System

Abstract

An object of a system according to an embodiment is to provide a hint and a way of thinking for a user to derive an answer by himself / herself.SOLUTION: A system according to an embodiment includes a hint provider, a concept presenter, and a self-evaluation promoter. The hint providing unit provides a hint. The concept presenting unit presents a concept. The self-evaluation promotion unit promotes the self-evaluation.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, relying on generative AI can rob users of their thinking and creativity.

[0005] The system according to the embodiment aims to provide hints and ideas to help users find answers on their own. [Means for solving the problem]

[0006] The system according to the embodiment includes a hint providing unit, a way of thinking presenting unit, and a self-assessment promoting unit. The hint providing unit provides hints. The way of thinking presenting unit presents ways of thinking. The self-assessment promoting unit promotes self-assessment. [Effects of the Invention]

[0007] The system according to the embodiment can provide hints and ideas to help the user find the answer by himself. [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) An application according to an embodiment of the present invention solves the problem of people who cannot live without generative AI-related services, but who are troubled by this and who end up losing their ability to think and be creative due to excessive reliance on generative AI. This application provides hints and ideas to help users find answers themselves, and aims to support the user's thought process rather than having the generative AI directly generate answers. This allows the application to utilize the user's ability to think and be creative to solve problems.

[0029] An application according to an embodiment includes a hint providing unit, a mindset suggestion unit, and a self-assessment promotion unit. The hint providing unit provides hints to a user. For example, if a user inputs "I want to think of a new business idea," the hint providing unit provides hints such as "Research market needs" and "Analyze competitors." If a user inputs "Project progress is behind schedule," the hint providing unit provides hints such as "Review task priorities" and "Strengthen communication with team members." If a user inputs "I'm ready for a presentation," the hint providing unit provides hints such as "Check the consistency of the content" and "Add visual elements." The mindset suggestion unit suggests mindsets to a user. For example, if a user inputs "I want to come up with a new design," the mindset suggestion unit suggests mindsets such as "Think from a different perspective" and "Try using existing designs as a reference." If a user inputs "I want to learn programming," the mindset suggestion unit suggests mindsets such as "Understand basic concepts" and "Try writing actual code." If a user inputs "Project progress is behind schedule," the mindset suggestion unit suggests mindsets such as "Review task priorities" and "Strengthen communication with team members." The self-assessment promotion unit promotes the user's self-assessment. For example, if the user inputs "I'm ready for my presentation," the self-assessment promotion unit provides feedback such as "Check the consistency of the content" and "Add visual elements." If the user inputs "I want to come up with a new design," the self-assessment promotion unit provides feedback such as "Think from a different perspective" and "Take reference to existing designs." If the user inputs "I want to learn programming," the self-assessment promotion unit provides feedback such as "Understand basic concepts" and "Try writing some actual code." In this way, the application according to the embodiment allows the user to demonstrate their own thinking ability and creativity and solve problems.

[0030] The hint providing unit can analyze the user's past behavior history and preferences and provide individually customized hints. The hint providing unit provides related hints based on, for example, keywords searched for by the user in the past or pages viewed by the user. For example, a user who has read many marketing-related articles in the past is provided with hints about marketing strategies. The hint providing unit also analyzes the history of problems the user has solved in the past and provides customized hints for similar problems. For example, a user who has solved a project management problem in the past is provided with specific hints about project management. The hint providing unit also analyzes the user's preferences and provides individually customized hints. For example, a user who is interested in creative design is provided with hints based on design thinking. This makes it possible to provide more appropriate hints to the user.

[0031] The hint providing unit can provide hints for problems entered by a user, including citations from related academic papers and specialized books. For example, the hint providing unit searches for academic papers related to the problem entered by the user and extracts important citations from them to provide as hints. For example, for a problem about marketing strategy, the hint providing unit cites the latest marketing theory. The hint providing unit also analyzes the contents of specialized books and provides hints by citing appropriate parts for the problem entered by the user. For example, for a problem about project management, the hint providing unit provides citations from specialized books on project management. The hint providing unit also utilizes a database of academic papers and specialized books to automatically extract the most relevant citations for the problem entered by the user and provide hints. For example, for a problem about design thinking, the hint providing unit provides citations from specialized books on design thinking. This makes it possible to provide highly reliable information to the user.

[0032] The hint providing unit can provide hints not only in text format but also in audio or video format to suit the user's learning style. For example, the hint providing unit provides audio format hints in addition to text format hints. For example, if the user prefers audio explanations, an audio guide is provided. The hint providing unit also provides video format hints to make the content easier to understand visually. For example, if the user prefers visual content, a video tutorial is provided. The hint providing unit also provides hints in any of text, audio, or video format to suit the user's learning style. For example, if the user is a visual learner, video format hints are preferentially provided. This makes it possible to provide hints that suit the user's learning style.

