system

Abstract

The system according to this embodiment aims to demonstrate the skills of creators and to clearly distinguish them from illustrations generated by AI. [Solution] The system according to the embodiment comprises a submission unit, a certificate issuance unit, a link issuance unit, and a check unit. The submission unit receives the illustration creation process from the creator. The certificate issuance unit issues an author certificate based on the creation process submitted by the submission unit. The link issuance unit provides the author certificate issued by the certificate issuance unit in link format. The check unit determines whether the data was generated by a generation AI after reliable data has been collected.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, it is difficult to distinguish between an illustration created by a generative AI and an illustration created manually by a creator, and there is a risk that the relative value of the creator's technology will decrease.

[0005] The system according to the embodiment aims to prove the creator's technology and clarify the distinction from illustrations by generative AI.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a submission unit, a certificate issuance unit, a link issuance unit, and a checking unit. The submission unit receives the illustration creation process from the creator. The certificate issuance unit issues an author certificate based on the creation process submitted by the submission unit. The link issuance unit provides the author certificate issued by the certificate issuance unit in link format. The checking unit determines whether the data was generated by a generation AI after reliable data has been collected. [Effects of the Invention]

[0007] The system according to this embodiment can demonstrate the skills of the creator and clearly distinguish them from illustrations generated by AI. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of 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), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the 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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The creator certification system according to an embodiment of the present invention can generate high-quality illustrations in seconds using a generation AI, but there are concerns about a decrease in the relative value of the creator's skills. Therefore, this system issues authorship certificates upon submission of the creator's creation process. The creator certification system issues authorship certificates based on the submitted creation process after the creator submits the creation process of the illustration. This authorship certificate is issued in the form of a link and can be used for proof on social media. Furthermore, after reliable data has been collected, a generation AI check system will be developed to determine whether the work was generated by the generation AI. This system aims to create a world where creators are valued, with a view to accumulating and publishing the creator's creation process. For example, in the creator certification system, the creator submits the creation process of the illustration. In this case, the creator records and submits each step of the illustration in detail. For example, each step such as sketching, line drawing, coloring, and finishing is recorded. This makes the creator's skills and efforts visible. Next, the creator certification system issues authorship certificates based on the submitted creation process. This authorship certificate proves the creator's creation process and is issued in the form of a link. By sharing this link on social media, the creator can prove that their work was created by them. For example, by sharing a link on social media, creators can appeal to their followers to demonstrate the authenticity of their work. Furthermore, once reliable data has been collected, the creator verification system will develop a generative AI check system. This system will determine whether or not a work was generated by generative AI, thus proving that a creator's work was not generated by AI. For example, the generative AI check system can be used to verify that a submitted illustration was not generated by generative AI. This system aims to create a world where creators are valued, with a view to accumulating and publishing the creator's creative process. The creator's creative process is very beautiful and never gets boring to watch, so by publishing the creative process, the creator's skills and efforts will be appreciated.Furthermore, by making the creation process public, interaction with other creators and fans can be deepened, and the creator community is expected to be revitalized. In this way, the creator certification system can generate high-quality illustrations in seconds using generation AI, but it aims to prevent a decline in the relative value of creators' skills and create a world where creators are properly valued. Thus, the creator certification system can prove and evaluate the creation process of creators.

[0029] The creator certification system according to this embodiment comprises a submission unit, a certification issuance unit, a link issuance unit, and a checking unit. The submission unit receives the creator's illustration creation process. The submission unit allows the creator to record and submit each step of the illustration in detail. For example, the submission unit records each step such as sketching, line drawing, coloring, and finishing. The submission unit can also record the tools and techniques used by the creator. For example, the submission unit records information about the software and hardware used. Furthermore, the submission unit can record the creator's creation process in video format. For example, the submission unit records the creation process as a time-lapse video. The certification issuance unit issues a certificate of authorship based on the creation process submitted by the submission unit. The certification issuance unit analyzes the submitted creation process and evaluates the creator's skills and efforts. For example, the certification issuance unit analyzes each step of the submitted creation process and evaluates the creator's skill level. The certification issuance unit can also verify the validity of the submitted creation process. For example, the certification issuance unit checks whether the submitted creation process matches other works. The Link Issuing Unit provides author certificates issued by the Certificate Issuing Unit in link format. The Link Issuing Unit issues author certificates in formats such as URL links or QR codes (registered trademarks). For example, the Link Issuing Unit issues links that creators can share on social media. The Link Issuing Unit can also send author certificates via email. For example, the Link Issuing Unit sends the author certificate link to the creator's email address. The Checking Unit determines whether the data was generated by a generative AI after reliable data has been collected. For example, the Checking Unit verifies that the submitted illustration was not generated by a generative AI. For example, the Checking Unit analyzes the creation process of the submitted illustration to check for any traces of generation by a generative AI. The Checking Unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the Checking Unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI.As a result, the creator certification system according to the embodiment can receive the creator's creation process, issue a certificate of authorship, provide it in link format, and determine whether or not it was generated by a generative AI.

[0030] The submission section allows creators to submit their illustration creation process. For example, creators can meticulously record and submit each step of the illustration process. Specifically, the submission section records each step, such as sketching, line art, coloring, and finishing. Creators can upload screenshots or images for each step, enabling detailed documentation of the creation process. The submission section also allows creators to record the tools and techniques they used. For example, it records information about the software and hardware used. Specifically, it allows users to input information such as the version of the graphics software used and the model of the pen tablet. Furthermore, the submission section can record the creator's creation process in video format. For example, it can record the creation process as a time-lapse video. Creators can generate a time-lapse video by capturing the screen during work and taking screenshots at regular intervals. This allows the submission section to comprehensively record the creator's creation process and provide detailed evidence. Additionally, the submission section provides a function for creators to add comments and explanations when submitting their creation process. For example, creators can add comments explaining the techniques and methods they used for each step. This allows the submission department to meticulously record the creator's intentions and ingenuity, thereby increasing the reliability of the proof.

[0031] The Certificate Issuance Department issues author certificates based on the creation process submitted by the Submitting Department. For example, the Certificate Issuance Department analyzes the submitted creation process and evaluates the creator's skills and effort. Specifically, the Certificate Issuance Department analyzes each step of the submitted creation process and evaluates the creator's skill level. For example, the precision of the sketch, the quality of the line art, and the coloring technique can be used as evaluation criteria. The Certificate Issuance Department can also verify the authenticity of the submitted creation process. For example, the Certificate Issuance Department checks whether the submitted creation process matches other works. Specifically, it can compare the submitted images and videos with a database to check for similarity to existing works. Furthermore, the Certificate Issuance Department can analyze the timestamps and metadata of the submitted creation process to verify the authenticity of the creation date and time and the tools used. This allows the Certificate Issuance Department to accurately evaluate the creator's skills and effort and issue reliable author certificates. The Certificate Issuance Department includes the creator's name, the title of the work, and details of the creation process on the issued certificate, providing it as an official certificate. This allows creators to obtain reliable certificates to prove their skills and efforts.

[0032] The Link Issuing Department provides author certificates issued by the Certificate Issuing Department in link format. The Link Issuing Department issues author certificates in formats such as URL links and QR codes. Specifically, the Link Issuing Department issues links that creators can share on social media. Creators can paste this link into their profiles or posts to demonstrate their skills and efforts to other users. The Link Issuing Department can also send author certificates via email. For example, the Link Issuing Department sends a link to the author certificate to the creator's email address. This allows creators to easily share their certificates. Furthermore, the Link Issuing Department ensures that users who access the issued link can view the certificate details. Specifically, accessing the link opens a webpage displaying the certificate's contents and creation process details. This webpage includes the creator's name, the title of the work, and details of each step in the creation process. This allows the Link Issuing Department to widely share creators' skills and efforts and provide reliable proof.

[0033] The verification unit determines whether the submitted data was generated by a generative AI after reliable data has been collected. For example, the verification unit confirms that the submitted illustration was not generated by a generative AI. Specifically, the verification unit analyzes the creation process of the submitted illustration to check for any traces of generative AI generation. For example, the verification unit analyzes each step of the submitted illustration to check if any manual corrections or adjustments have been made. The verification unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generative AI generation. Specifically, the verification unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generative AI generation. For example, generative AI generation may exhibit certain patterns or characteristics. The verification unit detects these characteristics and evaluates the possibility of generative AI generation. Furthermore, the verification unit can also analyze the metadata and timestamps of the submitted illustration to verify the authenticity of the creation date and the tools used. This allows the verification unit to confirm that the submitted illustration was not generated by a generative AI and provide reliable proof.

[0034] The submission section allows creators to meticulously record and submit each step of their illustration process. For example, creators can meticulously record and submit each step, such as sketching, line drawing, coloring, and finishing. The submission section can also record the tools and techniques used by the creator. For example, it can record information about the software and hardware used. Furthermore, the submission section can record the creator's creative process in video format. For example, it can record the creative process as a time-lapse video. This makes the creator's skills and efforts visible. Some or all of the above processes in the submission section may be performed using AI, or not. For example, the submission section can input the data of the creative process recorded by the creator into an AI, which can then analyze the data and submit it.

