system

Abstract

Provide a system. A means for initiating the capture of original data; means for inspecting the copyright information of the original data; A means of checking whether or not a copyright exists by checking against a copyright information database; a means for generating a warning message for original data containing copyright; means for sending a warning message to the terminal to warn the user; a means for initiating the image generation process if copyright is acceptable; means for embedding a digital fingerprint in the generated image; means for transmitting the generated image to a terminal; A system including:

Description

[Technical Field]

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

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

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

[0004] Current generative AI technology does not adequately manage copyright information for the source data used by users to generate new images, which could result in unintentional copyright infringement. Therefore, there is a need for a means to verify the legitimacy of the source data when users generate images using generative AI and avoid the risk of copyright infringement. Furthermore, by assigning appropriate digital fingerprints to generated images, copyright information can be clearly displayed, preventing potential rights disputes that may arise later. [Means for solving the problem]

[0005] As claimed in the claims, the present invention provides the following means: a system including means for starting the import of original data, means for inspecting copyright information on the original data, means for verifying the existence of copyright by comparing the original data with a copyright information database, means for generating a warning message for original data containing copyright, means for warning a user by sending the warning message to a terminal, means for starting an image generation process if the copyright is not an issue, means for embedding a digital fingerprint in the generated image, and means for transmitting the generated image to a terminal. This allows users to verify the legitimacy of the original data and avoid the risk of copyright infringement. Furthermore, by adding a digital fingerprint to the generated image, copyright information can be clearly indicated, preventing potential rights disputes that may arise later.

[0006] "Original data" refers to existing images and data that generative AI needs to generate new images.

[0007] "Copyright information" is information indicating that a particular content is a copyrighted work protected by law.

[0008] A "copyright information database" is a database that collects information on copyrighted content.

[0009] A "warning message" is a message that notifies the user that the original data poses a risk of copyright infringement.

[0010] A "pop-up message" is a type of message that suddenly appears on the screen and is used to convey important information to the user.

[0011] The "image generation process" refers to a series of steps in which the generative AI generates a new image based on a user request.

[0012] "Digital fingerprinting" is a technology that embeds identifying information into digital content.

[0013] "Digital watermarking technology" is a technology that adds copyright information and identification information by embedding invisible information in digital content.

[0014] A "terminal" is a device that allows a user to access the generated AI and send requests.

[0015] The "server" is the central processing unit on which the generation AI runs, inspecting copyright information and carrying out the image generation process. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes various means such as importing the original data, inspecting the copyright information, comparing it with a copyright information database, generating and sending a warning message, the image generation process, assigning a digital fingerprint, and providing the generated image.

[0038] Detailed system description

[0039] Users can generate new images using generated AI.

[0040] The user accesses the generative AI application and makes a request to generate a new image, for example, "I want you to generate an illustration of a cat."

[0041] Importing original data and checking copyright information

[0042] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0043] Copyright Infringement Warning

[0044] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0045] Image generation when there are no problems

[0046] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0047] Digital fingerprinting

[0048] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0049] Providing generated images

[0050] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0051] Specific examples

[0052] Example 1: Copyright Infringement Warning Process

[0053] When a user requests an "illustration of a famous character" using the generation AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The device displays a warning saying, "This content is copyrighted and cannot be used," and the user inputs a new request.

[0054] Example 2: Normal image generation process

[0055] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data has no copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device, which then displays the image to the user. The user then downloads the resulting landscape painting.

[0056] The above is a detailed description of the embodiment of the present invention. This system allows users to use AI generation with peace of mind and avoids the risk of copyright infringement.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0060] Step 2:

[0061] The terminal sends the user's request to the server.

[0062] Step 3:

[0063] The server receives the request and retrieves the raw data required to generate the image.

[0064] Step 4:

[0065] After the server retrieves the original data, it checks the copyright information of the original data.

[0066] Step 5:

[0067] The server checks the original data against a copyright information database to see if the original data contains copyright.

[0068] Step 6:

[0069] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[0070] Step 7:

[0071] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[0072] Step 8:

[0073] Sends server-generated warning messages to the terminal.

[0074] Step 9:

[0075] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[0076] Step 10:

[0077] The user confirms the warning message and enters a new request.

[0078] Step 11:

[0079] The server receives the request again and inspects the original data (resume from step 3).

[0080] Step 12:

[0081] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[0082] Step 13:

[0083] A generation AI built into the server generates a new image based on the request.

[0084] Step 14:

[0085] The server will double-check the copyright information on the generated image.

[0086] Step 15:

[0087] If the server generates an image containing copyright, it embeds a digital fingerprint.

[0088] Step 16:

[0089] The server verifies that the digital fingerprint embedding was completed successfully.

[0090] Step 17:

[0091] The server transmits the generated image to the terminal.

[0092] Step 18:

[0093] The terminal displays the generated image to the user and allows the user to download it.

[0094] Step 19:

[0095] The user can review the generated images and download or request new ones as needed.

[0096] Example 1

[0097] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0098] In recent years, the use of generative AI models to generate images has been increasing, but there is a need to properly manage copyright information for the original data. If generated images are distributed without verifying whether the original data is copyrighted, the risk of copyright infringement increases. Furthermore, if warnings and countermeasures against copyright infringement are insufficient, users may feel uneasy about using the generated images. The purpose of this invention is to solve these problems and provide a system that reliably manages copyright when generating images using generative AI models.

[0099] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0100] In this invention, the server includes means for a user to input a prompt sentence, means for starting import of original data, means for inspecting copyright information of the original data, means for checking the copyright existence by comparing the original data with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn the user, means for starting an image generation process if there is no copyright issue, means for embedding a digital fingerprint in the generated image, and means for sending the generated image to the terminal. This makes it possible to properly manage copyright information and safely generate images using a generative AI model while avoiding the risk of copyright infringement.

[0101] The "means for the user to input a prompt sentence" is an interface through which the user inputs a text-based request for image generation by the generative AI model.

[0102] "Means to start importing original data" refers to the function by which the generative AI model obtains initial data in response to a user request and imports it into the system.

[0103] The "means for inspecting copyright information of original data" is a function for analyzing and checking the copyright information contained in the imported original data.

[0104] "Means for checking copyright by comparing with copyright information database" is a function for checking the copyright information of the original data against an existing database to confirm whether the original data is protected by copyright.

[0105] The "means for generating a warning message for original data containing copyright" is a function for generating a warning message for original data that is protected by copyright.

[0106] The "means for sending a warning message to a terminal to warn a user" is a function for sending a generated warning message to a user's terminal and notifying the user of the warning.

[0107] "Means for initiating the image generation process if there are no copyright issues" refers to a function that starts the process of generating a new image using a generative AI model if it is confirmed that there are no copyright issues.

[0108] "Means for embedding a digital fingerprint into the generated image" refers to a function that embeds a digital fingerprint (e.g., a digital watermark) into the generated image to clearly indicate the copyright information of the image.

[0109] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal so that the user can view, save or use the image.

[0110] This invention is a system that properly manages copyright information of original data when a user generates an image using a generative AI model, thereby avoiding the risk of copyright infringement. The main components of this system are a server, a terminal, and a user. The specific hardware and software configuration and data processing procedures are described below.

[0111] System Configuration

[0112] User

[0113] Users access the generative AI application and request the generation of a new image. Examples of prompts include "I want you to generate an illustration of a cat" or "I want you to generate a landscape painting of a sunset."

[0114] server

[0115] The server is equipped with hardware and software for receiving user requests and performing the following processes:

[0116] Hardware: Server equipment with a powerful CPU, GPU, and sufficient storage.

[0117] Software: Programming environments including Python and JavaScript (registered trademark), PIL (Pillow) and OpenCV for metadata analysis, database management systems (e.g., MySQL (registered trademark) and PostgreSQL) for copyright information management, and APIs for accessing generative AI models (e.g., DALL-E and Stable Diffusion).

[0118] Terminal

[0119] A web browser is installed on the user's device, which displays instructions from the server and accepts user operations. The device supports HTML and JavaScript to display warning messages in a pop-up format.

[0120] Specific examples

[0121] Example 1: Copyright Infringement Warning Process

[0122] When a user requests an "illustration of a famous character" using the generation AI, the server checks the copyright information of the original data and compares it with the copyright information database. If the server detects that the original data contains the copyright of "Character A," it generates a warning message and sends it to the device. The device displays a warning saying, "This content is copyrighted and therefore unavailable," and the user must re-enter a new request.

[0123] Example 2: Normal image generation process

[0124] When a user requests a "sunset landscape painting," the server checks the copyright information of the original data and compares it with a copyright information database. If the original data is found to have no copyright issues, the server activates a generative AI model to generate an image based on the user's request. The server then embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. After the fingerprint has been embedded, the server sends the generated image to the user's device. The device displays the image to the user and makes it available for download.

[0125] This allows users to use generative AI models safely and securely, and generate images with copyright information managed.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] The user enters a prompt statement

[0129] The user inputs a prompt through the interface of the generation AI application. For example, they might input "I want a cat illustration generated" and click the send button. Input: Prompt text "I want a cat illustration generated." Output: The prompt text is sent to the server. Specifically, the user inputs a request text into the text box and clicks the send button.

[0130] Step 2:

[0131] The server retrieves the original data

[0132] The server receives the prompt sentence sent by the user and retrieves the related original data from the storage system. This original data is temporarily stored in memory. Input: User's prompt sentence. Output: Related original data. Specifically, the server retrieves the original data from storage (e.g., cloud storage) and stores it in memory.

[0133] Step 3:

[0134] The server checks the copyright information of the original data

[0135] The server analyzes the metadata of the imported original data using PIL (Pillow) or OpenCV and extracts copyright information. Input: Original data. Output: Copyright information. Specifically, the server runs a program and uses a metadata analysis library to obtain copyright information from the original data.

[0136] Step 4:

[0137] The server checks the copyright information against a database

[0138] The server compares the extracted copyright information with a dedicated database to determine whether the original data is copyrighted. Input: Copyright information. Output: Determination result regarding copyright status. Specifically, the server uses an SQL query to check the compatibility of the database.

[0139] Step 5:

[0140] The server generates a warning message and sends it to the device.

[0141] If copyrighted original data is detected, the server generates a warning message and sends it to the user's device. Input: Judgment result on whether copyright is included. Output: Warning message. Specifically, the server creates a warning message using HTML and JavaScript and sends it to the device as an HTTP response.

[0142] Step 6:

[0143] The device displays a warning message

[0144] The user's device displays the warning message sent from the server in a pop-up format. Input: Warning message. Output: Pop-up warning message. Specifically, the browser executes JavaScript and displays the warning on the screen.

[0145] Step 7:

[0146] The user enters a new prompt.

[0147] Upon receiving the warning, the user re-enters a new prompt. Input: New prompt. Output: Send the new prompt to the server. Specifically, the user re-enters the request text in the text box and clicks the send button.

[0148] Step 8:

[0149] If the server has no copyright issues, it starts the image generation process.

[0150] If the server confirms that there are no copyright issues, it begins generating images using a generative AI model (for example, DALL-E or Stable Diffusion). Input: Prompt text. Output: Generated image. Specifically, the server sends a request to the API of the generative AI model to generate an image.

[0151] Step 9:

[0152] The server embeds a digital fingerprint into the generated image.

[0153] The server embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. Input: Generated image. Output: Image with embedded fingerprint. Specifically, the server uses libraries such as OpenCV or PyMuPDF to add a digital watermark to the image.

[0154] Step 10:

[0155] The server provides the generated image to the user's device

[0156] After the fingerprint embedding is complete, the server sends the generated image to the user's device. Input: Image with embedded fingerprint. Output: Image displayed to the user. Specifically, the server sends the image as an HTTP response, and the browser displays it.

[0157] This is the specific processing flow of the system. Through these steps, users can use the generative AI model with confidence and obtain images with properly managed copyright information.

[0158] (Application example 1)

[0159] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0160] Conventional image generation systems using generative AI have insufficient management of copyright information, which means that images generated by users may unknowingly infringe copyrights. Furthermore, digital fingerprints to protect the copyright of generated images are often not assigned. This increases the risk of copyright infringement, making it difficult for users to use image generation services with peace of mind. Furthermore, similar security services are needed when users use various devices, such as smartphones, smart glasses, head-mounted displays, and robots, but previous systems have not been able to provide sufficient security.