[0033] The hint providing unit can aggregate hints from experts in different fields and provide approaches from multiple perspectives. For example, the hint providing unit aggregates hints from experts in different fields and provides them to the user. For example, hints from experts in marketing, design, and technology are provided on a single platform. The hint providing unit also provides a multifaceted approach to a problem the user is facing based on the opinions of multiple experts. For example, for a project management problem, hints from experts in management, communication, and technology are provided. The hint providing unit also integrates hints from experts in different fields to enable the user to solve the problem from various perspectives. For example, for a creative design problem, hints from experts in design, psychology, and marketing are provided. This makes it possible to provide the user with hints from multiple perspectives.

[0034] The idea suggestion unit can monitor the user's problem-solving process in real time and suggest ideas at the appropriate time. For example, as the user proceeds with the problem-solving process, the idea suggestion unit monitors the progress in real time and suggests ideas at the appropriate time. For example, it suggests a new approach when the user hits an impasse. The idea suggestion unit also analyzes the user's behavioral data and suggests ideas at the optimal time in the problem-solving process. For example, it suggests the timing to review task priorities. The idea suggestion unit also builds a system that tracks the user's problem-solving process in real time and suggests ideas at the appropriate time. For example, it suggests an efficient method when progress is slow. This makes it possible to support the user's problem-solving process and provide effective ideas.

[0035] The idea suggestion unit can analyze cases of problem solving that have been successful in the past by the user and present ideas based on them. For example, the idea suggestion unit stores cases of problem solving that have been successful in the past by the user in a database and presents ideas based on that data. For example, it proposes an approach that references past success cases. The idea suggestion unit also analyzes the user's past success cases and presents similar ideas for similar problems. For example, it re-proposes a method that has been successful in project management in the past. The idea suggestion unit also builds a system that presents optimal ideas for problems that the user is facing based on past success cases. For example, it provides ideas that reference the methods of successful projects. In this way, it is possible to present effective ideas based on the user's past success cases.

[0036] The idea presentation unit can present ideas in the form of an interactive simulation or game, allowing users to learn while having fun. The idea presentation unit, for example, uses an interactive simulation to allow users to learn ideas while having fun. For example, it provides a problem-solving process as a simulation game. The idea presentation unit also presents ideas in the form of a game, allowing users to learn while having fun. For example, it provides a game to review task priorities. The idea presentation unit also allows users to learn ideas in a practical way through interactive simulations or games. For example, it provides a project management simulation game. This allows users to learn while having fun.

[0037] The idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from diverse perspectives. For example, the idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from diverse perspectives. For example, it can introduce problem-solving methods from Asia, Europe, and America. The idea presentation unit can also collect opinions from experts from different cultures and regions, and provide users with ideas from diverse perspectives. For example, it can provide advice from experts from different cultures. The idea presentation unit can also introduce problem-solving cases from different cultures and regions, and enable users to solve problems from diverse perspectives. For example, it can provide ideas based on success stories from different regions. This makes it possible to provide users with ideas from diverse perspectives.

[0038] The self-assessment promotion unit can quantitatively evaluate the user's progress and provide feedback in the form of specific numerical values ​​and graphs. The self-assessment promotion unit, for example, quantitatively evaluates the user's progress and provides feedback in the form of specific numerical values ​​and graphs. For example, it displays the task completion rate and the passage of time in a graph. The self-assessment promotion unit also analyzes the user's progress data and provides feedback in the form of specific numerical values ​​and graphs. For example, it displays the progress of a project in a graph. The self-assessment promotion unit also builds a system for quantitatively evaluating the user's progress and provides feedback in the form of specific numerical values ​​and graphs. For example, it quantifies learning progress and displays it in a graph. This makes it easier to visually grasp the user's progress.

[0039] The self-assessment promotion unit can monitor the degree of achievement of goals set by the user in real time and provide feedback as appropriate. The self-assessment promotion unit, for example, builds a system that monitors the degree of achievement of goals set by the user in real time and provides feedback as appropriate. For example, it displays the goal achievement rate in real time. The self-assessment promotion unit also analyzes the user's degree of goal achievement in real time and provides feedback as appropriate. For example, it displays progress toward the goal in real time. The self-assessment promotion unit also develops a system that monitors the degree of achievement of goals set by the user in real time and provides feedback. For example, it provides advice toward achieving the goal in real time. This allows the user to grasp their progress toward achieving their goal in real time.

[0040] The self-assessment promotion unit can provide a community function that allows users to share self-assessment feedback with other users and evaluate each other. The self-assessment promotion unit, for example, builds a system that provides a community function that allows users to share self-assessment feedback with other users and evaluate each other. For example, a bulletin board is provided for sharing feedback. The self-assessment promotion unit also provides a community function that allows users to share self-assessment feedback with other users and evaluate each other. For example, a function is added to comment on and evaluate feedback. The self-assessment promotion unit also provides a community function that allows users to share self-assessment feedback with other users and evaluate each other, thereby improving user motivation. For example, an evaluation score for feedback is displayed. This allows users to evaluate each other and improve their motivation.