[0035] The certification issuing unit can issue authorship certificates based on the submitted creation process. For example, the certification issuing unit can analyze the submitted creation process and evaluate the creator's skills and efforts. For example, the certification issuing unit can analyze each step of the submitted creation process and evaluate the creator's skill level. The certification issuing unit can also verify the legitimacy of the submitted creation process. For example, the certification issuing unit can check whether the submitted creation process matches any other works. This allows the creator's creation process to be verified. Some or all of the above processes in the certification issuing unit may be performed using AI, for example, or not using AI. For example, the certification issuing unit can input the data of the submitted creation process into an AI, which can then analyze the data and issue authorship certificates.

[0036] The link issuing unit issues author certificates in link format, which can be used for proof on social media. The link issuing unit issues author certificates in formats such as URL links or QR codes. For example, the link issuing unit issues links that creators can share on social media. The link issuing unit can also send author certificates via email. For example, the link issuing unit sends an author certificate link to the creator's email address. This allows creators to prove the authenticity of their work on social media. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or not using AI. For example, the link issuing unit can input author certificate data into AI, and the AI ​​can issue it in link format.

[0037] The checking unit can determine whether or not an illustration was generated by a generative AI. For example, the checking unit can verify that a submitted illustration was not generated by a generative AI. For example, the checking unit can analyze the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit can also analyze the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit can analyze the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI. This allows the checking unit to verify whether or not an illustration was generated by a generative AI. Some or all of the above-described processes in the checking unit may be performed using a generative AI, or they may be performed without using a generative AI. For example, the checking unit can input the data of the submitted illustration into a generative AI, and the generative AI can analyze the data and make a determination.

[0038] The checking unit can verify that the submitted illustration was not generated by a generative AI. For example, the checking unit can analyze the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit can also analyze the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit can analyze the brushstrokes and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI. This makes it possible to prove that the creator's work was not generated by a generative AI. Some or all of the above-described processes in the checking unit may be performed using AI, for example, or without using AI. For example, the checking unit can input the data of the submitted illustration into an AI, which can then analyze and verify the data.

[0039] The submission unit can store the creator's creation process. For example, the submission unit can save the data of the creation process submitted by the creator to a database. For example, the submission unit can classify the creator's creation process step by step and store it in the database. The submission unit can also store the creator's creation process chronologically. For example, the submission unit can save each step of the creation process with a timestamp. This allows the creator's creation process to be stored. Some or all of the above processing in the submission unit may be performed using AI, for example, or not using AI. For example, the submission unit can input the data of the creation process submitted by the creator into an AI, which can then analyze and store the data.

[0040] The submission section can make the creator's creative process public. For example, the submission section can publish the data of the creator's submitted creative process on its website or social media. For example, the submission section can publish the creator's creative process in video format. The submission section can also publish the creator's creative process step by step. For example, the submission section can publish each step, such as sketching, line drawing, coloring, and finishing, individually. This allows the creator's creative process to be made public. Some or all of the above processing in the submission section may be performed using AI, for example, or not using AI. For example, the submission section can input the data of the creator's submitted creative process into an AI, which can then analyze and publish the data.

[0041] The submission unit can analyze the creator's past creation process and select the optimal submission method at the time of submission. For example, the submission unit may prioritize suggesting submission methods (file format, submission procedure, etc.) that the creator has used in the past. For example, the submission unit may analyze the creator's past submission history and suggest the optimal submission method. The submission unit can also suggest the most efficient submission method based on the creator's past submission history. For example, the submission unit may select the optimal submission method based on the creator's past submission history. The submission unit can also analyze the creator's past creation process and suggest an appropriate timing for submission. For example, the submission unit may analyze the creator's past creation process and suggest an appropriate timing for submission. This allows the submission unit to analyze the creator's past creation process and select the optimal submission method. Some or all of the above processes in the submission unit may be performed using AI, or not. For example, the submission unit can input data on the creator's past creation process into AI, which can then analyze the data and select the optimal submission method.

[0042] The submission system can filter submissions based on the creator's current projects and areas of interest. For example, the system can prioritize submissions of creation processes related to the creator's current projects. The system can also prioritize submissions of creation processes related to the creator's current projects. The system can also submit highly relevant creation processes based on the creator's areas of interest. The system can also select which creation processes to submit based on the progress of the creator's current projects. This allows the system to filter submissions based on the creator's current projects and areas of interest. Some or all of the above processing in the submission system may be performed using AI, or not. For example, the system can input data on the creator's current projects and areas of interest into an AI, which can then analyze and filter the data.

[0043] The submission system can prioritize submitting creation processes that are highly relevant to the creator, taking into account the creator's geographical location. For example, if the creator is in a specific region, the system will prioritize submitting creation processes related to that region. For example, the system will prioritize submitting relevant creation processes based on the creator's geographical location. The system can also suggest the optimal submission timing based on the creator's geographical location. For example, the system will suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring that the submission is made in a stable environment. For example, the system will adjust the submission timing if the creator is on the move, based on the creator's geographical location. This allows the system to consider the creator's geographical location when making submissions. Some or all of the above processing in the submission system may be performed using AI, or not. For example, the system can input the creator's geographical location data into an AI, which can analyze the data and prioritize submitting creation processes that are highly relevant.

[0044] The submission unit can analyze the creator's social media activity and submit relevant creation processes at the time of submission. For example, the submission unit can analyze the content of the creator's social media activities and submit relevant creation processes. For example, the submission unit can analyze the content of the creator's social media posts and submit relevant creation processes. The submission unit can also select the creation processes to submit based on the interests of the creator's followers. For example, the submission unit can analyze the interests of the creator's followers and submit highly relevant creation processes. The submission unit can also adjust the timing of submission based on the creator's social media reactions. For example, the submission unit can analyze the creator's social media reactions and suggest the optimal submission timing. This allows for the analysis of the creator's social media activity and subsequent submission. Some or all of the above processes in the submission unit may be performed using AI, for example, or not. For example, the submission unit can input data on the creator's social media activity into an AI, which can then analyze the data and submit relevant creation processes.

[0045] The certificate issuing unit can adjust the level of detail of the certificate based on the importance of the creation process when issuing a certificate. For example, the certificate issuing unit issues a detailed certificate for a highly important creation process. For example, the certificate issuing unit evaluates the importance of the creation process and issues a detailed certificate for a highly important creation process. The certificate issuing unit can also issue a concise certificate for a less important creation process. For example, the certificate issuing unit evaluates the importance of the creation process and issues a concise certificate for a less important creation process. The certificate issuing unit can also customize the content of the certificate according to the importance of the creation process. For example, the certificate issuing unit adjusts the content of the certificate based on the importance of the creation process. This allows the level of detail of the certificate to be adjusted based on the importance of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the importance of the creation process into AI, and the AI ​​can analyze the data and adjust the level of detail of the certificate.

[0046] The certificate issuing unit can apply different proof algorithms depending on the category of the creation process when issuing a certificate. For example, the certificate issuing unit can apply different proof algorithms depending on the category of the illustration. For example, the certificate issuing unit can evaluate the category of the creation process and apply a proof algorithm according to the category of the illustration. The certificate issuing unit can also adjust the proof algorithm according to the step of the creation process. For example, the certificate issuing unit can evaluate the step of the creation process and adjust the proof algorithm according to the step. The certificate issuing unit can also optimize the proof algorithm according to the complexity of the creation process. For example, the certificate issuing unit can evaluate the complexity of the creation process and optimize the proof algorithm according to the complexity. This allows the certificate issuing unit to apply a proof algorithm according to the category of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or without AI. For example, the certificate issuing unit can input data on the category of the creation process into AI, and the AI ​​can analyze the data and apply a proof algorithm.

[0047] The certificate issuing unit can determine the priority of certificates based on the submission timing of the creation process when issuing certificates. For example, the certificate issuing unit will issue certificates preferentially to creation processes that were submitted earlier. For example, the certificate issuing unit will evaluate the submission timing of the creation process and issue certificates preferentially to those that were submitted earlier. The certificate issuing unit can also postpone issuing certificates to creation processes that were submitted later. For example, the certificate issuing unit will evaluate the submission timing of the creation process and issue certificates to those that were submitted later. The certificate issuing unit can also adjust the order of certificate issuance according to the submission timing. For example, the certificate issuing unit will adjust the order of certificate issuance based on the submission timing of the creation process. This allows the priority of certificates to be determined based on the submission timing of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the submission timing of the creation process into AI, and the AI ​​can analyze the data to determine the priority of certificates.

[0048] The certificate issuing unit can adjust the order of certificates based on the relevance of the creation process when issuing certificates. For example, the certificate issuing unit can prioritize issuing certificates to creation processes that are highly relevant. For example, the certificate issuing unit can evaluate the relevance of the creation process and prioritize issuing certificates to those that are highly relevant. The certificate issuing unit can also postpone issuing certificates to creation processes that are less relevant. For example, the certificate issuing unit can evaluate the relevance of the creation process and postpone issuing certificates to those that are less relevant. The certificate issuing unit can also adjust the order of certificate issuance according to the relevance of the creation process. For example, the certificate issuing unit adjusts the order of certificate issuance based on the relevance of the creation process. This allows the order of certificates to be adjusted based on the relevance of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the relevance of the creation process into AI, and the AI ​​can analyze the data to adjust the order of certificates.