[0161] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0162] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information, means for checking against a copyright information database to confirm the presence or absence of copyright, means for generating a warning message for original data that includes copyright, means for sending a warning message to a terminal to warn the user, means for starting an image generation process if the copyright is not an issue, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, and means for operating various means such as import of original data, inspection of copyright information, checking against the copyright information database, generation and transmission of a warning message, image generation process, assignment of a digital fingerprint, and provision of the generated image using an application installed on a smartphone, smart glasses, a head-mounted display, and a robot.

[0163] This allows users to properly manage copyright information when creating images, preventing copyright infringement and ensuring that the copyright of the created images is protected. It also supports a variety of devices, including smartphones, smart glasses, head-mounted displays, and robots, providing consistent security services regardless of the device the user uses.

[0164] "Original data" refers to information such as images and text that serves as the basis for use by the generating AI.

[0165] "Copyright information" refers to legal rights information regarding the ownership and usage rights of the original data.

[0166] A "copyright information database" is a database that holds information on content for which copyrights are registered.

[0167] A "warning message" is a message that notifies the user of a possible copyright infringement.

[0168] A "terminal" is a device operated by a user, and includes a smartphone, smart glasses, a head-mounted display, a robot, etc.

[0169] The "image generation process" is the process of using generative AI to generate a new image based on a user request.

[0170] "Digital fingerprinting" refers to techniques such as digital watermarking for embedding copyright information into generated images.

[0171] A "smartphone" is a mobile phone equipped with internet connectivity and various applications.

[0172] "Smart glasses" are glasses-type information terminals that provide visual information.

[0173] A "head-mounted display" is an information display device that is worn on the head and provides visual information.

[0174] A "robot" is a mechanical device used to perform automated operations or tasks.

[0175] An "application" is a software program designed to perform a specific function or task.

[0176] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system operates through an application installed on information terminals such as smartphones, smart glasses, head-mounted displays, and robots.

[0177] The server receives an image generation request from the user and begins to import the original data. It then performs a copyright information check on the imported original data and compares it with a copyright information database. This comparison confirms whether the original data is copyrighted. If it is confirmed to be copyrighted, the server generates a warning message and sends it to the terminal to notify the user. This warning message is displayed in a pop-up format, stating, "This content cannot be used because it contains copyright information."

[0178] On the other hand, if it is confirmed that there are no copyright issues, the server begins the image generation process. It uses a generative AI model (e.g., a model using TENSORFLOW (registered trademark) or PyTorch) to generate a new image based on the user's request. The generated image is also checked for copyright information again, and a digital fingerprint (e.g., digital watermarking technology) is embedded if necessary. After the digital fingerprint has been embedded, the generated image is sent to the user's device, where it can be viewed and downloaded.

[0179] As an example of how this system can be used, consider the case where a user makes a request from their smartphone to "generate an illustration of a cathedral." The server inspects the original data, checks it against a copyright information database to ensure there are no violations, and then generates an illustration of the cathedral using a generative AI model. A digital fingerprint is embedded in the generated illustration, which is sent to the user's smartphone. The user can then view and download the generated illustration.

[0180] An example prompt is:

[0181] "I want to generate an illustration of a cathedral."

[0182] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0183] Step 1:

[0184] A user sends an image generation request from a smartphone, smart glasses, head-mounted display, or robot. A prompt sentence (e.g., "Please generate an illustration of a cathedral") is sent as input. The server receives this request. The request content is passed to the server as output.

[0185] Step 2:

[0186] The server starts fetching raw data based on the received prompt statement. The prompt statement is used as input. The server retrieves the relevant raw data from a database or storage. The raw data is fetched as output.

[0187] Step 3:

[0188] The server checks the copyright information of the imported original data. The imported original data is used as input. The server compares the original data with the copyright information database to check whether the copyright is included. The output is the check result (whether or not the copyright exists).

[0189] Step 4:

[0190] The server generates a warning message if copyright is included based on the inspection result. The inspection result is used as input. The server generates a warning message saying "This content is copyrighted and therefore unavailable." The warning message is obtained as output.

[0191] Step 5:

[0192] The server sends the generated warning message to the terminal and notifies the user. The warning message is used as input. The terminal displays the received warning message in a popup format. The warning message is displayed to the user as output.

[0193] Step 6:

[0194] The server starts the image generation process if there are no copyright issues. The prompt and inspection results are used as input. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate an image based on the user's request. The generated image is obtained as output.

[0195] Step 7:

[0196] The server embeds a digital fingerprint into the generated image. The generated image is used as input. The server embeds the fingerprint into the image using digital watermarking technology. The output is an image with the embedded digital fingerprint.

[0197] Step 8:

[0198] The server sends the generated image with the embedded digital fingerprint to the terminal, which uses the fingerprinted image as input and displays the received image to the user and makes it available for download, providing the generated image as output, viewable by the user.

[0199] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0200] This invention is a system that combines a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI with an emotion engine that recognizes the user's emotions. This system includes means for importing original data, means for inspecting copyright information, means for comparing with a copyright information database, means for generating and transmitting warning messages, an image generation process, means for assigning digital fingerprints, means for providing generated images, and an emotion engine.

[0201] Detailed system description

[0202] Users can generate new images using generated AI.

[0203] The user accesses the generative AI application and makes a request to generate a new image. For example, they input a request such as "I want you to generate an illustration of a cat."

[0204] Importing original data and checking copyright information

[0205] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0206] Copyright Infringement Warning

[0207] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0208] Image generation when there are no problems

[0209] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0210] Digital fingerprinting

[0211] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0212] Providing generated images

[0213] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0214] Use of emotion engine

[0215] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[0216] The emotion engine also analyzes the user's emotional response to the warning message and provides information to the server if the user is feeling stressed or dissatisfied. The server can then use this information to provide an explanation or alternative solution that the user can understand.

[0217] Specific examples

[0218] Example 1: Copyright Infringement Warning Process

[0219] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The emotion engine also monitors the user's reaction to the warning message, and if the user feels disappointed or dissatisfied, it sends that information to the server. The server can then suggest other materials and resources that the user can use.

[0220] Example 2: Normal image generation process

[0221] When a user requests a "sunset landscape painting," the server checks the database to ensure there are no copyright issues with the original data. The server then starts the image generation process and embeds a digital fingerprint into the generated landscape painting. After the embedding is complete, the server sends the generated landscape painting to the user's device. The emotion engine monitors the user's reaction and checks whether the user is satisfied. This information is fed back to the server and reflected in future image generation processes.

[0222] The above is a detailed description of an embodiment of the present invention. This system allows users to use generative AI with peace of mind and avoids the risk of copyright infringement. In addition, the use of an emotion engine can increase user satisfaction.

[0223] The processing flow will be explained below.

[0224] Step 1:

[0225] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0226] Step 2:

[0227] The terminal sends the user's request to the server.

[0228] Step 3:

[0229] The server receives the request and retrieves the raw data required to generate the image.

[0230] Step 4:

[0231] After the server retrieves the original data, it checks the copyright information of the original data.

[0232] Step 5:

[0233] The server checks the original data against a copyright information database to see if the original data contains copyright.

[0234] Step 6:

[0235] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[0236] Step 7:

[0237] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[0238] Step 8:

[0239] Sends server-generated warning messages to the terminal.

[0240] Step 9:

[0241] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[0242] Step 10:

[0243] The emotion engine monitors the user's reaction to the warning message on the device and collects the user's emotion data.

[0244] Step 11:

[0245] The user enters a new request or takes the appropriate action.

[0246] Step 12:

[0247] The server receives the request again and inspects the original data (resume from step 3).

[0248] Step 13:

[0249] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[0250] Step 14:

[0251] A generation AI built into the server generates a new image based on the request.

[0252] Step 15:

[0253] The emotion engine analyzes the user's emotions while executing the request and sends the information to the server.

[0254] Step 16:

[0255] The server will double-check the copyright information on the generated image.

[0256] Step 17:

[0257] If the server generates an image containing copyright, it embeds a digital fingerprint.

[0258] Step 18:

[0259] The server verifies that the digital fingerprint embedding was completed successfully.

[0260] Step 19:

[0261] The server transmits the generated image to the terminal.

[0262] Step 20:

[0263] The terminal displays the generated image to the user and allows the user to download it.

[0264] Step 21:

[0265] The emotion engine monitors the user's reactions as they view the generated images and collects their emotion data.

[0266] Step 22:

[0267] The collected emotion data is fed back to the server and used to optimize future image generation processes.

[0268] Step 23:

[0269] The user can review the generated images and download or request new ones as needed.

[0270] Example 2

[0271] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0272] Conventional generative AI systems often lacked methods for properly managing copyright information on the original data and effectively preventing violations. Furthermore, they were unable to incorporate the emotions felt by users during the image generation process, which hindered efforts to improve user satisfaction. Furthermore, there was an insufficient method for clearly indicating copyright information on generated images, making copyright protection of images difficult.

[0273] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0274] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the existence of copyright by comparing it with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn a user, means for starting an image generation process if the copyright is not an issue, means for using a generative AI model in the image generation process, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, means for using an emotion engine for recognizing user emotions, and means for analyzing emotion data obtained from the emotion engine to optimize the image generation process. This makes it possible to appropriately manage the copyright of the original data and improve user satisfaction, while avoiding the risk of copyright infringement and effectively indicating copyright information on generated images.

[0275] 1. "Original Data" refers to the initial data used to generate an image, including user-entered text and image files.

[0276] 2. "Copyright Information" refers to information that describes the legally protected rights and details of such rights regarding data and content.

[0277] 3. "Copyright Information Database" refers to a database that stores copyright-related information and makes it searchable and collatable.

[0278] 4. "Warning Message" means an alert message that notifies the user of a possible copyright infringement.

[0279] 5. "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to operate an image generation system.

[0280] 6. “Image generation process” refers to the general procedure for using a generative AI model to create a new image based on a user request.

[0281] 7. "Generative AI model" refers to algorithms or software that use artificial intelligence techniques to generate new images from user input data.

[0282] 8. "Digital fingerprint" refers to identification information applied to a generated image, and refers to a method of clearly indicating copyright information using digital watermarking technology, etc.

[0283] 9. "Emotion engine" refers to technology or software for recognizing and analyzing user emotions.

[0284] 10. "Emotion Data" refers to data regarding a user's emotions obtained by the emotion engine.

[0285] The present invention provides a system for appropriately managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes a means for importing original data, a means for inspecting copyright information, a means for comparing with a copyright information database, a means for generating and transmitting a warning message, an image generation process, a means for assigning a digital fingerprint, a means for providing the generated image, and an emotion engine. The embodiments of each element are described in detail below.

[0286] Importing original data and checking copyright information

[0287] The server receives a request from the user and starts to retrieve the original data. Specifically, the user accesses the generation AI application and inputs a request such as "I want you to generate an illustration of a cat." The request is sent to the server as an HTTP request.

[0288] After the original data is imported into the server, the server checks it for copyright information. To do this, the server uses specialized analysis software to extract metadata and existing copyright information from the original data. The extracted copyright information is then checked against internal or external copyright information databases via API.

[0289] Copyright strike and re-entry request

[0290] If the original data contains copyright, the server generates a warning message and sends it to the terminal. This message states, "This content is copyrighted and cannot be used," and the user must re-enter the request. This warning message is displayed in a pop-up format.

[0291] Image Generation Process

[0292] When a user inputs a request that does not have copyright issues, the server starts the image generation process. The server launches a generative AI model and inputs the user's prompt (e.g., "I want you to generate a landscape painting of a sunset") into the model. Technologies such as Stable Diffusion and DALL-E are used as the generative AI model.

[0293] Digital fingerprinting

[0294] If the generated image is verified as legitimate, the server embeds a digital fingerprint into the image, using digital watermarking technology, which clearly identifies the copyright information for the generated image.

[0295] Providing generated images

[0296] The image with the embedded digital fingerprint is then sent back from the server to the user's device, where the generated image is displayed and made available for download.

[0297] Use of emotion engine

[0298] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[0299] The emotion engine also analyzes the user's emotional response to the warning message and provides information about stress or frustration to the server, which can then provide a more understandable explanation or alternative, such as suggesting the use of other permitted material.