[0041] The self-assessment promotion unit can reflect the results of the self-assessment in the user's long-term growth plan and suggest the next step. The self-assessment promotion unit, for example, builds a system that reflects the results of the self-assessment in the user's long-term growth plan and suggests the next step. For example, it suggests the next skills or knowledge to be learned. The self-assessment promotion unit also creates a long-term growth plan based on the user's self-assessment results and suggests the next step. For example, it provides a specific action plan for achieving the goal. The self-assessment promotion unit also develops a system that reflects the results of the self-assessment in the long-term growth plan and enables the user to clearly understand the next step. For example, it suggests tasks based on the growth plan. This makes it possible to support the user's long-term growth.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The hint providing unit can provide hints for problems entered by a user, including citations from related academic papers and specialized books. For example, it searches for academic papers related to the problem entered by the user and extracts important citations from them to provide as hints. For example, it cites the latest marketing theory for a problem related to marketing strategy. The hint providing unit can also analyze the contents of specialized books and provide hints by citing appropriate parts for the problem entered by the user. For example, it provides citations from specialized books on project management for a problem related to project management. The hint providing unit can also utilize a database of academic papers and specialized books to automatically extract the most relevant citations for the problem entered by the user and provide hints. For example, it provides citations from specialized books on design thinking for a problem related to design thinking. This makes it possible to provide highly reliable information to the user.

[0044] The hint providing unit can provide hints not only in text format but also in audio or video format to suit the user's learning style. For example, in addition to text format hints, audio format hints are also provided. For example, if the user prefers audio explanations, an audio guide is provided. The hint providing unit can also provide video format hints to make the content easier to understand visually. For example, if the user prefers visual content, a video tutorial is provided. The hint providing unit can also provide hints in any of text, audio, or video format to suit the user's learning style. For example, if the user is a visual learner, video format hints are preferentially provided. This makes it possible to provide hints that suit the user's learning style.

[0045] The hint providing unit can aggregate hints from experts in different fields and provide approaches from multiple perspectives. For example, hints from experts in different fields can be aggregated and provided to the user. For example, hints from experts in marketing, design, and technology can be provided on a single platform. The hint providing unit also provides a multifaceted approach to problems faced by the user based on the opinions of multiple experts. For example, for a project management problem, hints from experts in management, communication, and technology can be provided. The hint providing unit also integrates hints from experts in different fields to enable the user to solve problems from various perspectives. For example, for a creative design problem, hints from experts in design, psychology, and marketing can be provided. This makes it possible to provide the user with hints from multiple perspectives.

[0046] The idea suggestion unit can monitor the user's problem-solving process in real time and suggest ideas at the appropriate time. For example, as the user proceeds with the problem-solving process, it can monitor the progress in real time and suggest ideas at the appropriate time. For example, it can suggest a new approach when the user is stuck. The idea suggestion unit also analyzes the user's behavioral data and suggests ideas at the optimal time in the problem-solving process. For example, it can suggest the timing to review task priorities. The idea suggestion unit can also build a system that tracks the user's problem-solving process in real time and suggests ideas at the appropriate time. For example, it can suggest an efficient method when progress is slow. This makes it possible to support the user's problem-solving process and provide effective ideas.

[0047] The idea suggestion unit can analyze cases of problem solving that have been successful in the past by the user and present ideas based on them. For example, it can store cases of problem solving that have been successful in the past by the user in a database and present ideas based on that data. For example, it can propose an approach that references past success cases. The idea suggestion unit can also analyze the user's past success cases and present similar ideas for similar problems. For example, it can re-propose a method that has been successful in project management in the past. The idea suggestion unit can also build a system that presents optimal ideas for problems that the user is facing based on past success cases. For example, it can present ideas that reference the methods of successful projects. This makes it possible to present effective ideas based on the user's past success cases.

[0048] The idea presentation unit can present ideas in the form of an interactive simulation or game, allowing users to learn while having fun. For example, an interactive simulation can be used to allow users to learn ideas while having fun. For example, a problem-solving process can be provided as a simulation game. The idea presentation unit can also present ideas in the form of a game, allowing users to learn while having fun. For example, a game can be provided to review task priorities. The idea presentation unit can also allow users to learn ideas in a practical way through interactive simulations or games. For example, a project management simulation game can be provided. This allows users to learn while having fun.