[0049] The link issuing unit can select the optimal link format by referring to the creator's past link issuing history when issuing a link. For example, the link issuing unit may prioritize suggesting link formats previously used by the creator. For example, the link issuing unit may analyze the creator's past link issuing history and suggest the optimal link format. The link issuing unit can also select the most effective link format from the creator's past link issuing history. For example, the link issuing unit may select the optimal link format based on the creator's past link issuing history. The link issuing unit may also analyze the creator's past link issuing history and suggest the optimal link format. For example, the link issuing unit may suggest the optimal link format based on the creator's past link issuing history. This allows the optimal link format to be selected by referring to the creator's past link issuing history. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's past link issuing history into AI, which can then analyze the data and select the optimal link format.

[0050] The link issuing unit can customize the content of links based on the creator's current projects and areas of interest when issuing them. For example, the link issuing unit can issue links related to the projects the creator is currently working on. The link issuing unit can also issue highly relevant links based on the creator's areas of interest. The link issuing unit can also customize the content of links according to the progress of the creator's current projects. This allows the content of links to be customized based on the creator's current projects and areas of interest. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's current projects and areas of interest into AI, which can then analyze the data and customize the content of the links.

[0051] The link issuing unit can select the optimal link format when issuing a link, taking into account the creator's geographical location information. For example, if the creator is in a specific region, the link issuing unit will issue a link related to that region. For example, the link issuing unit will issue a relevant link based on the creator's geographical location information. The link issuing unit can also select the optimal link format based on the creator's geographical location information. For example, the link issuing unit will select the optimal link format based on the creator's geographical location information. Furthermore, if the creator is on the move, the link issuing unit can adjust the timing of link issuance to issue the link in a stable environment. For example, the link issuing unit will adjust the timing of link issuance if the creator is on the move, based on the creator's geographical location information. This allows the unit to select the optimal link format, taking into account the creator's geographical location information. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input the creator's geographical location data into AI, and the AI ​​can analyze the data to select the optimal link format.

[0052] The link issuing unit can analyze the creator's social media activity and adjust the content of the link when issuing it. For example, the link issuing unit can analyze the creator's social media activity and issue relevant links. For example, the link issuing unit can analyze the content of the creator's social media posts and issue relevant links. The link issuing unit can also adjust the content of the link based on the interests of the creator's followers. For example, the link issuing unit can analyze the interests of the creator's followers and issue highly relevant links. The link issuing unit can also adjust the timing of link issuance based on the creator's social media reactions. For example, the link issuing unit can analyze the creator's social media reactions and suggest the optimal timing for link issuance. This allows the link content to be adjusted by analyzing the creator's social media activity. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's social media activity into AI, which can then analyze the data and adjust the content of the link.

[0053] The checking unit can improve the accuracy of its checks by considering the interrelationships of the creation process during the check. For example, the checking unit can improve the accuracy of its checks by analyzing the relationships between each step of the creation process. For example, the checking unit can improve the accuracy of its checks by evaluating the relationships between each step of the creation process. The checking unit can also adjust the criteria for checking by considering the interrelationships of the creation process. For example, the checking unit can evaluate the interrelationships of the creation process and adjust the criteria for checking. The checking unit can also determine the priority of checks based on the interrelationships of the creation process. For example, the checking unit can evaluate the interrelationships of the creation process and determine the priority of checks. This allows the checking unit to improve the accuracy of its checks by considering the interrelationships of the creation process. Some or all of the above processing in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input data on the interrelationships of the creation process into AI, and the AI ​​can analyze the data to improve the accuracy of the checks.

[0054] The checking unit can perform checks while considering the attribute information of the submitter during the creation process. For example, the checking unit can adjust the checking criteria by considering the submitter's attribute information (age, experience, etc.). For example, the checking unit can evaluate the submitter's attribute information and adjust the checking criteria based on age and experience. The checking unit can also determine the priority of checks based on the submitter's attribute information. For example, the checking unit evaluates the submitter's attribute information and determines the priority of checks. The checking unit can also analyze the submitter's attribute information and propose the optimal checking method. For example, the checking unit evaluates the submitter's attribute information and proposes the optimal checking method. This allows the checking to be performed while considering the submitter's attribute information. Some or all of the above processes in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input the submitter's attribute information data into AI, and the AI ​​can analyze the data and perform checks.

[0055] The checking unit can perform checks while considering the geographical distribution of the creation process. For example, the checking unit can analyze the geographical distribution of the creation process and adjust the checking criteria. For example, the checking unit can evaluate the geographical distribution of the creation process and adjust the checking criteria. The checking unit can also determine the priority of checks based on the geographical distribution. For example, the checking unit can evaluate the geographical distribution of the creation process and determine the priority of checks. The checking unit can also optimize the checking method while considering the geographical distribution. For example, the checking unit can evaluate the geographical distribution of the creation process and optimize the checking method. This allows the checking to be performed while considering the geographical distribution of the creation process. Some or all of the above processing in the checking unit may be performed using AI, for example, or without using AI. For example, the checking unit can input data on the geographical distribution of the creation process into AI, and the AI ​​can analyze the data and perform checks.

[0056] The checking unit can improve the accuracy of its checks by referring to relevant literature during the creation process. For example, the checking unit can improve the accuracy of its checks by referring to relevant literature during the creation process. For example, the checking unit can improve the accuracy of its checks by evaluating relevant literature during the creation process. The checking unit can also adjust the criteria for checking based on relevant literature. For example, the checking unit can evaluate relevant literature and adjust the criteria for checking. The checking unit can also analyze relevant literature and propose the optimal checking method. For example, the checking unit can evaluate relevant literature and propose the optimal checking method. This allows the checking unit to improve the accuracy of its checks by referring to relevant literature during the creation process. Some or all of the above processes in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input data from relevant literature during the creation process into AI, and the AI ​​can analyze the data to improve the accuracy of its checks.

[0057] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0058] The creator certification system allows for the evaluation of a creator's technical progress by comparing their current work with their past works when they submit their creation process. For example, the submission section accumulates data on the creator's past submitted creation processes and compares it with the newly submitted process. This allows for the evaluation of the creator's technical improvement and acquisition of new skills. Furthermore, the certification issuance section can issue a certificate proving the creator's technical progress based on the comparison results with past creation processes. For example, the certification issuance section compares the techniques the creator used in the past with the techniques they have newly used to evaluate their technical progress. In addition, the link issuance section can issue certificates demonstrating technical progress in the form of links, which can be shared on social media. For example, the link issuance section issues links that creators can use to showcase their technical progress. This allows for the evaluation and verification of the creator's technical progress.

[0059] The creator verification system can customize submissions by taking into account the creator's geographical location when submitting their work. For example, if the creator is in a specific region, the system will prioritize submitting work related to that region. The system can also suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring a stable environment for submission. This allows for customization of submissions by considering the creator's geographical location.

[0060] The creator verification system allows creators to submit their creation processes by analyzing their social media activity and selecting relevant processes. For example, the submission team can analyze the creator's social media activity and submit relevant processes. The submission team can also select the processes to submit based on the interests of the creator's followers. For example, the submission team can analyze the interests of the creator's followers and submit highly relevant processes. Furthermore, the submission team can adjust the timing of submissions based on the creator's social media reactions. For example, the submission team can analyze the creator's social media reactions and suggest the optimal submission timing. This allows creators to analyze their social media activity and adjust their submissions accordingly.

[0061] The creator verification system can analyze a creator's past creation process and select the optimal submission method when they submit their work. For example, the submission system prioritizes suggesting submission methods (file format, submission procedure, etc.) that the creator has used in the past. For example, the submission system analyzes the creator's past submission history and suggests the optimal submission method. The submission system can also suggest the most efficient submission method based on the creator's past submission history. For example, the submission system selects the optimal submission method based on the creator's past submission history. The submission system can also analyze the creator's past creation process and suggest the most suitable timing for submission. For example, the submission system analyzes the creator's past creation process and suggests the most suitable timing for submission. This allows the system to analyze the creator's past creation process and select the optimal submission method.

[0062] The creator certification system allows for filtering of creators' work processes based on their current projects and areas of interest. For example, the system prioritizes submissions of work processes related to the creator's current projects. It can also prioritize submissions of work processes relevant to the creator's areas of interest. Furthermore, the system can select work processes to submit based on the progress of the creator's current projects. This allows for filtering of submissions based on the creator's current projects and areas of interest.

[0063] The creator verification system can prioritize the submission of creator work processes that are most relevant to the creator's location, taking into account the creator's geographical location when the creator submits their work. For example, if the creator is in a specific region, the system will prioritize submitting work processes related to that region. The system can also suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring that the work is submitted in a stable environment. This allows the system to consider the creator's geographical location when submitting work.

