estimation function to analyze the user's emotional response to the prompts being bought and sold, and preferentially display prompts that elicit a positive response. The buying and selling unit, for example, develops a system that uses the emotion estimation function to analyze the user's emotional response to the prompts being bought and sold. For example, the system analyzes the user's facial expressions and voice and calculates an emotion score. This allows the system to preferentially display prompts that elicit a positive response.

[0080] The advertising department can use generation AI to customize the content of advertisements based on the user's interests and concerns, thereby maximizing advertising effectiveness. For example, the advertising department develops a system that uses generation AI to customize the content of advertisements based on the user's interests and concerns. For example, the advertising department personalizes advertisements based on the user's browsing history and search history. This makes it possible to maximize advertising effectiveness based on the user's interests and concerns.

[0081] The advertising department can introduce a system that tracks click rates and conversion rates of advertisements in real time and automatically optimizes effective advertisements. The advertising department, for example, develops a system that tracks click rates and conversion rates of advertisements in real time and automatically optimizes effective advertisements. For example, advertisements with high click rates are preferentially displayed. This makes it possible to track click rates and conversion rates of advertisements in real time and automatically optimize effective advertisements.

[0082] The advertising department can sell advertising space in an auction format, allowing advertisers to acquire advertising space through competitive bidding. The advertising department, for example, develops a system that sells advertising space in an auction format, allowing advertisers to acquire advertising space through competitive bidding. For example, advertisers set bid prices, and the highest bidder acquires the advertising space. This allows advertising space to be sold in an auction format, allowing advertisers to acquire advertising space through competitive bidding.

[0083] The advertising unit can diversify the types of advertisements and introduce new ad formats that attract users' attention, such as video advertisements and interactive advertisements. The advertising unit, for example, develops a system that diversifies the types of advertisements and introduces new ad formats that attract users' attention, such as video advertisements and interactive advertisements. For example, the advertising unit displays video advertisements and interactive advertisements. This allows the advertising unit to diversify the types of advertisements and introduce new ad formats that attract users' attention.

[0084] The advertising department can use the emotion estimation function to analyze the user's emotional response to the advertisement and preferentially display advertisements that elicit a positive response. The advertising department, for example, develops a system that uses the emotion estimation function to analyze the user's emotional response to the advertisement. For example, the system analyzes the user's facial expressions and voice and calculates an emotion score. This allows advertisements that elicit a positive response to be preferentially displayed.

[0085] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0086] The prompt introduction unit can automatically suggest highly relevant prompts based on the user's past search history. For example, if the user has searched for many travel-related prompts in the past, new travel-related prompts will be displayed preferentially. Also, if the user shows interest in a particular topic, prompts related to that topic can be introduced intensively. Furthermore, by analyzing the user's search history and suggesting unused prompts, new ideas and perspectives can be provided.

[0087] The prompt introduction unit can estimate the user's emotions and filter prompts based on the estimated emotions. For example, if the user is feeling stressed, prompts themed around relaxation and healing are displayed preferentially. Also, if the user is excited, prompts that encourage creative activities can be suggested. Furthermore, prompts that elicit positive emotions can be selected according to the user's emotional state, improving the user experience.

[0088] The prompt introduction unit can provide region-specific prompts based on the user's geographic location information. For example, if the user is in a specific city, the prompt introduction unit can present prompts containing tourist information and event information related to that city. Providing prompts based on the local culture and customs also allows the user to obtain information rooted in the region. Furthermore, the geographic location information can be used to provide region-specific special offers and campaign information.

[0089] The prompt introduction unit can estimate the user's emotions and dynamically change the display order of prompts based on the estimated emotions. For example, if the user is sad, prompts themed around encouragement and comfort can be displayed first. On the other hand, if the user is happy, prompts that elicit more positive emotions can be displayed first. Furthermore, prompts that encourage a change in emotions can be selected according to the user's emotional state, enriching the user's experience.

[0090] The prompt introduction unit can prioritize unused prompts based on the user's past prompt usage history. For example, it can analyze prompts the user has used in the past and display highly relevant prompts that the user has not yet used. Also, if the user is biased toward a particular category, it can provide new perspectives and ideas by suggesting prompts from other categories. Furthermore, suggesting unused prompts can attract the user's interest and create new usage opportunities.