[0300] This invention allows users to use generative AI with peace of mind, avoiding the risk of copyright infringement, and increases user satisfaction through the use of an emotion engine.

[0301] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0302] Step 1:

[0303] Description: A user accesses the generative AI application and enters a request to generate an image.

[0304] Input: The user enters the prompt "I want an illustration of a cat."

[0305] How it works: The user launches a browser or a dedicated app, enters a prompt in the text box, and clicks the "Submit" button.

[0306] Output: The entered prompt text is sent to the server as an HTTP request.

[0307] Step 2:

[0308] Description: The server receives the user request and starts fetching the raw data.

[0309] Input: The prompt text included in the HTTP request received by the server.

[0310] What happens: The server parses the HTTP request and begins the process of retrieving the original data.

[0311] Output: The original data is temporarily saved.

[0312] Step 3:

[0313] Description: The server checks the original data for copyright information and matches it with a copyright information database.

[0314] Input: Temporarily saved original data.

[0315] How it works: The server uses analysis software to extract metadata and copyright information from the raw data, and sends API requests to a copyright information database for matching.

[0316] Output: The result of the copyright check.

[0317] Step 4:

[0318] Description: If the server verifies the copyright information and finds any problems, it generates a warning message and sends it to the user's device.

[0319] Input: If the copyright information check results in "problem".

[0320] Behavior: The server generates a warning message stating "This content is copyrighted and therefore unavailable" and sends it to the device as an HTTP response.

[0321] Output: A warning message is displayed on the terminal.

[0322] Step 5:

[0323] Description: If the server has no copyright issues, it will start the image generation process.

[0324] Input: If the copyright information check result is "OK".

[0325] How it works: The server launches a generative AI model (e.g., Stable Diffusion or DALL-E) and passes the prompt statement as input.

[0326] Output: The generative AI model generates new image data.

[0327] Step 6:

[0328] Description: The server double-checks the generated image for copyright information and embeds a digital fingerprint if copyright is present.

[0329] Input: The newly generated image data.

[0330] How it works: The server uses digital watermarking technology to embed copyright information into the image as a digital fingerprint.

[0331] Output: Image data with embedded digital fingerprint.

[0332] Step 7:

[0333] Description: The server sends the generated image to the user's device.

[0334] Input: Image data with embedded digital fingerprint.

[0335] Operation: The server sends the image data to the user's device as an HTTP response.

[0336] Output: The generated image is displayed on the device, ready for the user to download.

[0337] Step 8:

[0338] Description: The emotion engine monitors the user's reactions and provides this information to the server.

[0339] Input: Emotional data such as user behavior, facial expressions, and tone of voice.

[0340] How it works: The emotion engine analyzes the user's reactions using the camera and microphone, and sends the analysis results back to the server.

[0341] Output: The server receives the emotion data and uses the analysis results to improve the image generation process in the future.

[0342] By following the above steps, the system can safely generate images based on the user's prompt sentence, improving user satisfaction.

[0343] (Application example 2)

[0344] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] When generating images using generative AI technology, it is necessary to properly manage the copyright information of the original data to avoid the risk of copyright infringement by users and to increase user satisfaction. It is also important to understand how users feel about their experience during the generation process and provide feedback accordingly.

[0346] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the presence or absence of intellectual property by comparing the original data with a copyright information database, means for generating a warning message for original data that includes intellectual property, means for sending the warning message to the terminal to warn the user, means for starting the image generation process if the intellectual property is not a problem, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, an emotion engine for analyzing the user's emotions, means for receiving feedback from the emotion engine, and means for optimizing the image generation process based on the feedback. This enables accurate management of intellectual property information and optimal image generation according to the user's emotions.

[0347] The "means for initiating the import of raw data" is a function for initiating a process based on data provided by the user.

[0348] The "means for inspecting copyright information of original data" is a function for checking copyright information included in the original data.

[0349] "Means for checking the existence of intellectual property by checking against the copyright information database" is a function for comparing the copyright information database with the original data to check whether intellectual property rights exist.

[0350] The "means for generating a warning message for original data containing intellectual property" is a function for generating a warning message to the user when intellectual property is included in the original data.

[0351] The "means for sending a warning message to the terminal to warn the user" is a function for sending a warning message to the user's terminal and notifying the user.

[0352] The "means for starting the image generation process when there are no intellectual property issues" is a function for starting image generation based on original data that has no copyright issues.

[0353] The "means for embedding a digital fingerprint in the generated image" is a function for embedding a digital fingerprint in the generated image to identify the ownership and origin of the image.

[0354] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal.

[0355] The "emotion engine that analyzes user emotions" is a component that analyzes the user's emotions and provides feedback based on that data.

[0356] The "means for receiving feedback from the emotion engine" is a function for receiving emotion information analyzed by the emotion engine and adjusting the process based on that information.

[0357] The "means for optimizing the image generation process based on feedback" is a function for optimizing the image generation process based on feedback information obtained from the emotion engine, thereby increasing user satisfaction.

[0358] The system of the present invention implements a series of processes, including the import of original data, the search for copyright information, the image generation process, the assignment of a digital fingerprint, and feedback by an emotion engine. Specific embodiments will be described below.

[0359] Program Generation and Processing Description

[0360] This system is a combination of a server, a user terminal, and an emotion engine, and each function works in cooperation with the others.

[0361] Hardware and Software Configuration

[0362] Server: This is the main component that imports original data, checks and collates copyright information, generates images, assigns digital fingerprints, and processes feedback from the emotion engine. The server contains an image processing API (ImageProcessingAPI), an emotion analysis API (EmotionAPI), and a copyright information inspection API (CopyrightCheckAPI).

[0363] User terminal: A device on which a user inputs image generation requests and receives generated images and alert messages. Examples include mobile devices such as smartphones and tablets.

[0364] Emotion Engine: A component that analyzes the user's emotions and provides the feedback to the server. The emotion engine is designed to analyze the user's input data and reactions.

[0365] System operation explanation

[0366] 1. Importing original data: Receive an image generation request from the user device. For example, the user may input a request such as "I want an illustration of a cat to be generated."

[0367] 2. Copyright information inspection and matching: The server searches for the copyright information of the original data and matches it with the copyright information database. For example, if the original data is "Character A", it will compare it with the copyright database to see if the character is copyrighted.

[0368] 3. Generating a warning message: If the server detects that the original data contains copyrighted material, it generates a warning message and sends it to the user's device. For example, if a user requests an illustration of a famous character, the server sends a message stating, "This content is copyrighted and therefore unavailable."

[0369] 4. Image generation process: If there are no copyright issues, the server uses the generation AI to generate a new image based on the user request. For example, if a user requests a "sunset landscape painting," the server generates a landscape painting after confirming that there are no issues with the copyright database.

[0370] 5. Digital Fingerprinting: The server embeds a digital fingerprint into the generated image, using digital watermarking technology to clearly indicate copyright information for the image.

[0371] 6. Providing the generated image: The image with the embedded fingerprint is sent to the user's device, allowing the user to view and download the image.

[0372] 7. Use of Emotion Engine: The emotion engine analyzes the user's emotions regarding requests and warning messages and feeds the data back to the server, which then optimizes the image generation process based on this feedback to improve user satisfaction.

[0373] Specific examples

[0374] Copyright Strike Process

[0375] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains copyright. The server then sends a pop-up message to the user's device stating, "This content is copyrighted and cannot be used."

[0376] Normal image generation process

[0377] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data is free of copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device.

[0378] Prompt Sentence Examples

[0379] "I want to generate a sunset landscape image."

[0380] "I want you to generate an illustration of a cat"

[0381] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0382] Step 1:

[0383] The user inputs an image generation request from the terminal. For example, the user inputs a prompt such as "I want an illustration of a cat." The input prompt is sent to the system. The input data is passed to the server as a user request.

[0384] Step 2:

[0385] The server starts capturing the original data, collects relevant image data based on the prompts from the user, and passes the captured original data to the inspection process, which then uses the captured original data as input data for copyright information inspection.

[0386] Step 3:

[0387] The server checks the copyright information of the original data, analyzes the imported data, and processes it to extract the copyright information. The results of this data processing are compared with a copyright information database.

[0388] Step 4:

[0389] The server checks the existence of intellectual property by checking against the copyright information database. The copyright information extracted from the original data is compared with the database to check whether the rights exist. Based on the results from the database, the existence of intellectual property is output.

[0390] Step 5:

[0391] If intellectual property is included, the server generates a warning message. If intellectual property is included, a message to warn the user is generated and sent to the terminal as a warning. Specifically, the message reads, "This content cannot be used because it contains copyright."

[0392] Step 6:

[0393] A warning message is displayed in a pop-up format on the user's device. The user can correct or re-enter the request. The displayed warning message is notified to the user, and the user's reaction is analyzed by the emotion engine.

[0394] Step 7:

[0395] If the intellectual property is clear, the server starts the image generation process. It runs a generative AI model using the original data that has passed copyright inspection to generate a new image. This generated image is then passed on to the next step in the process.

[0396] Step 8:

[0397] The server embeds a digital fingerprint into the generated image. The server then embeds copyright information into the generated image using digital watermarking technology. This process clearly identifies the copyright information for the image.

[0398] Step 9:

[0399] The server sends the generated image to the user's device. The image data with the embedded fingerprint is transferred to the user's device, where it can be downloaded and displayed by the user. The image sent to the device is then confirmed by the user.

[0400] Step 10:

[0401] The emotion engine analyzes the user's emotions. It monitors the user's reaction to the images sent to the device and feeds that data back to the server. The user's emotional data is analyzed and used for further processing.

[0402] Step 11:

[0403] The server receives feedback from the emotion engine and optimizes the image generation process. Based on the user's emotion data, it adjusts the parameters of the AI ​​model and prompts to optimize the generation process from the next time onwards. This improves user satisfaction.

[0404] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0405] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0406] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0407] [Second embodiment]

[0408] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0409] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0410] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0411] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0412] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0413] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0414] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0415] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0416] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0417] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0418] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0419] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0420] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes various means such as importing the original data, inspecting the copyright information, comparing it with a copyright information database, generating and sending a warning message, the image generation process, assigning a digital fingerprint, and providing the generated image.

[0421] Detailed system description

[0422] Users can generate new images using generated AI.

[0423] The user accesses the generative AI application and makes a request to generate a new image, for example, "I want you to generate an illustration of a cat."

[0424] Importing original data and checking copyright information

[0425] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0426] Copyright Infringement Warning

[0427] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0428] Image generation when there are no problems

[0429] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0430] Digital fingerprinting

[0431] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0432] Providing generated images

[0433] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0434] Specific examples

[0435] Example 1: Copyright Infringement Warning Process

[0436] When a user requests an "illustration of a famous character" using the generation AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The device displays a warning saying, "This content is copyrighted and cannot be used," and the user inputs a new request.

[0437] Example 2: Normal image generation process

[0438] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data has no copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device, which then displays the image to the user. The user then downloads the resulting landscape painting.

[0439] The above is a detailed description of the embodiment of the present invention. This system allows users to use AI generation with peace of mind and avoids the risk of copyright infringement.

[0440] The processing flow will be explained below.

[0441] Step 1:

[0442] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0443] Step 2:

[0444] The terminal sends the user's request to the server.

[0445] Step 3:

[0446] The server receives the request and retrieves the raw data required to generate the image.

[0447] Step 4:

[0448] After the server retrieves the original data, it checks the copyright information of the original data.

[0449] Step 5:

[0450] The server checks the original data against a copyright information database to see if the original data contains copyright.

[0451] Step 6:

[0452] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[0453] Step 7:

[0454] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[0455] Step 8:

[0456] Sends server-generated warning messages to the terminal.

[0457] Step 9:

[0458] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[0459] Step 10:

[0460] The user confirms the warning message and enters a new request.

[0461] Step 11:

[0462] The server receives the request again and inspects the original data (resume from step 3).

[0463] Step 12:

[0464] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[0465] Step 13:

[0466] A generation AI built into the server generates a new image based on the request.

[0467] Step 14:

[0468] The server will double-check the copyright information on the generated image.