[0064] The creator verification system allows creators to submit their creation processes by analyzing their social media activity and selecting relevant processes. For example, the submission process can analyze the creator's social media activity and submit relevant processes. It can also select processes to submit based on the interests of the creator's followers. For example, it can analyze the interests of the creator's followers and submit highly relevant processes. Furthermore, the submission process can adjust the timing of submissions based on the creator's social media reactions. For example, it can analyze the creator's social media reactions and suggest the optimal submission timing. This allows for the analysis and submission of creators' social media activities.

[0065] The following briefly describes the processing flow for example form 1.

[0066] Step 1: The submission section is where creators submit their illustration creation process. For example, creators can submit detailed records of each step of the illustration process. For instance, the submission section might record each step, such as sketching, line drawing, coloring, and finishing. The submission section can also record the tools and techniques used by the creator. For example, it might record information about the software and hardware used. Furthermore, the submission section can record the creator's creation process in video format. For example, the submission section might record the creation process as a time-lapse video. Step 2: The Certificate Issuing Department issues a certificate of authorship based on the creation process submitted by the Submitting Department. The Certificate Issuing Department, for example, analyzes the submitted creation process and evaluates the creator's skills and effort. For example, the Certificate Issuing Department analyzes each step of the submitted creation process and evaluates the creator's skill level. The Certificate Issuing Department can also verify the legitimacy of the submitted creation process. For example, the Certificate Issuing Department checks whether the submitted creation process is consistent with other works. Step 3: The Link Issuing Unit provides the author certificate issued by the Certificate Issuing Unit in link format. The Link Issuing Unit issues the author certificate in the form of a URL link or QR code, for example. For example, the Link Issuing Unit issues a link that creators can share on social media. The Link Issuing Unit can also send the author certificate by email. For example, the Link Issuing Unit sends the author certificate link to the creator's email address. Step 4: The checking unit determines whether the data was generated by a generative AI after reliable data has been collected. For example, the checking unit verifies that the submitted illustration was not generated by a generative AI. For example, the checking unit analyzes the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI.

[0067] (Example of form 2) The creator certification system according to an embodiment of the present invention can generate high-quality illustrations in seconds using a generation AI, but there are concerns about a decrease in the relative value of the creator's skills. Therefore, this system issues authorship certificates upon submission of the creator's creation process. The creator certification system issues authorship certificates based on the submitted creation process after the creator submits the creation process of the illustration. This authorship certificate is issued in the form of a link and can be used for proof on social media. Furthermore, after reliable data has been collected, a generation AI check system will be developed to determine whether the work was generated by the generation AI. This system aims to create a world where creators are valued, with a view to accumulating and publishing the creator's creation process. For example, in the creator certification system, the creator submits the creation process of the illustration. In this case, the creator records and submits each step of the illustration in detail. For example, each step such as sketching, line drawing, coloring, and finishing is recorded. This makes the creator's skills and efforts visible. Next, the creator certification system issues authorship certificates based on the submitted creation process. This authorship certificate proves the creator's creation process and is issued in the form of a link. By sharing this link on social media, the creator can prove that their work was created by them. For example, by sharing a link on social media, creators can appeal to their followers to demonstrate the authenticity of their work. Furthermore, once reliable data has been collected, the creator verification system will develop a generative AI check system. This system will determine whether or not a work was generated by generative AI, thus proving that a creator's work was not generated by AI. For example, the generative AI check system can be used to verify that a submitted illustration was not generated by generative AI. This system aims to create a world where creators are valued, with a view to accumulating and publishing the creator's creative process. The creator's creative process is very beautiful and never gets boring to watch, so by publishing the creative process, the creator's skills and efforts will be appreciated.Furthermore, by making the creation process public, interaction with other creators and fans can be deepened, and the creator community is expected to be revitalized. In this way, the creator certification system can generate high-quality illustrations in seconds using generation AI, but it aims to prevent a decline in the relative value of creators' skills and create a world where creators are properly valued. Thus, the creator certification system can prove and evaluate the creation process of creators.

[0068] The creator certification system according to this embodiment comprises a submission unit, a certification issuance unit, a link issuance unit, and a checking unit. The submission unit receives the creator's illustration creation process. The submission unit allows the creator to record and submit each step of the illustration in detail. For example, the submission unit records each step such as sketching, line drawing, coloring, and finishing. The submission unit can also record the tools and techniques used by the creator. For example, the submission unit records information about the software and hardware used. Furthermore, the submission unit can record the creator's creation process in video format. For example, the submission unit records the creation process as a time-lapse video. The certification issuance unit issues a certificate of authorship based on the creation process submitted by the submission unit. The certification issuance unit analyzes the submitted creation process and evaluates the creator's skills and efforts. For example, the certification issuance unit analyzes each step of the submitted creation process and evaluates the creator's skill level. The certification issuance unit can also verify the validity of the submitted creation process. For example, the certification issuance unit checks whether the submitted creation process matches other works. The Link Issuing Unit provides author certificates issued by the Certificate Issuing Unit in link format. The Link Issuing Unit issues author certificates in formats such as URL links or QR codes. For example, the Link Issuing Unit issues links that creators can share on social media. The Link Issuing Unit can also send author certificates via email. For example, the Link Issuing Unit sends the author certificate link to the creator's email address. The Checking Unit determines whether the data was generated by a generative AI after reliable data has been collected. For example, the Checking Unit verifies that the submitted illustration was not generated by a generative AI. For example, the Checking Unit analyzes the creation process of the submitted illustration to check for any traces of generation by a generative AI. The Checking Unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the Checking Unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI.As a result, the creator certification system according to the embodiment can receive the creator's creation process, issue a certificate of authorship, provide it in link format, and determine whether or not it was generated by a generative AI.

[0069] The submission section allows creators to submit their illustration creation process. For example, creators can meticulously record and submit each step of the illustration process. Specifically, the submission section records each step, such as sketching, line art, coloring, and finishing. Creators can upload screenshots or images for each step, enabling detailed documentation of the creation process. The submission section also allows creators to record the tools and techniques they used. For example, it records information about the software and hardware used. Specifically, it allows users to input information such as the version of the graphics software used and the model of the pen tablet. Furthermore, the submission section can record the creator's creation process in video format. For example, it can record the creation process as a time-lapse video. Creators can generate a time-lapse video by capturing the screen during work and taking screenshots at regular intervals. This allows the submission section to comprehensively record the creator's creation process and provide detailed evidence. Additionally, the submission section provides a function for creators to add comments and explanations when submitting their creation process. For example, creators can add comments explaining the techniques and methods they used for each step. This allows the submission department to meticulously record the creator's intentions and ingenuity, thereby increasing the reliability of the proof.

[0070] The Certificate Issuance Department issues author certificates based on the creation process submitted by the Submitting Department. For example, the Certificate Issuance Department analyzes the submitted creation process and evaluates the creator's skills and effort. Specifically, the Certificate Issuance Department analyzes each step of the submitted creation process and evaluates the creator's skill level. For example, the precision of the sketch, the quality of the line art, and the coloring technique can be used as evaluation criteria. The Certificate Issuance Department can also verify the authenticity of the submitted creation process. For example, the Certificate Issuance Department checks whether the submitted creation process matches other works. Specifically, it can compare the submitted images and videos with a database to check for similarity to existing works. Furthermore, the Certificate Issuance Department can analyze the timestamps and metadata of the submitted creation process to verify the authenticity of the creation date and time and the tools used. This allows the Certificate Issuance Department to accurately evaluate the creator's skills and effort and issue reliable author certificates. The Certificate Issuance Department includes the creator's name, the title of the work, and details of the creation process on the issued certificate, providing it as an official certificate. This allows creators to obtain reliable certificates to prove their skills and efforts.

[0071] The Link Issuing Department provides author certificates issued by the Certificate Issuing Department in link format. The Link Issuing Department issues author certificates in formats such as URL links and QR codes. Specifically, the Link Issuing Department issues links that creators can share on social media. Creators can paste this link into their profiles or posts to demonstrate their skills and efforts to other users. The Link Issuing Department can also send author certificates via email. For example, the Link Issuing Department sends a link to the author certificate to the creator's email address. This allows creators to easily share their certificates. Furthermore, the Link Issuing Department ensures that users who access the issued link can view the certificate details. Specifically, accessing the link opens a webpage displaying the certificate's contents and creation process details. This webpage includes the creator's name, the title of the work, and details of each step in the creation process. This allows the Link Issuing Department to widely share creators' skills and efforts and provide reliable proof.

[0072] The verification unit determines whether the submitted data was generated by a generative AI after reliable data has been collected. For example, the verification unit confirms that the submitted illustration was not generated by a generative AI. Specifically, the verification unit analyzes the creation process of the submitted illustration to check for any traces of generative AI generation. For example, the verification unit analyzes each step of the submitted illustration to check if any manual corrections or adjustments have been made. The verification unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generative AI generation. Specifically, the verification unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generative AI generation. For example, generative AI generation may exhibit certain patterns or characteristics. The verification unit detects these characteristics and evaluates the possibility of generative AI generation. Furthermore, the verification unit can also analyze the metadata and timestamps of the submitted illustration to verify the authenticity of the creation date and the tools used. This allows the verification unit to confirm that the submitted illustration was not generated by a generative AI and provide reliable proof.