[0091] The prompt introduction unit can estimate the user's emotions and customize the content of the prompts based on the estimated emotions. For example, if the user is nervous, the prompts can be provided with words and expressions that have a relaxing effect. Alternatively, if the user is excited, the prompts can be suggested with energetic expressions. Furthermore, the tone and style of the prompts can be adjusted depending on the user's emotional state to provide a more personalized experience.

[0092] The prompt introduction section can display relevant news articles and blog posts along with the prompt based on the user's interests. For example, if a user searches for a business-related prompt, it can display the latest business news and expert blog posts. Alternatively, if a user searches for a travel-related prompt, it can provide travel guides and reviews of tourist spots. Furthermore, the related news and blog posts can help the user better understand and utilize the prompt.

[0093] The prompt introduction unit can estimate the user's emotions and adjust the difficulty of the prompts based on the estimated emotions. For example, if the user is tired, it can provide easy and relaxing prompts. Alternatively, if the user is concentrating, it can suggest more challenging and thought-provoking prompts. Furthermore, it can dynamically change the difficulty of the prompts depending on the user's emotional state to optimize the user's experience.

[0094] The prompt introduction unit can continuously improve the content of prompts based on user feedback. For example, when a user provides ratings or comments on a prompt, the prompt can be improved based on that feedback. The prompt introduction unit can also improve the overall quality of the prompts by analyzing user feedback and identifying common areas for improvement. Furthermore, by providing prompts that reflect user feedback, user satisfaction can be increased.

[0095] The prompt introduction unit can estimate the user's emotions and adjust the timing of prompt display based on the estimated emotions. For example, if the user is depressed, the prompt introduction unit can display a prompt with an encouraging message. Also, if the user is excited, the prompt introduction unit can provide an actionable prompt. Furthermore, the timing of prompt display can be optimized according to the user's emotional state to improve the user experience.

[0096] The processing flow of the second embodiment will be briefly explained below.

[0097] Step 1: The prompt introduction section introduces prompts necessary for utilizing the generative AI. For example, it introduces prompts for planning a trip or for assisting in writing a business email. It also provides instructions for the generative AI to generate appropriate responses. Step 2: The login section manages logins using the user's account. For example, it manages logins using accounts such as YID, SBID, and LINE. It is also possible to provide a login function using LINEID. Step 3: The rewards department rewards users based on the number of prompts used or page views. For example, if a user posts a prompt and many users use it, the user is rewarded. It can also provide a points system or cash rewards. Step 4: The trading unit manages the buying and selling of prompt ideas. For example, it manages that users sell prompt ideas to other users. In addition, SB can receive a certain amount of sales commission. Step 5: The advertising department places ads. For example, they display ads related to the prompt page. They can also place banner ads, text ads, and video ads.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0111] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0126] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0132] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0142] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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).

[0151] 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.

[0152] 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."

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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]

[0165] 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 prompt introduction section introduces the prompts necessary for utilizing generative AI, and A login section that manages logins with user accounts; a reward unit that provides rewards according to the number of times the prompt is used or the number of times a page is viewed; A trading department that manages the buying and selling of prompt ideas; and an advertising department that places advertisements. A system characterized by:

2. The prompt introduction unit The generative AI performs a sentiment analysis on each prompt, and evaluates the effectiveness of the prompt based on the intensity and type of emotion.

2. The system of claim 1.

3. The prompt introduction unit Add multimodal prompts, including images and audio data, to the prompt collection, enabling the AI ​​to utilize visual and auditory information.

2. The system of claim 1.

4. The login unit The emotional state of the user is grasped at the time of login, and the prompt is proposed accordingly.

2. The system of claim 1.

5. The reward unit: Automatically assess the quality of the posted prompts and provide bonus rewards for high-quality prompts.

2. The system of claim 1.

6. The buying and selling department The generating AI is used to perform sentiment analysis on the prompts being traded, and the prompts with high emotional value are preferentially displayed.

2. The system of claim 1.

7. The advertising department The display content of the advertisement is customized based on the user's interests using the generation AI, thereby maximizing the effectiveness of the advertisement.

2. The system of claim 1.

8. The advertising department Analyzing the user's emotional response to advertisements and preferentially displaying advertisements that elicit positive responses 2. The system of claim 1.

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