[0049] The idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can introduce problem-solving methods from Asia, Europe, and America. The idea presentation unit can also collect opinions from experts from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can provide advice from experts from different cultures. The idea presentation unit can also introduce problem-solving cases from different cultures and regions, and enable users to solve problems from a variety of perspectives. For example, it can provide ideas based on success stories from different regions. This makes it possible to provide users with ideas from a variety of perspectives.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The hint provider provides hints to the user. For example, if the user inputs "I want to think of a new business idea," the hint provider will provide hints such as "Research market needs" and "Conduct competitor analysis." If the user inputs "Project progress is behind schedule," the hint provider will provide hints such as "Review task priorities" and "Strengthen communication with team members." If the user inputs "I'm ready for my presentation," the hint provider will provide hints such as "Check the consistency of the content" and "Add visual elements." Step 2: The idea suggestion unit presents ideas to the user. For example, if the user inputs "I want to think of a new design," it will suggest ideas such as "Think from a different perspective" and "Use existing designs as a reference." If the user inputs "I want to learn programming," it will suggest ideas such as "Understand basic concepts" and "Try writing some actual code." If the user inputs "The project is behind schedule," it will suggest ideas such as "Reconsider task priorities" and "Strengthen communication with team members." Step 3: The self-assessment promotion unit encourages the user to self-assess. For example, if a user inputs "I'm ready for my presentation," it will provide feedback such as "Check the consistency of the content" and "Add visual elements." If a user inputs "I want to think of a new design," it will provide feedback such as "Think from a different perspective" and "Try using existing designs as reference." If a user inputs "I want to learn programming," it will provide feedback such as "Understand the basic concepts" and "Try writing some actual code."

[0052] (Example 2) An application according to an embodiment of the present invention solves the problem of people who cannot live without generative AI-related services, but who are troubled by this and who end up losing their ability to think and be creative due to excessive reliance on generative AI. This application provides hints and ideas to help users find answers themselves, and aims to support the user's thought process rather than having the generative AI directly generate answers. This allows the application to utilize the user's ability to think and be creative to solve problems.

[0053] An application according to an embodiment includes a hint providing unit, a mindset suggestion unit, and a self-assessment promotion unit. The hint providing unit provides hints to a user. For example, if a user inputs "I want to think of a new business idea," the hint providing unit provides hints such as "Research market needs" and "Analyze competitors." If a user inputs "Project progress is behind schedule," the hint providing unit provides hints such as "Review task priorities" and "Strengthen communication with team members." If a user inputs "I'm ready for a presentation," the hint providing unit provides hints such as "Check the consistency of the content" and "Add visual elements." The mindset suggestion unit suggests mindsets to a user. For example, if a user inputs "I want to come up with a new design," the mindset suggestion unit suggests mindsets such as "Think from a different perspective" and "Try using existing designs as a reference." If a user inputs "I want to learn programming," the mindset suggestion unit suggests mindsets such as "Understand basic concepts" and "Try writing actual code." If a user inputs "Project progress is behind schedule," the mindset suggestion unit suggests mindsets such as "Review task priorities" and "Strengthen communication with team members." The self-assessment promotion unit promotes the user's self-assessment. For example, if the user inputs "I'm ready for my presentation," the self-assessment promotion unit provides feedback such as "Check the consistency of the content" and "Add visual elements." If the user inputs "I want to come up with a new design," the self-assessment promotion unit provides feedback such as "Think from a different perspective" and "Take reference to existing designs." If the user inputs "I want to learn programming," the self-assessment promotion unit provides feedback such as "Understand basic concepts" and "Try writing some actual code." In this way, the application according to the embodiment allows the user to demonstrate their own thinking ability and creativity and solve problems.

[0054] The hint providing unit can analyze the user's past behavior history and preferences and provide individually customized hints. The hint providing unit provides related hints based on, for example, keywords searched for by the user in the past or pages viewed by the user. For example, a user who has read many marketing-related articles in the past is provided with hints about marketing strategies. The hint providing unit also analyzes the history of problems the user has solved in the past and provides customized hints for similar problems. For example, a user who has solved a project management problem in the past is provided with specific hints about project management. The hint providing unit also analyzes the user's preferences and provides individually customized hints. For example, a user who is interested in creative design is provided with hints based on design thinking. This makes it possible to provide more appropriate hints to the user.

[0055] The hint providing unit can provide hints for problems entered by a user, including citations from related academic papers and specialized books. For example, the hint providing unit searches for academic papers related to the problem entered by the user and extracts important citations from them to provide as hints. For example, for a problem about marketing strategy, the hint providing unit cites the latest marketing theory. The hint providing unit also analyzes the contents of specialized books and provides hints by citing appropriate parts for the problem entered by the user. For example, for a problem about project management, the hint providing unit provides citations from specialized books on project management. The hint providing unit also utilizes a database of academic papers and specialized books to automatically extract the most relevant citations for the problem entered by the user and provide hints. For example, for a problem about design thinking, the hint providing unit provides citations from specialized books on design thinking. This makes it possible to provide highly reliable information to the user.