[0073] The submission section allows creators to meticulously record and submit each step of their illustration process. For example, creators can meticulously record and submit each step, such as sketching, line drawing, coloring, and finishing. The submission section can also record the tools and techniques used by the creator. For example, it can record information about the software and hardware used. Furthermore, the submission section can record the creator's creative process in video format. For example, it can record the creative process as a time-lapse video. This makes the creator's skills and efforts visible. Some or all of the above processes in the submission section may be performed using AI, or not. For example, the submission section can input the data of the creative process recorded by the creator into an AI, which can then analyze the data and submit it.

[0074] The certification issuing unit can issue authorship certificates based on the submitted creation process. For example, the certification issuing unit can analyze the submitted creation process and evaluate the creator's skills and efforts. For example, the certification issuing unit can analyze each step of the submitted creation process and evaluate the creator's skill level. The certification issuing unit can also verify the legitimacy of the submitted creation process. For example, the certification issuing unit can check whether the submitted creation process matches any other works. This allows the creator's creation process to be verified. Some or all of the above processes in the certification issuing unit may be performed using AI, for example, or not using AI. For example, the certification issuing unit can input the data of the submitted creation process into an AI, which can then analyze the data and issue authorship certificates.

[0075] The link issuing unit issues author certificates in link format, which can be used for proof on social media. The link issuing unit issues author certificates in formats such as URL links or QR codes. For example, the link issuing unit issues links that creators can share on social media. The link issuing unit can also send author certificates via email. For example, the link issuing unit sends an author certificate link to the creator's email address. This allows creators to prove the authenticity of their work on social media. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or not using AI. For example, the link issuing unit can input author certificate data into AI, and the AI ​​can issue it in link format.

[0076] The checking unit can determine whether or not an illustration was generated by a generative AI. For example, the checking unit can verify that a submitted illustration was not generated by a generative AI. For example, the checking unit can analyze the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit can also analyze the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit can analyze the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI. This allows the checking unit to verify whether or not an illustration was generated by a generative AI. Some or all of the above-described processes in the checking unit may be performed using a generative AI, or they may be performed without using a generative AI. For example, the checking unit can input the data of the submitted illustration into a generative AI, and the generative AI can analyze the data and make a determination.

[0077] The checking unit can verify that the submitted illustration was not generated by a generative AI. For example, the checking unit can analyze the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit can also analyze the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit can analyze the brushstrokes and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI. This makes it possible to prove that the creator's work was not generated by a generative AI. Some or all of the above-described processes in the checking unit may be performed using AI, for example, or without using AI. For example, the checking unit can input the data of the submitted illustration into an AI, which can then analyze and verify the data.

[0078] The submission unit can store the creator's creation process. For example, the submission unit can save the data of the creation process submitted by the creator to a database. For example, the submission unit can classify the creator's creation process step by step and store it in the database. The submission unit can also store the creator's creation process chronologically. For example, the submission unit can save each step of the creation process with a timestamp. This allows the creator's creation process to be stored. Some or all of the above processing in the submission unit may be performed using AI, for example, or not using AI. For example, the submission unit can input the data of the creation process submitted by the creator into an AI, which can then analyze and store the data.

[0079] The submission section can make the creator's creative process public. For example, the submission section can publish the data of the creator's submitted creative process on its website or social media. For example, the submission section can publish the creator's creative process in video format. The submission section can also publish the creator's creative process step by step. For example, the submission section can publish each step, such as sketching, line drawing, coloring, and finishing, individually. This allows the creator's creative process to be made public. Some or all of the above processing in the submission section may be performed using AI, for example, or not using AI. For example, the submission section can input the data of the creator's submitted creative process into an AI, which can then analyze and publish the data.

[0080] The submission unit can estimate the creator's emotions and adjust the submission timing of the creation process based on the estimated emotions of the creator. For example, if the creator is feeling stressed, the submission unit can extend the submission deadline to allow them to submit in a relaxed state. For example, the submission unit can estimate the creator's emotions and extend the submission deadline if they are feeling stressed. The submission unit can also encourage submission when the creator is focused, so as not to disrupt the workflow. For example, the submission unit can estimate the creator's emotions and encourage submission when they are focused. The submission unit can also suggest a break if the creator is tired and encourage submission after resting. For example, the submission unit can estimate the creator's emotions and suggest a break when they are tired. This allows the submission timing to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the submission unit may be performed using AI, for example, or not using AI. For example, the submission system can input creator's emotional data into an AI, which then analyzes the data to adjust the submission timing.

[0081] The submission unit can analyze the creator's past creation process and select the optimal submission method at the time of submission. For example, the submission unit may prioritize suggesting submission methods (file format, submission procedure, etc.) that the creator has used in the past. For example, the submission unit may analyze the creator's past submission history and suggest the optimal submission method. The submission unit can also suggest the most efficient submission method based on the creator's past submission history. For example, the submission unit may select the optimal submission method based on the creator's past submission history. The submission unit can also analyze the creator's past creation process and suggest an appropriate timing for submission. For example, the submission unit may analyze the creator's past creation process and suggest an appropriate timing for submission. This allows the submission unit to analyze the creator's past creation process and select the optimal submission method. Some or all of the above processes in the submission unit may be performed using AI, or not. For example, the submission unit can input data on the creator's past creation process into AI, which can then analyze the data and select the optimal submission method.

[0082] The submission system can filter submissions based on the creator's current projects and areas of interest. For example, the system can prioritize submissions of creation processes related to the creator's current projects. The system can also prioritize submissions of creation processes related to the creator's current projects. The system can also submit highly relevant creation processes based on the creator's areas of interest. The system can also select which creation processes to submit based on the progress of the creator's current projects. This allows the system to filter submissions based on the creator's current projects and areas of interest. Some or all of the above processing in the submission system may be performed using AI, or not. For example, the system can input data on the creator's current projects and areas of interest into an AI, which can then analyze and filter the data.

[0083] The submission system can estimate the creator's emotions and, based on the estimated emotions, determine the priority of the creation process to be submitted. For example, if the creator is stressed, the system will prioritize submitting less important creation processes. The system can also prioritize submitting more important creation processes if the creator is relaxed. Furthermore, if the creator is focused, the system can adjust the submission priority to avoid disrupting the workflow. This allows the system to determine the priority of the creation process to be submitted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the submission section may be performed using AI, for example, or without AI. For example, the submission section may input creator's emotional data into AI, which then analyzes the data to determine the priority of the creation process to be submitted.

[0084] The submission system can prioritize submitting creation processes that are highly relevant to the creator, taking into account the creator's geographical location. For example, if the creator is in a specific region, the system will prioritize submitting creation processes related to that region. For example, the system will prioritize submitting relevant creation processes based on the creator's geographical location. The system can also suggest the optimal submission timing based on the creator's geographical location. For example, the system will suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring that the submission is made in a stable environment. For example, the system will adjust the submission timing if the creator is on the move, based on the creator's geographical location. This allows the system to consider the creator's geographical location when making submissions. Some or all of the above processing in the submission system may be performed using AI, or not. For example, the system can input the creator's geographical location data into an AI, which can analyze the data and prioritize submitting creation processes that are highly relevant.

[0085] The submission unit can analyze the creator's social media activity and submit relevant creation processes at the time of submission. For example, the submission unit can analyze the content of the creator's social media activities and submit relevant creation processes. For example, the submission unit can analyze the content of the creator's social media posts and submit relevant creation processes. The submission unit can also select the creation processes to submit based on the interests of the creator's followers. For example, the submission unit can analyze the interests of the creator's followers and submit highly relevant creation processes. The submission unit can also adjust the timing of submission based on the creator's social media reactions. For example, the submission unit can analyze the creator's social media reactions and suggest the optimal submission timing. This allows for the analysis of the creator's social media activity and subsequent submission. Some or all of the above processes in the submission unit may be performed using AI, for example, or not. For example, the submission unit can input data on the creator's social media activity into an AI, which can then analyze the data and submit relevant creation processes.

[0086] The certificate issuing unit can estimate the creator's emotions and adjust the presentation of the certificate based on the estimated emotions. For example, if the creator is relaxed, the certificate issuing unit may issue a detailed certificate. For example, if the creator is relaxed, the certificate issuing unit may issue a detailed certificate. For example, if the creator is in a hurry, the certificate issuing unit may issue a concise certificate. For example, if the creator is excited, the certificate issuing unit may issue a visually appealing certificate. For example, if the creator is excited, the certificate issuing unit may issue a visually appealing certificate. This allows the presentation of the certificate to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or without AI. For example, the certification issuing unit can input the creator's emotional data into an AI, which can then analyze the data and adjust the way the certification is presented.