[0469] Step 15:

[0470] If the server generates an image containing copyright, it embeds a digital fingerprint.

[0471] Step 16:

[0472] The server verifies that the digital fingerprint embedding was completed successfully.

[0473] Step 17:

[0474] The server transmits the generated image to the terminal.

[0475] Step 18:

[0476] The terminal displays the generated image to the user and allows the user to download it.

[0477] Step 19:

[0478] The user can review the generated images and download or request new ones as needed.

[0479] Example 1

[0480] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0481] In recent years, the use of generative AI models to generate images has been increasing, but there is a need to properly manage copyright information for the original data. If generated images are distributed without verifying whether the original data is copyrighted, the risk of copyright infringement increases. Furthermore, if warnings and countermeasures against copyright infringement are insufficient, users may feel uneasy about using the generated images. The purpose of this invention is to solve these problems and provide a system that reliably manages copyright when generating images using generative AI models.

[0482] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0483] In this invention, the server includes means for a user to input a prompt sentence, means for starting import of original data, means for inspecting copyright information of the original data, means for checking the copyright existence by comparing the original data with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn the user, means for starting an image generation process if there is no copyright issue, means for embedding a digital fingerprint in the generated image, and means for sending the generated image to the terminal. This makes it possible to properly manage copyright information and safely generate images using a generative AI model while avoiding the risk of copyright infringement.

[0484] The "means for the user to input a prompt sentence" is an interface through which the user inputs a text-based request for image generation by the generative AI model.

[0485] "Means to start importing original data" refers to the function by which the generative AI model obtains initial data in response to a user request and imports it into the system.

[0486] The "means for inspecting copyright information of original data" is a function for analyzing and checking the copyright information contained in the imported original data.

[0487] "Means for checking copyright by comparing with copyright information database" is a function for checking the copyright information of the original data against an existing database to confirm whether the original data is protected by copyright.

[0488] The "means for generating a warning message for original data containing copyright" is a function for generating a warning message for original data that is protected by copyright.

[0489] The "means for sending a warning message to a terminal to warn a user" is a function for sending a generated warning message to a user's terminal and notifying the user of the warning.

[0490] "Means for initiating the image generation process if there are no copyright issues" refers to a function that starts the process of generating a new image using a generative AI model if it is confirmed that there are no copyright issues.

[0491] "Means for embedding a digital fingerprint into the generated image" refers to a function that embeds a digital fingerprint (e.g., a digital watermark) into the generated image to clearly indicate the copyright information of the image.

[0492] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal so that the user can view, save or use the image.

[0493] This invention is a system that properly manages copyright information of original data when a user generates an image using a generative AI model, thereby avoiding the risk of copyright infringement. The main components of this system are a server, a terminal, and a user. The specific hardware and software configuration and data processing procedures are described below.

[0494] System Configuration

[0495] User

[0496] Users access the generative AI application and request the generation of a new image. Examples of prompts include "I want you to generate an illustration of a cat" or "I want you to generate a landscape painting of a sunset."

[0497] server

[0498] The server is equipped with hardware and software for receiving user requests and performing the following processes:

[0499] Hardware: Server equipment with a powerful CPU, GPU, and sufficient storage.

[0500] Software: Programming environments including Python and JavaScript, PIL (Pillow) and OpenCV for metadata analysis, database management systems (e.g., MySQL and PostgreSQL) for copyright information management, and APIs for accessing generative AI models (e.g., DALL-E and Stable Diffusion).

[0501] Terminal

[0502] A web browser is installed on the user's device, which displays instructions from the server and accepts user operations. The device supports HTML and JavaScript to display warning messages in a pop-up format.

[0503] Specific examples

[0504] Example 1: Copyright Infringement Warning Process

[0505] When a user requests an "illustration of a famous character" using the generation AI, the server checks the copyright information of the original data and compares it with the copyright information database. If the server detects that the original data contains the copyright of "Character A," it generates a warning message and sends it to the device. The device displays a warning saying, "This content is copyrighted and therefore unavailable," and the user must re-enter a new request.

[0506] Example 2: Normal image generation process

[0507] When a user requests a "sunset landscape painting," the server checks the copyright information of the original data and compares it with a copyright information database. If the original data is found to have no copyright issues, the server activates a generative AI model to generate an image based on the user's request. The server then embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. After the fingerprint has been embedded, the server sends the generated image to the user's device. The device displays the image to the user and makes it available for download.

[0508] This allows users to use generative AI models safely and securely, and generate images with copyright information managed.

[0509] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0510] Step 1:

[0511] The user enters a prompt statement

[0512] The user inputs a prompt through the interface of the generation AI application. For example, they might input "I want a cat illustration generated" and click the send button. Input: Prompt text "I want a cat illustration generated." Output: The prompt text is sent to the server. Specifically, the user inputs a request text into the text box and clicks the send button.

[0513] Step 2:

[0514] The server retrieves the original data

[0515] The server receives the prompt sentence sent by the user and retrieves the related original data from the storage system. This original data is temporarily stored in memory. Input: User's prompt sentence. Output: Related original data. Specifically, the server retrieves the original data from storage (e.g., cloud storage) and stores it in memory.

[0516] Step 3:

[0517] The server checks the copyright information of the original data

[0518] The server analyzes the metadata of the imported original data using PIL (Pillow) or OpenCV and extracts copyright information. Input: Original data. Output: Copyright information. Specifically, the server runs a program and uses a metadata analysis library to obtain copyright information from the original data.

[0519] Step 4:

[0520] The server checks the copyright information against a database

[0521] The server compares the extracted copyright information with a dedicated database to determine whether the original data is copyrighted. Input: Copyright information. Output: Determination result regarding copyright status. Specifically, the server uses an SQL query to check the compatibility of the database.

[0522] Step 5:

[0523] The server generates a warning message and sends it to the device.

[0524] If copyrighted original data is detected, the server generates a warning message and sends it to the user's device. Input: Judgment result on whether copyright is included. Output: Warning message. Specifically, the server creates a warning message using HTML and JavaScript and sends it to the device as an HTTP response.

[0525] Step 6:

[0526] The device displays a warning message

[0527] The user's device displays the warning message sent from the server in a pop-up format. Input: Warning message. Output: Pop-up warning message. Specifically, the browser executes JavaScript and displays the warning on the screen.

[0528] Step 7:

[0529] The user enters a new prompt.

[0530] Upon receiving the warning, the user re-enters a new prompt. Input: New prompt. Output: Send the new prompt to the server. Specifically, the user re-enters the request text in the text box and clicks the send button.

[0531] Step 8:

[0532] If the server has no copyright issues, it starts the image generation process.

[0533] If the server confirms that there are no copyright issues, it begins generating images using a generative AI model (for example, DALL-E or Stable Diffusion). Input: Prompt text. Output: Generated image. Specifically, the server sends a request to the API of the generative AI model to generate an image.

[0534] Step 9:

[0535] The server embeds a digital fingerprint into the generated image.

[0536] The server embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. Input: Generated image. Output: Image with embedded fingerprint. Specifically, the server uses libraries such as OpenCV or PyMuPDF to add a digital watermark to the image.

[0537] Step 10:

[0538] The server provides the generated image to the user's device

[0539] After the fingerprint embedding is complete, the server sends the generated image to the user's device. Input: Image with embedded fingerprint. Output: Image displayed to the user. Specifically, the server sends the image as an HTTP response, and the browser displays it.

[0540] This is the specific processing flow of the system. Through these steps, users can use the generative AI model with confidence and obtain images with properly managed copyright information.

[0541] (Application example 1)

[0542] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0543] Conventional image generation systems using generative AI have insufficient management of copyright information, which means that images generated by users may unknowingly infringe copyrights. Furthermore, digital fingerprints to protect the copyright of generated images are often not assigned. This increases the risk of copyright infringement, making it difficult for users to use image generation services with peace of mind. Furthermore, similar security services are needed when users use various devices, such as smartphones, smart glasses, head-mounted displays, and robots, but previous systems have not been able to provide sufficient security.

[0544] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0545] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information, means for checking against a copyright information database to confirm the presence or absence of copyright, means for generating a warning message for original data that includes copyright, means for sending a warning message to a terminal to warn the user, means for starting an image generation process if the copyright is not an issue, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, and means for operating various means such as import of original data, inspection of copyright information, checking against the copyright information database, generation and transmission of a warning message, image generation process, assignment of a digital fingerprint, and provision of the generated image using an application installed on a smartphone, smart glasses, a head-mounted display, and a robot.

[0546] This allows users to properly manage copyright information when creating images, preventing copyright infringement and ensuring that the copyright of the created images is protected. It also supports a variety of devices, including smartphones, smart glasses, head-mounted displays, and robots, providing consistent security services regardless of the device the user uses.

[0547] "Original data" refers to information such as images and text that serves as the basis for use by the generating AI.

[0548] "Copyright information" refers to legal rights information regarding the ownership and usage rights of the original data.

[0549] A "copyright information database" is a database that holds information on content for which copyrights are registered.

[0550] A "warning message" is a message that notifies the user of a possible copyright infringement.

[0551] A "terminal" is a device operated by a user, and includes a smartphone, smart glasses, a head-mounted display, a robot, etc.

[0552] The "image generation process" is the process of using generative AI to generate a new image based on a user request.

[0553] "Digital fingerprinting" refers to techniques such as digital watermarking for embedding copyright information into generated images.

[0554] A "smartphone" is a mobile phone equipped with internet connectivity and various applications.

[0555] "Smart glasses" are glasses-type information terminals that provide visual information.

[0556] A "head-mounted display" is an information display device that is worn on the head and provides visual information.

[0557] A "robot" is a mechanical device used to perform automated operations or tasks.

[0558] An "application" is a software program designed to perform a specific function or task.

[0559] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system operates through an application installed on information terminals such as smartphones, smart glasses, head-mounted displays, and robots.

[0560] The server receives an image generation request from the user and begins to import the original data. It then performs a copyright information check on the imported original data and compares it with a copyright information database. This comparison confirms whether the original data is copyrighted. If it is confirmed to be copyrighted, the server generates a warning message and sends it to the terminal to notify the user. This warning message is displayed in a pop-up format, stating, "This content cannot be used because it contains copyright information."

[0561] On the other hand, if it is confirmed that there are no copyright issues, the server begins the image generation process. It uses a generative AI model (e.g., a model using TensorFlow or PyTorch) to generate a new image based on the user's request. The generated image is then checked for copyright information again, and a digital fingerprint (e.g., digital watermarking technology) is embedded if necessary. After the digital fingerprint has been embedded, the generated image is sent to the user's device, where it can be viewed and downloaded.

[0562] As an example of how this system can be used, consider the case where a user makes a request from their smartphone to "generate an illustration of a cathedral." The server inspects the original data, checks it against a copyright information database to ensure there are no violations, and then generates an illustration of the cathedral using a generative AI model. A digital fingerprint is embedded in the generated illustration, which is sent to the user's smartphone. The user can then view and download the generated illustration.

[0563] An example prompt is:

[0564] "I want to generate an illustration of a cathedral."

[0565] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0566] Step 1:

[0567] A user sends an image generation request from a smartphone, smart glasses, head-mounted display, or robot. A prompt sentence (e.g., "Please generate an illustration of a cathedral") is sent as input. The server receives this request. The request content is passed to the server as output.

[0568] Step 2:

[0569] The server starts fetching raw data based on the received prompt statement. The prompt statement is used as input. The server retrieves the relevant raw data from a database or storage. The raw data is fetched as output.

[0570] Step 3:

[0571] The server checks the copyright information of the imported original data. The imported original data is used as input. The server compares the original data with the copyright information database to check whether the copyright is included. The output is the check result (whether or not the copyright exists).

[0572] Step 4:

[0573] The server generates a warning message if copyright is included based on the inspection result. The inspection result is used as input. The server generates a warning message saying "This content is copyrighted and therefore unavailable." The warning message is obtained as output.

[0574] Step 5:

[0575] The server sends the generated warning message to the terminal and notifies the user. The warning message is used as input. The terminal displays the received warning message in a popup format. The warning message is displayed to the user as output.

[0576] Step 6:

[0577] The server starts the image generation process if there are no copyright issues. The prompt and inspection results are used as input. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate an image based on the user's request. The generated image is obtained as output.