[0056] The hint providing unit uses the emotion estimation function to provide hints according to the user's current emotional state, thereby reducing stress. The hint providing unit, for example, analyzes the user's facial expressions and voice to estimate the user's current emotional state. For example, if the user is feeling stressed, it provides a hint to help the user relax. The hint providing unit also uses the emotion estimation function to provide optimal hints when the user is relaxed. For example, when the user is in a positive emotional state, it provides a hint that encourages creative thinking. The hint providing unit also adjusts the content and expression of the hint according to the user's emotional state. For example, when the user is in a negative emotional state, it provides a hint that includes an encouraging message. This reduces the user's stress and provides more effective hints.

[0057] The hint providing unit can provide hints not only in text format but also in audio or video format to suit the user's learning style. For example, the hint providing unit provides audio format hints in addition to text format hints. For example, if the user prefers audio explanations, an audio guide is provided. The hint providing unit also provides video format hints to make the content easier to understand visually. For example, if the user prefers visual content, a video tutorial is provided. The hint providing unit also provides hints in any of text, audio, or video format to suit the user's learning style. For example, if the user is a visual learner, video format hints are preferentially provided. This makes it possible to provide hints that suit the user's learning style.

[0058] The hint providing unit can aggregate hints from experts in different fields and provide approaches from multiple perspectives. For example, the hint providing unit aggregates hints from experts in different fields and provides them to the user. For example, hints from experts in marketing, design, and technology are provided on a single platform. The hint providing unit also provides a multifaceted approach to a problem the user is facing based on the opinions of multiple experts. For example, for a project management problem, hints from experts in management, communication, and technology are provided. The hint providing unit also integrates hints from experts in different fields to enable the user to solve the problem from various perspectives. For example, for a creative design problem, hints from experts in design, psychology, and marketing are provided. This makes it possible to provide the user with hints from multiple perspectives.

[0059] The hint providing unit can use the emotion estimation function to analyze the emotional reaction of the user when receiving a hint and reflect the result in providing the next hint. For example, the hint providing unit can analyze the emotional reaction of the user when receiving a hint in real time and adjust the next hint to be provided based on the data. For example, hints with a large number of positive reactions can be provided preferentially. The hint providing unit can also use the emotion estimation function to analyze the user's emotional reaction and reflect the result in providing the next hint. For example, if there are a large number of negative reactions, the content and expression of the hint can be changed. The hint providing unit can also optimize the method of providing hints based on the user's emotional reaction data. For example, hints with a high emotion score can be provided preferentially, improving user satisfaction. This makes it possible to provide more effective hints based on the user's emotional reaction.

[0060] The idea suggestion unit can monitor the user's problem-solving process in real time and suggest ideas at the appropriate time. For example, as the user proceeds with the problem-solving process, the idea suggestion unit monitors the progress in real time and suggests ideas at the appropriate time. For example, it suggests a new approach when the user hits an impasse. The idea suggestion unit also analyzes the user's behavioral data and suggests ideas at the optimal time in the problem-solving process. For example, it suggests the timing to review task priorities. The idea suggestion unit also builds a system that tracks the user's problem-solving process in real time and suggests ideas at the appropriate time. For example, it suggests an efficient method when progress is slow. This makes it possible to support the user's problem-solving process and provide effective ideas.

[0061] The idea suggestion unit can analyze cases of problem solving that have been successful in the past by the user and present ideas based on them. For example, the idea suggestion unit stores cases of problem solving that have been successful in the past by the user in a database and presents ideas based on that data. For example, it proposes an approach that references past success cases. The idea suggestion unit also analyzes the user's past success cases and presents similar ideas for similar problems. For example, it re-proposes a method that has been successful in project management in the past. The idea suggestion unit also builds a system that presents optimal ideas for problems that the user is facing based on past success cases. For example, it provides ideas that reference the methods of successful projects. In this way, it is possible to present effective ideas based on the user's past success cases.

[0062] The idea suggestion unit uses the emotion estimation function to suggest ideas when the user is most relaxed, thereby promoting effective thinking. The idea suggestion unit, for example, monitors the user's emotional state in real time and suggests ideas when the user is most relaxed. For example, it suggests a new approach when stress is low. The idea suggestion unit also uses the emotion estimation function to identify when the user is relaxed and suggests the optimal idea at that time. For example, it suggests ideas that encourage creative thinking when the user is relaxed. The idea suggestion unit also builds a system that suggests ideas when the user is relaxed, based on the user's emotional data. For example, it suggests an efficient problem-solving method when the user is relaxed. This makes it possible to suggest effective ideas when the user is relaxed.

[0063] The idea presentation unit can present ideas in the form of an interactive simulation or game, allowing users to learn while having fun. The idea presentation unit, for example, uses an interactive simulation to allow users to learn ideas while having fun. For example, it provides a problem-solving process as a simulation game. The idea presentation unit also presents ideas in the form of a game, allowing users to learn while having fun. For example, it provides a game to review task priorities. The idea presentation unit also allows users to learn ideas in a practical way through interactive simulations or games. For example, it provides a project management simulation game. This allows users to learn while having fun.