[0087] The certificate issuing unit can adjust the level of detail of the certificate based on the importance of the creation process when issuing a certificate. For example, the certificate issuing unit issues a detailed certificate for a highly important creation process. For example, the certificate issuing unit evaluates the importance of the creation process and issues a detailed certificate for a highly important creation process. The certificate issuing unit can also issue a concise certificate for a less important creation process. For example, the certificate issuing unit evaluates the importance of the creation process and issues a concise certificate for a less important creation process. The certificate issuing unit can also customize the content of the certificate according to the importance of the creation process. For example, the certificate issuing unit adjusts the content of the certificate based on the importance of the creation process. This allows the level of detail of the certificate to be adjusted based on the importance of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the importance of the creation process into AI, and the AI ​​can analyze the data and adjust the level of detail of the certificate.

[0088] The certificate issuing unit can apply different proof algorithms depending on the category of the creation process when issuing a certificate. For example, the certificate issuing unit can apply different proof algorithms depending on the category of the illustration. For example, the certificate issuing unit can evaluate the category of the creation process and apply a proof algorithm according to the category of the illustration. The certificate issuing unit can also adjust the proof algorithm according to the step of the creation process. For example, the certificate issuing unit can evaluate the step of the creation process and adjust the proof algorithm according to the step. The certificate issuing unit can also optimize the proof algorithm according to the complexity of the creation process. For example, the certificate issuing unit can evaluate the complexity of the creation process and optimize the proof algorithm according to the complexity. This allows the certificate issuing unit to apply a proof algorithm according to the category of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or without AI. For example, the certificate issuing unit can input data on the category of the creation process into AI, and the AI ​​can analyze the data and apply a proof algorithm.

[0089] The certificate issuing unit can estimate the creator's emotions and adjust the length of the certificate based on the estimated emotions. For example, if the creator is relaxed, the certificate issuing unit will issue a detailed certificate. For example, if the certificate issuing unit estimates the creator's emotions and issues a detailed certificate if the creator is relaxed, it will issue a detailed certificate. The certificate issuing unit can also issue a concise certificate if the creator is in a hurry. For example, if the certificate issuing unit estimates the creator's emotions and issues a concise certificate if the creator is in a hurry, it will issue a visually appealing certificate if the creator is excited. For example, if the certificate issuing unit estimates the creator's emotions and issues a visually appealing certificate if the creator is excited, it will issue a visually appealing certificate. This allows the length of the certificate to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or without AI. For example, the certificate issuing unit can input the creator's emotional data into an AI, which can then analyze the data and adjust the length of the certificate.

[0090] The certificate issuing unit can determine the priority of certificates based on the submission timing of the creation process when issuing certificates. For example, the certificate issuing unit will issue certificates preferentially to creation processes that were submitted earlier. For example, the certificate issuing unit will evaluate the submission timing of the creation process and issue certificates preferentially to those that were submitted earlier. The certificate issuing unit can also postpone issuing certificates to creation processes that were submitted later. For example, the certificate issuing unit will evaluate the submission timing of the creation process and issue certificates to those that were submitted later. The certificate issuing unit can also adjust the order of certificate issuance according to the submission timing. For example, the certificate issuing unit will adjust the order of certificate issuance based on the submission timing of the creation process. This allows the priority of certificates to be determined based on the submission timing of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the submission timing of the creation process into AI, and the AI ​​can analyze the data to determine the priority of certificates.

[0091] The certificate issuing unit can adjust the order of certificates based on the relevance of the creation process when issuing certificates. For example, the certificate issuing unit can prioritize issuing certificates to creation processes that are highly relevant. For example, the certificate issuing unit can evaluate the relevance of the creation process and prioritize issuing certificates to those that are highly relevant. The certificate issuing unit can also postpone issuing certificates to creation processes that are less relevant. For example, the certificate issuing unit can evaluate the relevance of the creation process and postpone issuing certificates to those that are less relevant. The certificate issuing unit can also adjust the order of certificate issuance according to the relevance of the creation process. For example, the certificate issuing unit adjusts the order of certificate issuance based on the relevance of the creation process. This allows the order of certificates to be adjusted based on the relevance of the creation process. Some or all of the above processing in the certificate issuing unit may be performed using AI, for example, or not using AI. For example, the certificate issuing unit can input data on the relevance of the creation process into AI, and the AI ​​can analyze the data to adjust the order of certificates.

[0092] The link issuing unit can estimate the creator's emotions and adjust how links are displayed based on the estimated emotions. For example, if the creator is relaxed, the link issuing unit can display detailed link information. For example, if the creator is relaxed, the link issuing unit can estimate the creator's emotions and display detailed link information. The link issuing unit can also display concise link information if the creator is in a hurry. For example, if the creator is excited, the link issuing unit can display visually appealing link information. For example, if the creator is excited, the link issuing unit can estimate the creator's emotions and display visually appealing link information. This allows the link display method to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input creator's emotional data into an AI, which can then analyze the data and adjust how the links are displayed.

[0093] The link issuing unit can select the optimal link format by referring to the creator's past link issuing history when issuing a link. For example, the link issuing unit may prioritize suggesting link formats previously used by the creator. For example, the link issuing unit may analyze the creator's past link issuing history and suggest the optimal link format. The link issuing unit can also select the most effective link format from the creator's past link issuing history. For example, the link issuing unit may select the optimal link format based on the creator's past link issuing history. The link issuing unit may also analyze the creator's past link issuing history and suggest the optimal link format. For example, the link issuing unit may suggest the optimal link format based on the creator's past link issuing history. This allows the optimal link format to be selected by referring to the creator's past link issuing history. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's past link issuing history into AI, which can then analyze the data and select the optimal link format.

[0094] The link issuing unit can customize the content of links based on the creator's current projects and areas of interest when issuing them. For example, the link issuing unit can issue links related to the projects the creator is currently working on. The link issuing unit can also issue highly relevant links based on the creator's areas of interest. The link issuing unit can also customize the content of links according to the progress of the creator's current projects. This allows the content of links to be customized based on the creator's current projects and areas of interest. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's current projects and areas of interest into AI, which can then analyze the data and customize the content of the links.

[0095] The link issuing unit can estimate the creator's emotions and determine the priority of links based on the estimated emotions. For example, if the creator is relaxed, the link issuing unit will prioritize issuing high-importance links. For example, if the creator is relaxed, the link issuing unit will prioritize issuing high-importance links. The link issuing unit can also prioritize issuing low-importance links if the creator is in a hurry. For example, if the creator is excited, the link issuing unit can prioritize issuing visually appealing links. For example, if the creator is excited, the link issuing unit will prioritize issuing visually appealing links. This allows the link prioritization to be determined according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input creator's emotional data into AI, which can then analyze the data to determine the priority of links.

[0096] The link issuing unit can select the optimal link format when issuing a link, taking into account the creator's geographical location information. For example, if the creator is in a specific region, the link issuing unit will issue a link related to that region. For example, the link issuing unit will issue a relevant link based on the creator's geographical location information. The link issuing unit can also select the optimal link format based on the creator's geographical location information. For example, the link issuing unit will select the optimal link format based on the creator's geographical location information. Furthermore, if the creator is on the move, the link issuing unit can adjust the timing of link issuance to issue the link in a stable environment. For example, the link issuing unit will adjust the timing of link issuance if the creator is on the move, based on the creator's geographical location information. This allows the unit to select the optimal link format, taking into account the creator's geographical location information. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input the creator's geographical location data into AI, and the AI ​​can analyze the data to select the optimal link format.

[0097] The link issuing unit can analyze the creator's social media activity and adjust the content of the link when issuing it. For example, the link issuing unit can analyze the creator's social media activity and issue relevant links. For example, the link issuing unit can analyze the content of the creator's social media posts and issue relevant links. The link issuing unit can also adjust the content of the link based on the interests of the creator's followers. For example, the link issuing unit can analyze the interests of the creator's followers and issue highly relevant links. The link issuing unit can also adjust the timing of link issuance based on the creator's social media reactions. For example, the link issuing unit can analyze the creator's social media reactions and suggest the optimal timing for link issuance. This allows the link content to be adjusted by analyzing the creator's social media activity. Some or all of the above processing in the link issuing unit may be performed using AI, for example, or without AI. For example, the link issuing unit can input data on the creator's social media activity into AI, which can then analyze the data and adjust the content of the link.

[0098] The checking unit can estimate the creator's emotions and adjust the checking criteria based on the estimated emotions. For example, if the creator is relaxed, the checking unit can apply detailed checking criteria. For example, if the checking unit estimates the creator's emotions and applies detailed checking criteria when the creator is relaxed, it can apply concise checking criteria. For example, if the checking unit estimates the creator's emotions and applies concise checking criteria when the creator is in a hurry, it can apply concise checking criteria when the creator is excited, it can apply visually appealing checking criteria when the creator is excited, it can apply visually appealing checking criteria when the creator is excited. This allows the checking criteria to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the checking unit may be performed using AI, for example, or without AI. For example, the checking function can input creator's emotional data into an AI, which then analyzes the data and adjusts the checking criteria.