[0578] Step 7:

[0579] The server embeds a digital fingerprint into the generated image. The generated image is used as input. The server embeds the fingerprint into the image using digital watermarking technology. The output is an image with the embedded digital fingerprint.

[0580] Step 8:

[0581] The server sends the generated image with the embedded digital fingerprint to the terminal, which uses the fingerprinted image as input and displays the received image to the user and makes it available for download, providing the generated image as output, viewable by the user.

[0582] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0583] This invention is a system that combines a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI with an emotion engine that recognizes the user's emotions. This system includes means for importing original data, means for inspecting copyright information, means for comparing with a copyright information database, means for generating and transmitting warning messages, an image generation process, means for assigning digital fingerprints, means for providing generated images, and an emotion engine.

[0584] Detailed system description

[0585] Users can generate new images using generated AI.

[0586] The user accesses the generative AI application and makes a request to generate a new image. For example, they input a request such as "I want you to generate an illustration of a cat."

[0587] Importing original data and checking copyright information

[0588] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0589] Copyright Infringement Warning

[0590] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0591] Image generation when there are no problems

[0592] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0593] Digital fingerprinting

[0594] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0595] Providing generated images

[0596] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0597] Use of emotion engine

[0598] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[0599] The emotion engine also analyzes the user's emotional response to the warning message and provides information to the server if the user is feeling stressed or dissatisfied. The server can then use this information to provide an explanation or alternative solution that the user can understand.

[0600] Specific examples

[0601] Example 1: Copyright Infringement Warning Process

[0602] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The emotion engine also monitors the user's reaction to the warning message, and if the user feels disappointed or dissatisfied, it sends that information to the server. The server can then suggest other materials and resources that the user can use.

[0603] Example 2: Normal image generation process

[0604] When a user requests a "sunset landscape painting," the server checks the database to ensure there are no copyright issues with the original data. The server then starts the image generation process and embeds a digital fingerprint into the generated landscape painting. After the embedding is complete, the server sends the generated landscape painting to the user's device. The emotion engine monitors the user's reaction and checks whether the user is satisfied. This information is fed back to the server and reflected in future image generation processes.

[0605] The above is a detailed description of an embodiment of the present invention. This system allows users to use generative AI with peace of mind and avoids the risk of copyright infringement. In addition, the use of an emotion engine can increase user satisfaction.

[0606] The processing flow will be explained below.

[0607] Step 1:

[0608] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0609] Step 2:

[0610] The terminal sends the user's request to the server.

[0611] Step 3:

[0612] The server receives the request and retrieves the raw data required to generate the image.

[0613] Step 4:

[0614] After the server retrieves the original data, it checks the copyright information of the original data.

[0615] Step 5:

[0616] The server checks the original data against a copyright information database to see if the original data contains copyright.

[0617] Step 6:

[0618] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[0619] Step 7:

[0620] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[0621] Step 8:

[0622] Sends server-generated warning messages to the terminal.

[0623] Step 9:

[0624] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[0625] Step 10:

[0626] The emotion engine monitors the user's reaction to the warning message on the device and collects the user's emotion data.

[0627] Step 11:

[0628] The user enters a new request or takes the appropriate action.

[0629] Step 12:

[0630] The server receives the request again and inspects the original data (resume from step 3).

[0631] Step 13:

[0632] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[0633] Step 14:

[0634] A generation AI built into the server generates a new image based on the request.

[0635] Step 15:

[0636] The emotion engine analyzes the user's emotions while executing the request and sends the information to the server.

[0637] Step 16:

[0638] The server will double-check the copyright information on the generated image.

[0639] Step 17:

[0640] If the server generates an image containing copyright, it embeds a digital fingerprint.

[0641] Step 18:

[0642] The server verifies that the digital fingerprint embedding was completed successfully.

[0643] Step 19:

[0644] The server transmits the generated image to the terminal.

[0645] Step 20:

[0646] The terminal displays the generated image to the user and allows the user to download it.

[0647] Step 21:

[0648] The emotion engine monitors the user's reactions as they view the generated images and collects their emotion data.

[0649] Step 22:

[0650] The collected emotion data is fed back to the server and used to optimize future image generation processes.

[0651] Step 23:

[0652] The user can review the generated images and download or request new ones as needed.

[0653] Example 2

[0654] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0655] Conventional generative AI systems often lacked methods for properly managing copyright information on the original data and effectively preventing violations. Furthermore, they were unable to incorporate the emotions felt by users during the image generation process, which hindered efforts to improve user satisfaction. Furthermore, there was an insufficient method for clearly indicating copyright information on generated images, making copyright protection of images difficult.

[0656] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0657] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the existence of copyright by comparing it with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn a user, means for starting an image generation process if the copyright is not an issue, means for using a generative AI model in the image generation process, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, means for using an emotion engine for recognizing user emotions, and means for analyzing emotion data obtained from the emotion engine to optimize the image generation process. This makes it possible to appropriately manage the copyright of the original data and improve user satisfaction, while avoiding the risk of copyright infringement and effectively indicating copyright information on generated images.

[0658] 1. "Original Data" refers to the initial data used to generate an image, including user-entered text and image files.

[0659] 2. "Copyright Information" refers to information that describes the legally protected rights and details of such rights regarding data and content.

[0660] 3. "Copyright Information Database" refers to a database that stores copyright-related information and makes it searchable and collatable.

[0661] 4. "Warning Message" means an alert message that notifies the user of a possible copyright infringement.

[0662] 5. "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to operate an image generation system.

[0663] 6. “Image generation process” refers to the general procedure for using a generative AI model to create a new image based on a user request.

[0664] 7. "Generative AI model" refers to algorithms or software that use artificial intelligence techniques to generate new images from user input data.

[0665] 8. "Digital fingerprint" refers to identification information applied to a generated image, and refers to a method of clearly indicating copyright information using digital watermarking technology, etc.

[0666] 9. "Emotion engine" refers to technology or software for recognizing and analyzing user emotions.

[0667] 10. "Emotion Data" refers to data regarding a user's emotions obtained by the emotion engine.

[0668] The present invention provides a system for appropriately managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes a means for importing original data, a means for inspecting copyright information, a means for comparing with a copyright information database, a means for generating and transmitting a warning message, an image generation process, a means for assigning a digital fingerprint, a means for providing the generated image, and an emotion engine. The embodiments of each element are described in detail below.

[0669] Importing original data and checking copyright information

[0670] The server receives a request from the user and starts to retrieve the original data. Specifically, the user accesses the generation AI application and inputs a request such as "I want you to generate an illustration of a cat." The request is sent to the server as an HTTP request.

[0671] After the original data is imported into the server, the server checks it for copyright information. To do this, the server uses specialized analysis software to extract metadata and existing copyright information from the original data. The extracted copyright information is then checked against internal or external copyright information databases via API.

[0672] Copyright strike and re-entry request

[0673] If the original data contains copyright, the server generates a warning message and sends it to the terminal. This message states, "This content is copyrighted and cannot be used," and the user must re-enter the request. This warning message is displayed in a pop-up format.

[0674] Image Generation Process

[0675] When a user inputs a request that does not have copyright issues, the server starts the image generation process. The server launches a generative AI model and inputs the user's prompt (e.g., "I want you to generate a landscape painting of a sunset") into the model. Technologies such as Stable Diffusion and DALL-E are used as the generative AI model.

[0676] Digital fingerprinting

[0677] If the generated image is verified as legitimate, the server embeds a digital fingerprint into the image, using digital watermarking technology, which clearly identifies the copyright information for the generated image.

[0678] Providing generated images

[0679] The image with the embedded digital fingerprint is then sent back from the server to the user's device, where the generated image is displayed and made available for download.

[0680] Use of emotion engine

[0681] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[0682] The emotion engine also analyzes the user's emotional response to the warning message and provides information about stress or frustration to the server, which can then provide a more understandable explanation or alternative, such as suggesting the use of other permitted material.

[0683] This invention allows users to use generative AI with peace of mind, avoiding the risk of copyright infringement, and increases user satisfaction through the use of an emotion engine.

[0684] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0685] Step 1:

[0686] Description: A user accesses the generative AI application and enters a request to generate an image.

[0687] Input: The user enters the prompt "I want an illustration of a cat."

[0688] How it works: The user launches a browser or a dedicated app, enters a prompt in the text box, and clicks the "Submit" button.

[0689] Output: The entered prompt text is sent to the server as an HTTP request.

[0690] Step 2:

[0691] Description: The server receives the user request and starts fetching the raw data.

[0692] Input: The prompt text included in the HTTP request received by the server.

[0693] What happens: The server parses the HTTP request and begins the process of retrieving the original data.

[0694] Output: The original data is temporarily saved.

[0695] Step 3:

[0696] Description: The server checks the original data for copyright information and matches it with a copyright information database.

[0697] Input: Temporarily saved original data.

[0698] How it works: The server uses analysis software to extract metadata and copyright information from the raw data, and sends API requests to a copyright information database for matching.

[0699] Output: The result of the copyright check.

[0700] Step 4:

[0701] Description: If the server verifies the copyright information and finds any problems, it generates a warning message and sends it to the user's device.

[0702] Input: If the copyright information check results in "problem".

[0703] Behavior: The server generates a warning message stating "This content is copyrighted and therefore unavailable" and sends it to the device as an HTTP response.

[0704] Output: A warning message is displayed on the terminal.

[0705] Step 5:

[0706] Description: If the server has no copyright issues, it will start the image generation process.

[0707] Input: If the copyright information check result is "OK".

[0708] How it works: The server launches a generative AI model (e.g., Stable Diffusion or DALL-E) and passes the prompt statement as input.

[0709] Output: The generative AI model generates new image data.

[0710] Step 6:

[0711] Description: The server double-checks the generated image for copyright information and embeds a digital fingerprint if copyright is present.

[0712] Input: The newly generated image data.

[0713] How it works: The server uses digital watermarking technology to embed copyright information into the image as a digital fingerprint.

[0714] Output: Image data with embedded digital fingerprint.

[0715] Step 7:

[0716] Description: The server sends the generated image to the user's device.

[0717] Input: Image data with embedded digital fingerprint.

[0718] Operation: The server sends the image data to the user's device as an HTTP response.

[0719] Output: The generated image is displayed on the device, ready for the user to download.

[0720] Step 8:

[0721] Description: The emotion engine monitors the user's reactions and provides this information to the server.

[0722] Input: Emotional data such as user behavior, facial expressions, and tone of voice.

[0723] How it works: The emotion engine analyzes the user's reactions using the camera and microphone, and sends the analysis results back to the server.

[0724] Output: The server receives the emotion data and uses the analysis results to improve the image generation process in the future.

[0725] By following the above steps, the system can safely generate images based on the user's prompt sentence, improving user satisfaction.

[0726] (Application example 2)

[0727] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0728] When generating images using generative AI technology, it is necessary to properly manage the copyright information of the original data to avoid the risk of copyright infringement by users and to increase user satisfaction. It is also important to understand how users feel about their experience during the generation process and provide feedback accordingly.

[0729] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the presence or absence of intellectual property by comparing the original data with a copyright information database, means for generating a warning message for original data that includes intellectual property, means for sending the warning message to the terminal to warn the user, means for starting the image generation process if the intellectual property is not a problem, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, an emotion engine for analyzing the user's emotions, means for receiving feedback from the emotion engine, and means for optimizing the image generation process based on the feedback. This enables accurate management of intellectual property information and optimal image generation according to the user's emotions.

[0730] The "means for initiating the import of raw data" is a function for initiating a process based on data provided by the user.

[0731] The "means for inspecting copyright information of original data" is a function for checking copyright information included in the original data.

[0732] "Means for checking the existence of intellectual property by checking against the copyright information database" is a function for comparing the copyright information database with the original data to check whether intellectual property rights exist.

[0733] The "means for generating a warning message for original data containing intellectual property" is a function for generating a warning message to the user when intellectual property is included in the original data.

[0734] The "means for sending a warning message to the terminal to warn the user" is a function for sending a warning message to the user's terminal and notifying the user.

[0735] The "means for starting the image generation process when there are no intellectual property issues" is a function for starting image generation based on original data that has no copyright issues.