[0064] The idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from diverse perspectives. For example, the idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from diverse perspectives. For example, it can introduce problem-solving methods from Asia, Europe, and America. The idea presentation unit can also collect opinions from experts from different cultures and regions, and provide users with ideas from diverse perspectives. For example, it can provide advice from experts from different cultures. The idea presentation unit can also introduce problem-solving cases from different cultures and regions, and enable users to solve problems from diverse perspectives. For example, it can provide ideas based on success stories from different regions. This makes it possible to provide users with ideas from diverse perspectives.

[0065] The idea presentation unit can use the emotion estimation function to analyze the emotional response of the user when receiving an idea and reflect the result in the next content to be presented. The idea presentation unit, for example, analyzes the emotional response of the user when receiving an idea in real time and adjusts the next content to be presented based on the data. For example, ideas with a high number of positive responses are provided preferentially. The idea presentation unit also uses the emotion estimation function to analyze the user's emotional response and reflect this in the next idea presentation. For example, if there are a lot of negative responses, the content or expression method of the idea is changed. The idea presentation unit also optimizes the method of presenting ideas based on the user's emotional response data. For example, ideas with a high emotion score are provided preferentially, improving user satisfaction. This makes it possible to provide more effective ideas based on the user's emotional response.

[0066] The self-assessment promotion unit can quantitatively evaluate the user's progress and provide feedback in the form of specific numerical values ​​and graphs. The self-assessment promotion unit, for example, quantitatively evaluates the user's progress and provides feedback in the form of specific numerical values ​​and graphs. For example, it displays the task completion rate and the passage of time in a graph. The self-assessment promotion unit also analyzes the user's progress data and provides feedback in the form of specific numerical values ​​and graphs. For example, it displays the progress of a project in a graph. The self-assessment promotion unit also builds a system for quantitatively evaluating the user's progress and provides feedback in the form of specific numerical values ​​and graphs. For example, it quantifies learning progress and displays it in a graph. This makes it easier to visually grasp the user's progress.

[0067] The self-assessment promotion unit can monitor the degree of achievement of goals set by the user in real time and provide feedback as appropriate. The self-assessment promotion unit, for example, builds a system that monitors the degree of achievement of goals set by the user in real time and provides feedback as appropriate. For example, it displays the goal achievement rate in real time. The self-assessment promotion unit also analyzes the user's degree of goal achievement in real time and provides feedback as appropriate. For example, it displays progress toward the goal in real time. The self-assessment promotion unit also develops a system that monitors the degree of achievement of goals set by the user in real time and provides feedback. For example, it provides advice toward achieving the goal in real time. This allows the user to grasp their progress toward achieving their goal in real time.

[0068] The self-assessment promotion unit uses the emotion estimation function to analyze the emotional state of the user when making a self-assessment and can emphasize positive feedback. The self-assessment promotion unit, for example, analyzes the emotional state of the user when making a self-assessment in real time and emphasizes positive feedback. For example, it highlights parts with high emotion scores. The self-assessment promotion unit also uses the emotion estimation function to build a system that analyzes the user's emotional state and emphasizes positive feedback. For example, it preferentially displays parts with strong positive emotions. The self-assessment promotion unit also develops a system that emphasizes positive feedback when making a self-assessment based on the user's emotional state. For example, it highlights parts with high emotion scores to improve the user's motivation. This makes it possible to emphasize the user's positive emotions and improve motivation.

[0069] The self-assessment promotion unit can provide a community function that allows users to share self-assessment feedback with other users and evaluate each other. The self-assessment promotion unit, for example, builds a system that provides a community function that allows users to share self-assessment feedback with other users and evaluate each other. For example, a bulletin board is provided for sharing feedback. The self-assessment promotion unit also provides a community function that allows users to share self-assessment feedback with other users and evaluate each other. For example, a function is added to comment on and evaluate feedback. The self-assessment promotion unit also provides a community function that allows users to share self-assessment feedback with other users and evaluate each other, thereby improving user motivation. For example, an evaluation score for feedback is displayed. This allows users to evaluate each other and improve their motivation.

[0070] The self-assessment promotion unit can reflect the results of the self-assessment in the user's long-term growth plan and suggest the next step. The self-assessment promotion unit, for example, builds a system that reflects the results of the self-assessment in the user's long-term growth plan and suggests the next step. For example, it suggests the next skills or knowledge to be learned. The self-assessment promotion unit also creates a long-term growth plan based on the user's self-assessment results and suggests the next step. For example, it provides a specific action plan for achieving the goal. The self-assessment promotion unit also develops a system that reflects the results of the self-assessment in the long-term growth plan and enables the user to clearly understand the next step. For example, it suggests tasks based on the growth plan. This makes it possible to support the user's long-term growth.