[0099] The checking unit can improve the accuracy of its checks by considering the interrelationships of the creation process during the check. For example, the checking unit can improve the accuracy of its checks by analyzing the relationships between each step of the creation process. For example, the checking unit can improve the accuracy of its checks by evaluating the relationships between each step of the creation process. The checking unit can also adjust the criteria for checking by considering the interrelationships of the creation process. For example, the checking unit can evaluate the interrelationships of the creation process and adjust the criteria for checking. The checking unit can also determine the priority of checks based on the interrelationships of the creation process. For example, the checking unit can evaluate the interrelationships of the creation process and determine the priority of checks. This allows the checking unit to improve the accuracy of its checks by considering the interrelationships of the creation process. Some or all of the above processing in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input data on the interrelationships of the creation process into AI, and the AI ​​can analyze the data to improve the accuracy of the checks.

[0100] The checking unit can perform checks while considering the attribute information of the submitter during the creation process. For example, the checking unit can adjust the checking criteria by considering the submitter's attribute information (age, experience, etc.). For example, the checking unit can evaluate the submitter's attribute information and adjust the checking criteria based on age and experience. The checking unit can also determine the priority of checks based on the submitter's attribute information. For example, the checking unit evaluates the submitter's attribute information and determines the priority of checks. The checking unit can also analyze the submitter's attribute information and propose the optimal checking method. For example, the checking unit evaluates the submitter's attribute information and proposes the optimal checking method. This allows the checking to be performed while considering the submitter's attribute information. Some or all of the above processes in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input the submitter's attribute information data into AI, and the AI ​​can analyze the data and perform checks.

[0101] The checking unit can estimate the creator's emotions and adjust the order in which the check results are displayed based on the estimated emotions. For example, if the creator is relaxed, the checking unit may prioritize displaying detailed check results. For example, if the checking unit estimates the creator's emotions and is relaxed, it may prioritize displaying detailed check results. The checking unit may also prioritize displaying concise check results if the creator is in a hurry. For example, if the checking unit estimates the creator's emotions and is in a hurry, it may prioritize displaying concise check results. The checking unit may also prioritize displaying visually appealing check results if the creator is excited. For example, if the checking unit estimates the creator's emotions and is excited, it may prioritize displaying visually appealing check results. This allows the order in which the check results are displayed to be adjusted according to the creator's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input creator's emotional data into the AI, which then analyzes the data and adjusts the order in which the check results are displayed.

[0102] The checking unit can perform checks while considering the geographical distribution of the creation process. For example, the checking unit can analyze the geographical distribution of the creation process and adjust the checking criteria. For example, the checking unit can evaluate the geographical distribution of the creation process and adjust the checking criteria. The checking unit can also determine the priority of checks based on the geographical distribution. For example, the checking unit can evaluate the geographical distribution of the creation process and determine the priority of checks. The checking unit can also optimize the checking method while considering the geographical distribution. For example, the checking unit can evaluate the geographical distribution of the creation process and optimize the checking method. This allows the checking to be performed while considering the geographical distribution of the creation process. Some or all of the above processing in the checking unit may be performed using AI, for example, or without using AI. For example, the checking unit can input data on the geographical distribution of the creation process into AI, and the AI ​​can analyze the data and perform checks.

[0103] The checking unit can improve the accuracy of its checks by referring to relevant literature during the creation process. For example, the checking unit can improve the accuracy of its checks by referring to relevant literature during the creation process. For example, the checking unit can improve the accuracy of its checks by evaluating relevant literature during the creation process. The checking unit can also adjust the criteria for checking based on relevant literature. For example, the checking unit can evaluate relevant literature and adjust the criteria for checking. The checking unit can also analyze relevant literature and propose the optimal checking method. For example, the checking unit can evaluate relevant literature and propose the optimal checking method. This allows the checking unit to improve the accuracy of its checks by referring to relevant literature during the creation process. Some or all of the above processes in the checking unit may be performed using AI, for example, or without AI. For example, the checking unit can input data from relevant literature during the creation process into AI, and the AI ​​can analyze the data to improve the accuracy of its checks.

[0104] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0105] The creator certification system allows for the evaluation of a creator's technical progress by comparing their current work with their past works when they submit their creation process. For example, the submission section accumulates data on the creator's past submitted creation processes and compares it with the newly submitted process. This allows for the evaluation of the creator's technical improvement and acquisition of new skills. Furthermore, the certification issuance section can issue a certificate proving the creator's technical progress based on the comparison results with past creation processes. For example, the certification issuance section compares the techniques the creator used in the past with the techniques they have newly used to evaluate their technical progress. In addition, the link issuance section can issue certificates demonstrating technical progress in the form of links, which can be shared on social media. For example, the link issuance section issues links that creators can use to showcase their technical progress. This allows for the evaluation and verification of the creator's technical progress.

[0106] The creator verification system can estimate a creator's emotions when they submit their creation process and customize the submission based on those emotions. For example, if the creator is stressed, the system can simplify the submission to reduce their burden. For instance, the system can estimate the creator's emotions and encourage them to submit only the minimum necessary information if they are stressed. The system can also request more detailed submissions if the creator is relaxed. For example, the system can estimate the creator's emotions and encourage them to submit a detailed creation process if they are relaxed. Furthermore, the system can optimize the submission to avoid disrupting the workflow if the creator is focused. For example, the system can estimate the creator's emotions and optimize the submission if they are focused. This allows the system to customize the submission according to the creator's emotions.

[0107] The creator verification system can customize submissions by taking into account the creator's geographical location when submitting their work. For example, if the creator is in a specific region, the system will prioritize submitting work related to that region. The system can also suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring a stable environment for submission. This allows for customization of submissions by considering the creator's geographical location.

[0108] The creator verification system allows creators to submit their creation processes by analyzing their social media activity and selecting relevant processes. For example, the submission team can analyze the creator's social media activity and submit relevant processes. The submission team can also select the processes to submit based on the interests of the creator's followers. For example, the submission team can analyze the interests of the creator's followers and submit highly relevant processes. Furthermore, the submission team can adjust the timing of submissions based on the creator's social media reactions. For example, the submission team can analyze the creator's social media reactions and suggest the optimal submission timing. This allows creators to analyze their social media activity and adjust their submissions accordingly.

[0109] The creator certification system can estimate the creator's emotions when they submit their work and adjust the submission timing based on those emotions. For example, if the submission system estimates the creator's emotions and extends the deadline to allow them to submit their work in a relaxed state, it can do so. The system can also encourage submission when the creator is focused, ensuring that the workflow is not disrupted. The system can also suggest a break if the creator is tired, encouraging submission after rest. This allows the system to adjust the submission timing according to the creator's emotions.

[0110] The creator verification system can analyze a creator's past creation process and select the optimal submission method when they submit their work. For example, the submission system prioritizes suggesting submission methods (file format, submission procedure, etc.) that the creator has used in the past. For example, the submission system analyzes the creator's past submission history and suggests the optimal submission method. The submission system can also suggest the most efficient submission method based on the creator's past submission history. For example, the submission system selects the optimal submission method based on the creator's past submission history. The submission system can also analyze the creator's past creation process and suggest the most suitable timing for submission. For example, the submission system analyzes the creator's past creation process and suggests the most suitable timing for submission. This allows the system to analyze the creator's past creation process and select the optimal submission method.

[0111] The creator certification system allows for filtering of creators' work processes based on their current projects and areas of interest. For example, the system prioritizes submissions of work processes related to the creator's current projects. It can also prioritize submissions of work processes relevant to the creator's areas of interest. Furthermore, the system can select work processes to submit based on the progress of the creator's current projects. This allows for filtering of submissions based on the creator's current projects and areas of interest.

[0112] The creator verification system can estimate the creator's emotions when they submit their work processes and prioritize the submitted processes based on those emotions. For example, if the creator is feeling stressed, the system will prioritize submitting less important processes. The system can also prioritize submitting more important processes if the creator is relaxed. Furthermore, if the creator is focused, the system can adjust the submission priority to avoid disrupting their workflow. This allows the system to determine the priority of submitted processes according to the creator's emotions.

[0113] The creator verification system can prioritize the submission of creator work processes that are most relevant to the creator's location, taking into account the creator's geographical location when the creator submits their work. For example, if the creator is in a specific region, the system will prioritize submitting work processes related to that region. The system can also suggest the optimal submission timing based on the creator's geographical location. The system can also adjust the submission timing if the creator is on the move, ensuring that the work is submitted in a stable environment. This allows the system to consider the creator's geographical location when submitting work.

[0114] The creator verification system allows creators to submit their creation processes by analyzing their social media activity and selecting relevant processes. For example, the submission process can analyze the creator's social media activity and submit relevant processes. It can also select processes to submit based on the interests of the creator's followers. For example, it can analyze the interests of the creator's followers and submit highly relevant processes. Furthermore, the submission process can adjust the timing of submissions based on the creator's social media reactions. For example, it can analyze the creator's social media reactions and suggest the optimal submission timing. This allows for the analysis and submission of creators' social media activities.

[0115] The following briefly describes the processing flow for example form 2.