[0736] The "means for embedding a digital fingerprint in the generated image" is a function for embedding a digital fingerprint in the generated image to identify the ownership and origin of the image.

[0737] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal.

[0738] The "emotion engine that analyzes user emotions" is a component that analyzes the user's emotions and provides feedback based on that data.

[0739] The "means for receiving feedback from the emotion engine" is a function for receiving emotion information analyzed by the emotion engine and adjusting the process based on that information.

[0740] The "means for optimizing the image generation process based on feedback" is a function for optimizing the image generation process based on feedback information obtained from the emotion engine, thereby increasing user satisfaction.

[0741] The system of the present invention implements a series of processes, including the import of original data, the search for copyright information, the image generation process, the assignment of a digital fingerprint, and feedback by an emotion engine. Specific embodiments will be described below.

[0742] Program Generation and Processing Description

[0743] This system is a combination of a server, a user terminal, and an emotion engine, and each function works in cooperation with the others.

[0744] Hardware and Software Configuration

[0745] Server: This is the main component that imports original data, checks and collates copyright information, generates images, assigns digital fingerprints, and processes feedback from the emotion engine. The server contains an image processing API (ImageProcessingAPI), an emotion analysis API (EmotionAPI), and a copyright information inspection API (CopyrightCheckAPI).

[0746] User terminal: A device on which a user inputs image generation requests and receives generated images and alert messages. Examples include mobile devices such as smartphones and tablets.

[0747] Emotion Engine: A component that analyzes the user's emotions and provides the feedback to the server. The emotion engine is designed to analyze the user's input data and reactions.

[0748] System operation explanation

[0749] 1. Importing original data: Receive an image generation request from the user device. For example, the user may input a request such as "I want an illustration of a cat to be generated."

[0750] 2. Copyright information inspection and matching: The server searches for the copyright information of the original data and matches it with the copyright information database. For example, if the original data is "Character A", it will compare it with the copyright database to see if the character is copyrighted.

[0751] 3. Generating a warning message: If the server detects that the original data contains copyrighted material, it generates a warning message and sends it to the user's device. For example, if a user requests an illustration of a famous character, the server sends a message stating, "This content is copyrighted and therefore unavailable."

[0752] 4. Image generation process: If there are no copyright issues, the server uses the generation AI to generate a new image based on the user request. For example, if a user requests a "sunset landscape painting," the server generates a landscape painting after confirming that there are no issues with the copyright database.

[0753] 5. Digital Fingerprinting: The server embeds a digital fingerprint into the generated image, using digital watermarking technology to clearly indicate copyright information for the image.

[0754] 6. Providing the generated image: The image with the embedded fingerprint is sent to the user's device, allowing the user to view and download the image.

[0755] 7. Use of Emotion Engine: The emotion engine analyzes the user's emotions regarding requests and warning messages and feeds the data back to the server, which then optimizes the image generation process based on this feedback to improve user satisfaction.

[0756] Specific examples

[0757] Copyright Strike Process

[0758] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains copyright. The server then sends a pop-up message to the user's device stating, "This content is copyrighted and cannot be used."

[0759] Normal image generation process

[0760] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data is free of copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device.

[0761] Prompt Sentence Examples

[0762] "I want to generate a sunset landscape image."

[0763] "I want you to generate an illustration of a cat"

[0764] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0765] Step 1:

[0766] The user inputs an image generation request from the terminal. For example, the user inputs a prompt such as "I want an illustration of a cat." The input prompt is sent to the system. The input data is passed to the server as a user request.

[0767] Step 2:

[0768] The server starts capturing the original data, collects relevant image data based on the prompts from the user, and passes the captured original data to the inspection process, which then uses the captured original data as input data for copyright information inspection.

[0769] Step 3:

[0770] The server checks the copyright information of the original data, analyzes the imported data, and processes it to extract the copyright information. The results of this data processing are compared with a copyright information database.

[0771] Step 4:

[0772] The server checks the existence of intellectual property by checking against the copyright information database. The copyright information extracted from the original data is compared with the database to check whether the rights exist. Based on the results from the database, the existence of intellectual property is output.

[0773] Step 5:

[0774] If intellectual property is included, the server generates a warning message. If intellectual property is included, a message to warn the user is generated and sent to the terminal as a warning. Specifically, the message reads, "This content cannot be used because it contains copyright."

[0775] Step 6:

[0776] A warning message is displayed in a pop-up format on the user's device. The user can correct or re-enter the request. The displayed warning message is notified to the user, and the user's reaction is analyzed by the emotion engine.

[0777] Step 7:

[0778] If the intellectual property is clear, the server starts the image generation process. It runs a generative AI model using the original data that has passed copyright inspection to generate a new image. This generated image is then passed on to the next step in the process.

[0779] Step 8:

[0780] The server embeds a digital fingerprint into the generated image. The server then embeds copyright information into the generated image using digital watermarking technology. This process clearly identifies the copyright information for the image.

[0781] Step 9:

[0782] The server sends the generated image to the user's device. The image data with the embedded fingerprint is transferred to the user's device, where it can be downloaded and displayed by the user. The image sent to the device is then confirmed by the user.

[0783] Step 10:

[0784] The emotion engine analyzes the user's emotions. It monitors the user's reaction to the images sent to the device and feeds that data back to the server. The user's emotional data is analyzed and used for further processing.

[0785] Step 11:

[0786] The server receives feedback from the emotion engine and optimizes the image generation process. Based on the user's emotion data, it adjusts the parameters of the AI ​​model and prompts to optimize the generation process from the next time onwards. This improves user satisfaction.

[0787] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0788] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0789] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0790] [Third embodiment]

[0791] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0792] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0793] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0794] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0795] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0796] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0797] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0798] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0799] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0800] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0801] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0802] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0803] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes various means such as importing the original data, inspecting the copyright information, comparing it with a copyright information database, generating and sending a warning message, the image generation process, assigning a digital fingerprint, and providing the generated image.

[0804] Detailed system description

[0805] Users can generate new images using generated AI.

[0806] The user accesses the generative AI application and makes a request to generate a new image, for example, "I want you to generate an illustration of a cat."

[0807] Importing original data and checking copyright information

[0808] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0809] Copyright Infringement Warning

[0810] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0811] Image generation when there are no problems

[0812] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0813] Digital fingerprinting

[0814] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0815] Providing generated images

[0816] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0817] Specific examples

[0818] Example 1: Copyright Infringement Warning Process

[0819] When a user requests an "illustration of a famous character" using the generation AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The device displays a warning saying, "This content is copyrighted and cannot be used," and the user inputs a new request.

[0820] Example 2: Normal image generation process

[0821] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data has no copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device, which then displays the image to the user. The user then downloads the resulting landscape painting.

[0822] The above is a detailed description of the embodiment of the present invention. This system allows users to use AI generation with peace of mind and avoids the risk of copyright infringement.

[0823] The processing flow will be explained below.

[0824] Step 1:

[0825] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0826] Step 2:

[0827] The terminal sends the user's request to the server.

[0828] Step 3:

[0829] The server receives the request and retrieves the raw data required to generate the image.

[0830] Step 4:

[0831] After the server retrieves the original data, it checks the copyright information of the original data.

[0832] Step 5:

[0833] The server checks the original data against a copyright information database to see if the original data contains copyright.

[0834] Step 6:

[0835] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[0836] Step 7:

[0837] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[0838] Step 8:

[0839] Sends server-generated warning messages to the terminal.

[0840] Step 9:

[0841] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[0842] Step 10:

[0843] The user confirms the warning message and enters a new request.

[0844] Step 11:

[0845] The server receives the request again and inspects the original data (resume from step 3).

[0846] Step 12:

[0847] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[0848] Step 13:

[0849] A generation AI built into the server generates a new image based on the request.

[0850] Step 14:

[0851] The server will double-check the copyright information on the generated image.

[0852] Step 15:

[0853] If the server generates an image containing copyright, it embeds a digital fingerprint.

[0854] Step 16:

[0855] The server verifies that the digital fingerprint embedding was completed successfully.

[0856] Step 17:

[0857] The server transmits the generated image to the terminal.

[0858] Step 18:

[0859] The terminal displays the generated image to the user and allows the user to download it.

[0860] Step 19:

[0861] The user can review the generated images and download or request new ones as needed.

[0862] Example 1

[0863] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0864] In recent years, the use of generative AI models to generate images has been increasing, but there is a need to properly manage copyright information for the original data. If generated images are distributed without verifying whether the original data is copyrighted, the risk of copyright infringement increases. Furthermore, if warnings and countermeasures against copyright infringement are insufficient, users may feel uneasy about using the generated images. The purpose of this invention is to solve these problems and provide a system that reliably manages copyright when generating images using generative AI models.

[0865] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0866] In this invention, the server includes means for a user to input a prompt sentence, means for starting import of original data, means for inspecting copyright information of the original data, means for checking the copyright existence by comparing the original data with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn the user, means for starting an image generation process if there is no copyright issue, means for embedding a digital fingerprint in the generated image, and means for sending the generated image to the terminal. This makes it possible to properly manage copyright information and safely generate images using a generative AI model while avoiding the risk of copyright infringement.

[0867] The "means for the user to input a prompt sentence" is an interface through which the user inputs a text-based request for image generation by the generative AI model.

[0868] "Means to start importing original data" refers to the function by which the generative AI model obtains initial data in response to a user request and imports it into the system.

[0869] The "means for inspecting copyright information of original data" is a function for analyzing and checking the copyright information contained in the imported original data.

[0870] "Means for checking copyright by comparing with copyright information database" is a function for checking the copyright information of the original data against an existing database to confirm whether the original data is protected by copyright.

[0871] The "means for generating a warning message for original data containing copyright" is a function for generating a warning message for original data that is protected by copyright.

[0872] The "means for sending a warning message to a terminal to warn a user" is a function for sending a generated warning message to a user's terminal and notifying the user of the warning.

[0873] "Means for initiating the image generation process if there are no copyright issues" refers to a function that starts the process of generating a new image using a generative AI model if it is confirmed that there are no copyright issues.

[0874] "Means for embedding a digital fingerprint into the generated image" refers to a function that embeds a digital fingerprint (e.g., a digital watermark) into the generated image to clearly indicate the copyright information of the image.

[0875] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal so that the user can view, save or use the image.

[0876] This invention is a system that properly manages copyright information of original data when a user generates an image using a generative AI model, thereby avoiding the risk of copyright infringement. The main components of this system are a server, a terminal, and a user. The specific hardware and software configuration and data processing procedures are described below.

[0877] System Configuration

[0878] User

[0879] Users access the generative AI application and request the generation of a new image. Examples of prompts include "I want you to generate an illustration of a cat" or "I want you to generate a landscape painting of a sunset."

[0880] server

[0881] The server is equipped with hardware and software for receiving user requests and performing the following processes:

[0882] Hardware: Server equipment with a powerful CPU, GPU, and sufficient storage.

[0883] Software: Programming environments including Python and JavaScript, PIL (Pillow) and OpenCV for metadata analysis, database management systems (e.g., MySQL and PostgreSQL) for copyright information management, and APIs for accessing generative AI models (e.g., DALL-E and Stable Diffusion).

[0884] Terminal

[0885] A web browser is installed on the user's device, which displays instructions from the server and accepts user operations. The device supports HTML and JavaScript to display warning messages in a pop-up format.

[0886] Specific examples

[0887] Example 1: Copyright Infringement Warning Process

[0888] When a user requests an "illustration of a famous character" using the generation AI, the server checks the copyright information of the original data and compares it with the copyright information database. If the server detects that the original data contains the copyright of "Character A," it generates a warning message and sends it to the device. The device displays a warning saying, "This content is copyrighted and therefore unavailable," and the user must re-enter a new request.

[0889] Example 2: Normal image generation process

[0890] When a user requests a "sunset landscape painting," the server checks the copyright information of the original data and compares it with a copyright information database. If the original data is found to have no copyright issues, the server activates a generative AI model to generate an image based on the user's request. The server then embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. After the fingerprint has been embedded, the server sends the generated image to the user's device. The device displays the image to the user and makes it available for download.

[0891] This allows users to use generative AI models safely and securely, and generate images with copyright information managed.