[0071] The self-evaluation promotion unit can use the emotion estimation function to analyze the emotional response of the user when they receive a self-evaluation and reflect it in the next feedback. The self-evaluation promotion unit, for example, analyzes the emotional response of the user when they receive a self-evaluation in real time and adjusts the next feedback based on the data. For example, it prioritizes providing feedback with a large number of positive responses. The self-evaluation promotion unit also uses the emotion estimation function to analyze the user's emotional response and reflect it in the next feedback. For example, if there are a large number of negative responses, it changes the content and expression of the feedback. The self-evaluation promotion unit also optimizes the method of providing feedback based on the user's emotional response data. For example, it prioritizes providing feedback with a high emotion score, improving user satisfaction. This makes it possible to provide more effective feedback based on the user's emotional response.

[0072] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0073] The hint providing unit can provide hints for problems entered by a user, including citations from related academic papers and specialized books. For example, it searches for academic papers related to the problem entered by the user and extracts important citations from them to provide as hints. For example, it cites the latest marketing theory for a problem related to marketing strategy. The hint providing unit can also analyze the contents of specialized books and provide hints by citing appropriate parts for the problem entered by the user. For example, it provides citations from specialized books on project management for a problem related to project management. The hint providing unit can also utilize a database of academic papers and specialized books to automatically extract the most relevant citations for the problem entered by the user and provide hints. For example, it provides citations from specialized books on design thinking for a problem related to design thinking. This makes it possible to provide highly reliable information to the user.

[0074] The hint providing unit uses the emotion estimation function to provide hints according to the user's current emotional state, thereby reducing stress. For example, the hint providing unit analyzes the user's facial expressions and voice to estimate the user's current emotional state. For example, if the user is feeling stressed, the hint providing unit provides a hint to help the user relax. The hint providing unit also uses the emotion estimation function to provide optimal hints when the user is relaxed. For example, when the user is in a positive emotional state, the hint providing unit provides a hint that encourages creative thinking. The hint providing unit also adjusts the content and expression of the hint according to the user's emotional state. For example, when the user is in a negative emotional state, the hint providing unit provides a hint that includes an encouraging message. This reduces the user's stress and provides more effective hints.

[0075] The hint providing unit can provide hints not only in text format but also in audio or video format to suit the user's learning style. For example, in addition to text format hints, audio format hints are also provided. For example, if the user prefers audio explanations, an audio guide is provided. The hint providing unit can also provide video format hints to make the content easier to understand visually. For example, if the user prefers visual content, a video tutorial is provided. The hint providing unit can also provide hints in any of text, audio, or video format to suit the user's learning style. For example, if the user is a visual learner, video format hints are preferentially provided. This makes it possible to provide hints that suit the user's learning style.

[0076] The hint providing unit can aggregate hints from experts in different fields and provide approaches from multiple perspectives. For example, hints from experts in different fields can be aggregated and provided to the user. For example, hints from experts in marketing, design, and technology can be provided on a single platform. The hint providing unit also provides a multifaceted approach to problems faced by the user based on the opinions of multiple experts. For example, for a project management problem, hints from experts in management, communication, and technology can be provided. The hint providing unit also integrates hints from experts in different fields to enable the user to solve problems from various perspectives. For example, for a creative design problem, hints from experts in design, psychology, and marketing can be provided. This makes it possible to provide the user with hints from multiple perspectives.

[0077] The hint providing unit can use the emotion estimation function to analyze the emotional response of the user when they receive a hint and reflect that in providing the next hint. For example, the emotional response of the user when they receive a hint can be analyzed in real time, and the next hint provided can be adjusted based on that data. For example, hints with a high number of positive responses can be provided preferentially. The hint providing unit can also use the emotion estimation function to analyze the user's emotional response and reflect that in providing the next hint. For example, if there are a lot of negative responses, the content and expression of the hint can be changed. The hint providing unit can also optimize the method of providing hints based on the user's emotional response data. For example, hints with a high emotion score can be provided preferentially, improving user satisfaction. This makes it possible to provide more effective hints based on the user's emotional response.

[0078] The idea suggestion unit can monitor the user's problem-solving process in real time and suggest ideas at the appropriate time. For example, as the user proceeds with the problem-solving process, it can monitor the progress in real time and suggest ideas at the appropriate time. For example, it can suggest a new approach when the user is stuck. The idea suggestion unit also analyzes the user's behavioral data and suggests ideas at the optimal time in the problem-solving process. For example, it can suggest the timing to review task priorities. The idea suggestion unit can also build a system that tracks the user's problem-solving process in real time and suggests ideas at the appropriate time. For example, it can suggest an efficient method when progress is slow. This makes it possible to support the user's problem-solving process and provide effective ideas.