[0116] Step 1: The submission section is where creators submit their illustration creation process. For example, creators can submit detailed records of each step of the illustration process. For instance, the submission section might record each step, such as sketching, line drawing, coloring, and finishing. The submission section can also record the tools and techniques used by the creator. For example, it might record information about the software and hardware used. Furthermore, the submission section can record the creator's creation process in video format. For example, the submission section might record the creation process as a time-lapse video. Step 2: The Certificate Issuing Department issues a certificate of authorship based on the creation process submitted by the Submitting Department. The Certificate Issuing Department, for example, analyzes the submitted creation process and evaluates the creator's skills and effort. For example, the Certificate Issuing Department analyzes each step of the submitted creation process and evaluates the creator's skill level. The Certificate Issuing Department can also verify the legitimacy of the submitted creation process. For example, the Certificate Issuing Department checks whether the submitted creation process is consistent with other works. Step 3: The Link Issuing Unit provides the author certificate issued by the Certificate Issuing Unit in link format. The Link Issuing Unit issues the author certificate in the form of a URL link or QR code, for example. For example, the Link Issuing Unit issues a link that creators can share on social media. The Link Issuing Unit can also send the author certificate by email. For example, the Link Issuing Unit sends the author certificate link to the creator's email address. Step 4: The checking unit determines whether the data was generated by a generative AI after reliable data has been collected. For example, the checking unit verifies that the submitted illustration was not generated by a generative AI. For example, the checking unit analyzes the creation process of the submitted illustration to check for any traces of generation by a generative AI. The checking unit also analyzes the style and technique of the submitted illustration to evaluate the possibility of generation by a generative AI. For example, the checking unit analyzes the handwriting and color usage of the submitted illustration to evaluate the possibility of generation by a generative AI.

[0117] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0118] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0119] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0120] Each of the multiple elements described above, including the submission unit, certificate issuance unit, link issuance unit, and check unit, is implemented in at least one of the smart device 14 and the data processing device 12. For example, the submission unit is implemented by the control unit 46A of the smart device 14, allowing creators to record and submit the illustration creation process in detail. The certificate issuance unit is implemented by the specific processing unit 290 of the data processing device 12, analyzing the submitted creation process and evaluating the creator's skill and effort. The link issuance unit is implemented by the control unit 46A of the smart device 14, providing author certification in link format. The check unit is implemented by the specific processing unit 290 of the data processing device 12, verifying that the submitted illustration was not generated by a generation AI. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0121] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0122] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0123] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0124] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0125] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0126] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0127] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0128] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0129] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0130] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0131] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0132] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0133] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0134] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0135] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0136] Each of the multiple elements described above, including the submission unit, certificate issuance unit, link issuance unit, and check unit, is implemented in at least one of the smart glasses 214 and the data processing device 12. For example, the submission unit is implemented by the control unit 46A of the smart glasses 214, allowing creators to record and submit the illustration creation process in detail. The certificate issuance unit is implemented by the identification processing unit 290 of the data processing device 12, for example, to analyze the submitted creation process and evaluate the creator's skill and effort. The link issuance unit is implemented by the control unit 46A of the smart glasses 214, for example, to provide author certification in link format. The check unit is implemented by the identification processing unit 290 of the data processing device 12, for example, to verify that the submitted illustration was not generated by a generation AI. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0137] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0138] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0139] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0140] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0141] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0142] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0143] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0144] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0145] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0146] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0147] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0148] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0149] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0150] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0151] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0152] Each of the multiple elements described above, including the submission unit, certificate issuance unit, link issuance unit, and check unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the submission unit is implemented by the control unit 46A of the headset terminal 314, allowing creators to record and submit the illustration creation process in detail. The certificate issuance unit is implemented by the specific processing unit 290 of the data processing unit 12, analyzing the submitted creation process and evaluating the creator's skill and effort. The link issuance unit is implemented by the control unit 46A of the headset terminal 314, providing author certification in link format. The check unit is implemented by the specific processing unit 290 of the data processing unit 12, verifying that the submitted illustration was not generated by a generation AI. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0153] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0154] As shown in Figure 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.

[0155] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0156] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0157] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0158] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0159] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0160] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0161] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0162] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0163] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0164] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0165] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0166] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0167] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0168] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0169] Each of the multiple elements described above, including the submission unit, certificate issuance unit, link issuance unit, and check unit, is implemented, for example, in at least one of the robot 414 and the data processing unit 12. For example, the submission unit is implemented by the control unit 46A of the robot 414, allowing a creator to record and submit the illustration creation process in detail. The certificate issuance unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, which analyzes the submitted creation process and evaluates the creator's skill and effort. The link issuance unit is implemented, for example, by the control unit 46A of the robot 414, which provides author certification in link format. The check unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, which verifies that the submitted illustration was not generated by a generation AI. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0170] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0171] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0172] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0173] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0174] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0175] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0176] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0177] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0178] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0179] 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.

[0180] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0181] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0182] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0183] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0184] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0185] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0186] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0187] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0188] (Note 1) There is a submission section where creators submit the process of creating their illustrations, A certification issuing unit that issues author certificates based on the creation process submitted by the aforementioned submission unit, A link issuing unit that provides author certificates issued by the aforementioned certificate issuing unit in link format, It includes a checking unit that determines whether the data was generated by a generation AI after reliable data has been collected. A system characterized by the following features. (Note 2) The aforementioned submission section, The creator meticulously records and submits each step of the illustration process. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned certificate issuing unit, Authorship certificates will be issued based on the submitted creation process. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned link issuing unit, Authorship verification will be issued as a link and used for verification on social media. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned checking unit is Determine whether it was generated by a generative AI. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned checking unit is Verify that the submitted illustration was not generated by a generative AI. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned submission section, Accumulate the creator's creative process The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned submission section, The creator's creative process is made public. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned submission section, We estimate the creator's emotions and adjust the submission timing of the creation process based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned submission section, At the time of submission, we analyze the creator's past creative process and select the most suitable submission method. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned submission section, When submitting entries, filtering will be performed based on the creator's current projects and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned submission section, It estimates the creator's emotions and determines the priorities of the creation process to submit based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned submission section, When submitting, the creator's geographical location will be taken into consideration, and the most relevant creative process will be prioritized. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned submission section, At the time of submission, analyze the creator's social media activity and submit the relevant creative process. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned certificate issuing unit, We estimate the creator's emotions and adjust the way the proof is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned certificate issuing unit, When issuing a certificate, the level of detail in the certificate is adjusted based on the importance of the creation process. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned certificate issuing unit, When issuing a proof, different proof algorithms are applied depending on the category of the creation process. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned certificate issuing unit, The creator's emotions are estimated, and the length of the proof is adjusted based on the estimated emotions of the creator. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned certificate issuing unit, When issuing a certificate, the priority of the certificate is determined based on the submission timing of the creation process. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned certificate issuing unit, When issuing a certificate, the order of the certificates is adjusted based on the relevance of the creation process. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned link issuing unit, It estimates the creator's emotions and adjusts how links are displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned link issuing unit, When issuing a link, the system will refer to the creator's past link issuance history to select the most suitable link format. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned link issuing unit, When issuing a link, customize the link content based on the creator's current projects and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned link issuing unit, It estimates the creator's emotions and prioritizes links based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned link issuing unit, When issuing a link, the optimal link format is selected considering the creator's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned link issuing unit, When issuing a link, we analyze the creator's social media activity and adjust the link's content accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned checking unit is We estimate the creator's emotions and adjust the review criteria based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned checking unit is During the checking process, we improve the accuracy of the checks by considering the interrelationships between the creation processes. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned checking unit is During the review process, the attribute information of the submitter during the creation process will be taken into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned checking unit is It estimates the creator's emotions and adjusts the order in which the check results are displayed based on the estimated creator's emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned checking unit is During the check, the geographical distribution of the creation process will be taken into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned checking unit is During the checking process, we refer to relevant literature from the creation process to improve the accuracy of the check. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0189] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. There is a submission section where creators submit the process of creating their illustrations, A certification issuing unit that issues author certificates based on the creation process submitted by the aforementioned submission unit, A link issuing unit that provides author certificates issued by the aforementioned certificate issuing unit in link format, It includes a checking unit that determines whether the data was generated by a generation AI after reliable data has been collected. A system characterized by the following features.

2. The aforementioned submission section, The creator meticulously records and submits each step of the illustration process. The system according to feature 1.

3. The aforementioned certificate issuing unit, Authorship certificates will be issued based on the submitted creation process. The system according to feature 1.

4. The aforementioned link issuing unit, Authorship verification will be issued as a link and used for verification on social media. The system according to feature 1.

5. The aforementioned checking unit is Determine whether it was generated by a generative AI. The system according to feature 1.

6. The aforementioned checking unit is Verify that the submitted illustration was not generated by a generative AI. The system according to feature 1.

7. The aforementioned submission section, Accumulate the creator's creative process The system according to feature 1.

8. The aforementioned submission section, The creator's creative process is made public. The system according to feature 1.

Images