[0892] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0893] Step 1:

[0894] The user enters a prompt statement

[0895] The user inputs a prompt through the interface of the generation AI application. For example, they might input "I want a cat illustration generated" and click the send button. Input: Prompt text "I want a cat illustration generated." Output: The prompt text is sent to the server. Specifically, the user inputs a request text into the text box and clicks the send button.

[0896] Step 2:

[0897] The server retrieves the original data

[0898] The server receives the prompt sentence sent by the user and retrieves the related original data from the storage system. This original data is temporarily stored in memory. Input: User's prompt sentence. Output: Related original data. Specifically, the server retrieves the original data from storage (e.g., cloud storage) and stores it in memory.

[0899] Step 3:

[0900] The server checks the copyright information of the original data

[0901] The server analyzes the metadata of the imported original data using PIL (Pillow) or OpenCV and extracts copyright information. Input: Original data. Output: Copyright information. Specifically, the server runs a program and uses a metadata analysis library to obtain copyright information from the original data.

[0902] Step 4:

[0903] The server checks the copyright information against a database

[0904] The server compares the extracted copyright information with a dedicated database to determine whether the original data is copyrighted. Input: Copyright information. Output: Determination result regarding copyright status. Specifically, the server uses an SQL query to check the compatibility of the database.

[0905] Step 5:

[0906] The server generates a warning message and sends it to the device.

[0907] If copyrighted original data is detected, the server generates a warning message and sends it to the user's device. Input: Judgment result on whether copyright is included. Output: Warning message. Specifically, the server creates a warning message using HTML and JavaScript and sends it to the device as an HTTP response.

[0908] Step 6:

[0909] The device displays a warning message

[0910] The user's device displays the warning message sent from the server in a pop-up format. Input: Warning message. Output: Pop-up warning message. Specifically, the browser executes JavaScript and displays the warning on the screen.

[0911] Step 7:

[0912] The user enters a new prompt.

[0913] Upon receiving the warning, the user re-enters a new prompt. Input: New prompt. Output: Send the new prompt to the server. Specifically, the user re-enters the request text in the text box and clicks the send button.

[0914] Step 8:

[0915] If the server has no copyright issues, it starts the image generation process.

[0916] If the server confirms that there are no copyright issues, it begins generating images using a generative AI model (for example, DALL-E or Stable Diffusion). Input: Prompt text. Output: Generated image. Specifically, the server sends a request to the API of the generative AI model to generate an image.

[0917] Step 9:

[0918] The server embeds a digital fingerprint into the generated image.

[0919] The server embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. Input: Generated image. Output: Image with embedded fingerprint. Specifically, the server uses libraries such as OpenCV or PyMuPDF to add a digital watermark to the image.

[0920] Step 10:

[0921] The server provides the generated image to the user's device

[0922] After the fingerprint embedding is complete, the server sends the generated image to the user's device. Input: Image with embedded fingerprint. Output: Image displayed to the user. Specifically, the server sends the image as an HTTP response, and the browser displays it.

[0923] This is the specific processing flow of the system. Through these steps, users can use the generative AI model with confidence and obtain images with properly managed copyright information.

[0924] (Application example 1)

[0925] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0926] Conventional image generation systems using generative AI have insufficient management of copyright information, which means that images generated by users may unknowingly infringe copyrights. Furthermore, digital fingerprints to protect the copyright of generated images are often not assigned. This increases the risk of copyright infringement, making it difficult for users to use image generation services with peace of mind. Furthermore, similar security services are needed when users use various devices, such as smartphones, smart glasses, head-mounted displays, and robots, but previous systems have not been able to provide sufficient security.

[0927] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0928] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information, means for checking against a copyright information database to confirm the presence or absence of copyright, means for generating a warning message for original data that includes copyright, means for sending a warning message to a terminal to warn the user, means for starting an image generation process if the copyright is not an issue, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, and means for operating various means such as import of original data, inspection of copyright information, checking against the copyright information database, generation and transmission of a warning message, image generation process, assignment of a digital fingerprint, and provision of the generated image using an application installed on a smartphone, smart glasses, a head-mounted display, and a robot.

[0929] This allows users to properly manage copyright information when creating images, preventing copyright infringement and ensuring that the copyright of the created images is protected. It also supports a variety of devices, including smartphones, smart glasses, head-mounted displays, and robots, providing consistent security services regardless of the device the user uses.

[0930] "Original data" refers to information such as images and text that serves as the basis for use by the generating AI.

[0931] "Copyright information" refers to legal rights information regarding the ownership and usage rights of the original data.

[0932] A "copyright information database" is a database that holds information on content for which copyrights are registered.

[0933] A "warning message" is a message that notifies the user of a possible copyright infringement.

[0934] A "terminal" is a device operated by a user, and includes a smartphone, smart glasses, a head-mounted display, a robot, etc.

[0935] The "image generation process" is the process of using generative AI to generate a new image based on a user request.

[0936] "Digital fingerprinting" refers to techniques such as digital watermarking for embedding copyright information into generated images.

[0937] A "smartphone" is a mobile phone equipped with internet connectivity and various applications.

[0938] "Smart glasses" are glasses-type information terminals that provide visual information.

[0939] A "head-mounted display" is an information display device that is worn on the head and provides visual information.

[0940] A "robot" is a mechanical device used to perform automated operations or tasks.

[0941] An "application" is a software program designed to perform a specific function or task.

[0942] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system operates through an application installed on information terminals such as smartphones, smart glasses, head-mounted displays, and robots.

[0943] The server receives an image generation request from the user and begins to import the original data. It then performs a copyright information check on the imported original data and compares it with a copyright information database. This comparison confirms whether the original data is copyrighted. If it is confirmed to be copyrighted, the server generates a warning message and sends it to the terminal to notify the user. This warning message is displayed in a pop-up format, stating, "This content cannot be used because it contains copyright information."

[0944] On the other hand, if it is confirmed that there are no copyright issues, the server begins the image generation process. It uses a generative AI model (e.g., a model using TensorFlow or PyTorch) to generate a new image based on the user's request. The generated image is then checked for copyright information again, and a digital fingerprint (e.g., digital watermarking technology) is embedded if necessary. After the digital fingerprint has been embedded, the generated image is sent to the user's device, where it can be viewed and downloaded.

[0945] As an example of how this system can be used, consider the case where a user makes a request from their smartphone to "generate an illustration of a cathedral." The server inspects the original data, checks it against a copyright information database to ensure there are no violations, and then generates an illustration of the cathedral using a generative AI model. A digital fingerprint is embedded in the generated illustration, which is sent to the user's smartphone. The user can then view and download the generated illustration.

[0946] An example prompt is:

[0947] "I want to generate an illustration of a cathedral."

[0948] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0949] Step 1:

[0950] A user sends an image generation request from a smartphone, smart glasses, head-mounted display, or robot. A prompt sentence (e.g., "Please generate an illustration of a cathedral") is sent as input. The server receives this request. The request content is passed to the server as output.

[0951] Step 2:

[0952] The server starts fetching raw data based on the received prompt statement. The prompt statement is used as input. The server retrieves the relevant raw data from a database or storage. The raw data is fetched as output.

[0953] Step 3:

[0954] The server checks the copyright information of the imported original data. The imported original data is used as input. The server compares the original data with the copyright information database to check whether the copyright is included. The output is the check result (whether or not the copyright exists).

[0955] Step 4:

[0956] The server generates a warning message if copyright is included based on the inspection result. The inspection result is used as input. The server generates a warning message saying "This content is copyrighted and therefore unavailable." The warning message is obtained as output.

[0957] Step 5:

[0958] The server sends the generated warning message to the terminal and notifies the user. The warning message is used as input. The terminal displays the received warning message in a popup format. The warning message is displayed to the user as output.

[0959] Step 6:

[0960] The server starts the image generation process if there are no copyright issues. The prompt and inspection results are used as input. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate an image based on the user's request. The generated image is obtained as output.

[0961] Step 7:

[0962] The server embeds a digital fingerprint into the generated image. The generated image is used as input. The server embeds the fingerprint into the image using digital watermarking technology. The output is an image with the embedded digital fingerprint.

[0963] Step 8:

[0964] The server sends the generated image with the embedded digital fingerprint to the terminal, which uses the fingerprinted image as input and displays the received image to the user and makes it available for download, providing the generated image as output, viewable by the user.

[0965] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0966] This invention is a system that combines a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI with an emotion engine that recognizes the user's emotions. This system includes means for importing original data, means for inspecting copyright information, means for comparing with a copyright information database, means for generating and transmitting warning messages, an image generation process, means for assigning digital fingerprints, means for providing generated images, and an emotion engine.

[0967] Detailed system description

[0968] Users can generate new images using generated AI.

[0969] The user accesses the generative AI application and makes a request to generate a new image. For example, they input a request such as "I want you to generate an illustration of a cat."

[0970] Importing original data and checking copyright information

[0971] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[0972] Copyright Infringement Warning

[0973] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[0974] Image generation when there are no problems

[0975] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[0976] Digital fingerprinting

[0977] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[0978] Providing generated images

[0979] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[0980] Use of emotion engine

[0981] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[0982] The emotion engine also analyzes the user's emotional response to the warning message and provides information to the server if the user is feeling stressed or dissatisfied. The server can then use this information to provide an explanation or alternative solution that the user can understand.

[0983] Specific examples

[0984] Example 1: Copyright Infringement Warning Process

[0985] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The emotion engine also monitors the user's reaction to the warning message, and if the user feels disappointed or dissatisfied, it sends that information to the server. The server can then suggest other materials and resources that the user can use.

[0986] Example 2: Normal image generation process

[0987] When a user requests a "sunset landscape painting," the server checks the database to ensure there are no copyright issues with the original data. The server then starts the image generation process and embeds a digital fingerprint into the generated landscape painting. After the embedding is complete, the server sends the generated landscape painting to the user's device. The emotion engine monitors the user's reaction and checks whether the user is satisfied. This information is fed back to the server and reflected in future image generation processes.

[0988] The above is a detailed description of an embodiment of the present invention. This system allows users to use generative AI with peace of mind and avoids the risk of copyright infringement. In addition, the use of an emotion engine can increase user satisfaction.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[0992] Step 2:

[0993] The terminal sends the user's request to the server.

[0994] Step 3:

[0995] The server receives the request and retrieves the raw data required to generate the image.

[0996] Step 4:

[0997] After the server retrieves the original data, it checks the copyright information of the original data.

[0998] Step 5:

[0999] The server checks the original data against a copyright information database to see if the original data contains copyright.

[1000] Step 6:

[1001] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[1002] Step 7:

[1003] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[1004] Step 8:

[1005] Sends server-generated warning messages to the terminal.

[1006] Step 9:

[1007] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[1008] Step 10:

[1009] The emotion engine monitors the user's reaction to the warning message on the device and collects the user's emotion data.

[1010] Step 11:

[1011] The user enters a new request or takes the appropriate action.

[1012] Step 12:

[1013] The server receives the request again and inspects the original data (resume from step 3).

[1014] Step 13:

[1015] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[1016] Step 14:

[1017] A generation AI built into the server generates a new image based on the request.

[1018] Step 15:

[1019] The emotion engine analyzes the user's emotions while executing the request and sends the information to the server.

[1020] Step 16:

[1021] The server will double-check the copyright information on the generated image.

[1022] Step 17:

[1023] If the server generates an image containing copyright, it embeds a digital fingerprint.

[1024] Step 18:

[1025] The server verifies that the digital fingerprint embedding was completed successfully.

[1026] Step 19:

[1027] The server transmits the generated image to the terminal.

[1028] Step 20:

[1029] The terminal displays the generated image to the user and allows the user to download it.

[1030] Step 21:

[1031] The emotion engine monitors the user's reactions as they view the generated images and collects their emotion data.

[1032] Step 22:

[1033] The collected emotion data is fed back to the server and used to optimize future image generation processes.

[1034] Step 23:

[1035] The user can review the generated images and download or request new ones as needed.

[1036] Example 2

[1037] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1038] Conventional generative AI systems often lacked methods for properly managing copyright information on the original data and effectively preventing violations. Furthermore, they were unable to incorporate the emotions felt by users during the image generation process, which hindered efforts to improve user satisfaction. Furthermore, there was an insufficient method for clearly indicating copyright information on generated images, making copyright protection of images difficult.