[0079] The idea suggestion unit can analyze cases of problem solving that have been successful in the past by the user and present ideas based on them. For example, it can store cases of problem solving that have been successful in the past by the user in a database and present ideas based on that data. For example, it can propose an approach that references past success cases. The idea suggestion unit can also analyze the user's past success cases and present similar ideas for similar problems. For example, it can re-propose a method that has been successful in project management in the past. The idea suggestion unit can also build a system that presents optimal ideas for problems that the user is facing based on past success cases. For example, it can present ideas that reference the methods of successful projects. This makes it possible to present effective ideas based on the user's past success cases.

[0080] The idea suggestion unit can use the emotion estimation function to suggest ideas when the user is most relaxed, promoting effective thinking. For example, it can monitor the user's emotional state in real time and suggest ideas when the user is most relaxed. For example, it can suggest new approaches when stress is low. The idea suggestion unit can also use the emotion estimation function to identify when the user is relaxed and suggest the optimal ideas for that time. For example, it can suggest ideas that encourage creative thinking when the user is relaxed. The idea suggestion unit can also build a system that suggests ideas when the user is relaxed, based on the user's emotional data. For example, it can suggest efficient problem-solving methods when the user is relaxed. This makes it possible to suggest effective ideas when the user is relaxed.

[0081] The idea presentation unit can present ideas in the form of an interactive simulation or game, allowing users to learn while having fun. For example, an interactive simulation can be used to allow users to learn ideas while having fun. For example, a problem-solving process can be provided as a simulation game. The idea presentation unit can also present ideas in the form of a game, allowing users to learn while having fun. For example, a game can be provided to review task priorities. The idea presentation unit can also allow users to learn ideas in a practical way through interactive simulations or games. For example, a project management simulation game can be provided. This allows users to learn while having fun.

[0082] The idea presentation unit can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can introduce problem-solving approaches from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can introduce problem-solving methods from Asia, Europe, and America. The idea presentation unit can also collect opinions from experts from different cultures and regions, and provide users with ideas from a variety of perspectives. For example, it can provide advice from experts from different cultures. The idea presentation unit can also introduce problem-solving cases from different cultures and regions, and enable users to solve problems from a variety of perspectives. For example, it can provide ideas based on success stories from different regions. This makes it possible to provide users with ideas from a variety of perspectives.

[0083] The processing flow of the second embodiment will be briefly explained below.

[0084] Step 1: The hint provider provides hints to the user. For example, if the user inputs "I want to think of a new business idea," the hint provider will provide hints such as "Research market needs" and "Conduct competitor analysis." If the user inputs "Project progress is behind schedule," the hint provider will provide hints such as "Review task priorities" and "Strengthen communication with team members." If the user inputs "I'm ready for my presentation," the hint provider will provide hints such as "Check the consistency of the content" and "Add visual elements." Step 2: The idea suggestion unit presents ideas to the user. For example, if the user inputs "I want to think of a new design," it will suggest ideas such as "Think from a different perspective" and "Use existing designs as a reference." If the user inputs "I want to learn programming," it will suggest ideas such as "Understand basic concepts" and "Try writing some actual code." If the user inputs "The project is behind schedule," it will suggest ideas such as "Reconsider task priorities" and "Strengthen communication with team members." Step 3: The self-assessment promotion unit encourages the user to self-assess. For example, if a user inputs "I'm ready for my presentation," it will provide feedback such as "Check the consistency of the content" and "Add visual elements." If a user inputs "I want to think of a new design," it will provide feedback such as "Think from a different perspective" and "Try using existing designs as reference." If a user inputs "I want to learn programming," it will provide feedback such as "Understand the basic concepts" and "Try writing some actual code."

[0085] 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.

[0086] 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.

[0087] 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.

[0088] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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).

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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).

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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).

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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).

[0138] 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.

[0139] 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."

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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]

[0152] 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. This is an application that uses generative AI to provide hints and ideas to help users find answers on their own. a hint providing unit that provides a hint; an idea presentation unit that presents an idea; a self-assessment promotion unit that promotes self-assessment; A system characterized by:

2. The hint providing unit Analyzing the user's past behavior and preferences to provide personalized tips 2. The system of claim 1.

3. The hint providing unit Providing hints for the problem entered by the user, including citations from related academic papers and specialist books 2. The system of claim 1.

4. The hint providing unit Providing hints based on the user's current emotional state to reduce stress 2. The system of claim 1.

5. The hint providing unit Providing hints in audio and video formats, as well as text, to suit the user's learning style 2. The system of claim 1.

6. The hint providing unit We aggregate tips from experts in different fields to provide a multi-perspective approach.

2. The system of claim 1.

7. The hint providing unit Analyze the emotional response of the user when receiving the hint and reflect it in providing the next hint.

2. The system of claim 1.

8. The idea presentation unit Monitor the user's problem-solving process in real time and present ideas at the appropriate time.

2. The system of claim 1.

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