[1039] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1040] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the existence of copyright by comparing it with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn a user, means for starting an image generation process if the copyright is not an issue, means for using a generative AI model in the image generation process, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, means for using an emotion engine for recognizing user emotions, and means for analyzing emotion data obtained from the emotion engine to optimize the image generation process. This makes it possible to appropriately manage the copyright of the original data and improve user satisfaction, while avoiding the risk of copyright infringement and effectively indicating copyright information on generated images.

[1041] 1. "Original Data" refers to the initial data used to generate an image, including user-entered text and image files.

[1042] 2. "Copyright Information" refers to information that describes the legally protected rights and details of such rights regarding data and content.

[1043] 3. "Copyright Information Database" refers to a database that stores copyright-related information and makes it searchable and collatable.

[1044] 4. "Warning Message" means an alert message that notifies the user of a possible copyright infringement.

[1045] 5. "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to operate an image generation system.

[1046] 6. “Image generation process” refers to the general procedure for using a generative AI model to create a new image based on a user request.

[1047] 7. "Generative AI model" refers to algorithms or software that use artificial intelligence techniques to generate new images from user input data.

[1048] 8. "Digital fingerprint" refers to identification information applied to a generated image, and refers to a method of clearly indicating copyright information using digital watermarking technology, etc.

[1049] 9. "Emotion engine" refers to technology or software for recognizing and analyzing user emotions.

[1050] 10. "Emotion Data" refers to data regarding a user's emotions obtained by the emotion engine.

[1051] The present invention provides a system for appropriately managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes a means for importing original data, a means for inspecting copyright information, a means for comparing with a copyright information database, a means for generating and transmitting a warning message, an image generation process, a means for assigning a digital fingerprint, a means for providing the generated image, and an emotion engine. The embodiments of each element are described in detail below.

[1052] Importing original data and checking copyright information

[1053] The server receives a request from the user and starts to retrieve the original data. Specifically, the user accesses the generation AI application and inputs a request such as "I want you to generate an illustration of a cat." The request is sent to the server as an HTTP request.

[1054] After the original data is imported into the server, the server checks it for copyright information. To do this, the server uses specialized analysis software to extract metadata and existing copyright information from the original data. The extracted copyright information is then checked against internal or external copyright information databases via API.

[1055] Copyright strike and re-entry request

[1056] If the original data contains copyright, the server generates a warning message and sends it to the terminal. This message states, "This content is copyrighted and cannot be used," and the user must re-enter the request. This warning message is displayed in a pop-up format.

[1057] Image Generation Process

[1058] When a user inputs a request that does not have copyright issues, the server starts the image generation process. The server launches a generative AI model and inputs the user's prompt (e.g., "I want you to generate a landscape painting of a sunset") into the model. Technologies such as Stable Diffusion and DALL-E are used as the generative AI model.

[1059] Digital fingerprinting

[1060] If the generated image is verified as legitimate, the server embeds a digital fingerprint into the image, using digital watermarking technology, which clearly identifies the copyright information for the generated image.

[1061] Providing generated images

[1062] The image with the embedded digital fingerprint is then sent back from the server to the user's device, where the generated image is displayed and made available for download.

[1063] Use of emotion engine

[1064] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[1065] The emotion engine also analyzes the user's emotional response to the warning message and provides information about stress or frustration to the server, which can then provide a more understandable explanation or alternative, such as suggesting the use of other permitted material.

[1066] This invention allows users to use generative AI with peace of mind, avoiding the risk of copyright infringement, and increases user satisfaction through the use of an emotion engine.

[1067] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1068] Step 1:

[1069] Description: A user accesses the generative AI application and enters a request to generate an image.

[1070] Input: The user enters the prompt "I want an illustration of a cat."

[1071] How it works: The user launches a browser or a dedicated app, enters a prompt in the text box, and clicks the "Submit" button.

[1072] Output: The entered prompt text is sent to the server as an HTTP request.

[1073] Step 2:

[1074] Description: The server receives the user request and starts fetching the raw data.

[1075] Input: The prompt text included in the HTTP request received by the server.

[1076] What happens: The server parses the HTTP request and begins the process of retrieving the original data.

[1077] Output: The original data is temporarily saved.

[1078] Step 3:

[1079] Description: The server checks the original data for copyright information and matches it with a copyright information database.

[1080] Input: Temporarily saved original data.

[1081] How it works: The server uses analysis software to extract metadata and copyright information from the raw data, and sends API requests to a copyright information database for matching.

[1082] Output: The result of the copyright check.

[1083] Step 4:

[1084] Description: If the server verifies the copyright information and finds any problems, it generates a warning message and sends it to the user's device.

[1085] Input: If the copyright information check results in "problem".

[1086] Behavior: The server generates a warning message stating "This content is copyrighted and therefore unavailable" and sends it to the device as an HTTP response.

[1087] Output: A warning message is displayed on the terminal.

[1088] Step 5:

[1089] Description: If the server has no copyright issues, it will start the image generation process.

[1090] Input: If the copyright information check result is "OK".

[1091] How it works: The server launches a generative AI model (e.g., Stable Diffusion or DALL-E) and passes the prompt statement as input.

[1092] Output: The generative AI model generates new image data.

[1093] Step 6:

[1094] Description: The server double-checks the generated image for copyright information and embeds a digital fingerprint if copyright is present.

[1095] Input: The newly generated image data.

[1096] How it works: The server uses digital watermarking technology to embed copyright information into the image as a digital fingerprint.

[1097] Output: Image data with embedded digital fingerprint.

[1098] Step 7:

[1099] Description: The server sends the generated image to the user's device.

[1100] Input: Image data with embedded digital fingerprint.

[1101] Operation: The server sends the image data to the user's device as an HTTP response.

[1102] Output: The generated image is displayed on the device, ready for the user to download.

[1103] Step 8:

[1104] Description: The emotion engine monitors the user's reactions and provides this information to the server.

[1105] Input: Emotional data such as user behavior, facial expressions, and tone of voice.

[1106] How it works: The emotion engine analyzes the user's reactions using the camera and microphone, and sends the analysis results back to the server.

[1107] Output: The server receives the emotion data and uses the analysis results to improve the image generation process in the future.

[1108] By following the above steps, the system can safely generate images based on the user's prompt sentence, improving user satisfaction.

[1109] (Application example 2)

[1110] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1111] When generating images using generative AI technology, it is necessary to properly manage the copyright information of the original data to avoid the risk of copyright infringement by users and to increase user satisfaction. It is also important to understand how users feel about their experience during the generation process and provide feedback accordingly.

[1112] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the presence or absence of intellectual property by comparing the original data with a copyright information database, means for generating a warning message for original data that includes intellectual property, means for sending the warning message to the terminal to warn the user, means for starting the image generation process if the intellectual property is not a problem, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, an emotion engine for analyzing the user's emotions, means for receiving feedback from the emotion engine, and means for optimizing the image generation process based on the feedback. This enables accurate management of intellectual property information and optimal image generation according to the user's emotions.

[1113] The "means for initiating the import of raw data" is a function for initiating a process based on data provided by the user.

[1114] The "means for inspecting copyright information of original data" is a function for checking copyright information included in the original data.

[1115] "Means for checking the existence of intellectual property by checking against the copyright information database" is a function for comparing the copyright information database with the original data to check whether intellectual property rights exist.

[1116] The "means for generating a warning message for original data containing intellectual property" is a function for generating a warning message to the user when intellectual property is included in the original data.

[1117] The "means for sending a warning message to the terminal to warn the user" is a function for sending a warning message to the user's terminal and notifying the user.

[1118] The "means for starting the image generation process when there are no intellectual property issues" is a function for starting image generation based on original data that has no copyright issues.

[1119] The "means for embedding a digital fingerprint in the generated image" is a function for embedding a digital fingerprint in the generated image to identify the ownership and origin of the image.

[1120] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal.

[1121] The "emotion engine that analyzes user emotions" is a component that analyzes the user's emotions and provides feedback based on that data.

[1122] The "means for receiving feedback from the emotion engine" is a function for receiving emotion information analyzed by the emotion engine and adjusting the process based on that information.

[1123] The "means for optimizing the image generation process based on feedback" is a function for optimizing the image generation process based on feedback information obtained from the emotion engine, thereby increasing user satisfaction.

[1124] The system of the present invention implements a series of processes, including the import of original data, the search for copyright information, the image generation process, the assignment of a digital fingerprint, and feedback by an emotion engine. Specific embodiments will be described below.

[1125] Program Generation and Processing Description

[1126] This system is a combination of a server, a user terminal, and an emotion engine, and each function works in cooperation with the others.

[1127] Hardware and Software Configuration

[1128] Server: This is the main component that imports original data, checks and collates copyright information, generates images, assigns digital fingerprints, and processes feedback from the emotion engine. The server contains an image processing API (ImageProcessingAPI), an emotion analysis API (EmotionAPI), and a copyright information inspection API (CopyrightCheckAPI).

[1129] User terminal: A device on which a user inputs image generation requests and receives generated images and alert messages. Examples include mobile devices such as smartphones and tablets.

[1130] Emotion Engine: A component that analyzes the user's emotions and provides the feedback to the server. The emotion engine is designed to analyze the user's input data and reactions.

[1131] System operation explanation

[1132] 1. Importing original data: Receive an image generation request from the user device. For example, the user may input a request such as "I want an illustration of a cat to be generated."

[1133] 2. Copyright information inspection and matching: The server searches for the copyright information of the original data and matches it with the copyright information database. For example, if the original data is "Character A", it will compare it with the copyright database to see if the character is copyrighted.

[1134] 3. Generating a warning message: If the server detects that the original data contains copyrighted material, it generates a warning message and sends it to the user's device. For example, if a user requests an illustration of a famous character, the server sends a message stating, "This content is copyrighted and therefore unavailable."

[1135] 4. Image generation process: If there are no copyright issues, the server uses the generation AI to generate a new image based on the user request. For example, if a user requests a "sunset landscape painting," the server generates a landscape painting after confirming that there are no issues with the copyright database.

[1136] 5. Digital Fingerprinting: The server embeds a digital fingerprint into the generated image, using digital watermarking technology to clearly indicate copyright information for the image.

[1137] 6. Providing the generated image: The image with the embedded fingerprint is sent to the user's device, allowing the user to view and download the image.

[1138] 7. Use of Emotion Engine: The emotion engine analyzes the user's emotions regarding requests and warning messages and feeds the data back to the server, which then optimizes the image generation process based on this feedback to improve user satisfaction.

[1139] Specific examples

[1140] Copyright Strike Process

[1141] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains copyright. The server then sends a pop-up message to the user's device stating, "This content is copyrighted and cannot be used."

[1142] Normal image generation process

[1143] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data is free of copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device.

[1144] Prompt Sentence Examples

[1145] "I want to generate a sunset landscape image."

[1146] "I want you to generate an illustration of a cat"

[1147] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1148] Step 1:

[1149] The user inputs an image generation request from the terminal. For example, the user inputs a prompt such as "I want an illustration of a cat." The input prompt is sent to the system. The input data is passed to the server as a user request.

[1150] Step 2:

[1151] The server starts capturing the original data, collects relevant image data based on the prompts from the user, and passes the captured original data to the inspection process, which then uses the captured original data as input data for copyright information inspection.

[1152] Step 3:

[1153] The server checks the copyright information of the original data, analyzes the imported data, and processes it to extract the copyright information. The results of this data processing are compared with a copyright information database.

[1154] Step 4:

[1155] The server checks the existence of intellectual property by checking against the copyright information database. The copyright information extracted from the original data is compared with the database to check whether the rights exist. Based on the results from the database, the existence of intellectual property is output.

[1156] Step 5:

[1157] If intellectual property is included, the server generates a warning message. If intellectual property is included, a message to warn the user is generated and sent to the terminal as a warning. Specifically, the message reads, "This content cannot be used because it contains copyright."

[1158] Step 6:

[1159] A warning message is displayed in a pop-up format on the user's device. The user can correct or re-enter the request. The displayed warning message is notified to the user, and the user's reaction is analyzed by the emotion engine.

[1160] Step 7:

[1161] If the intellectual property is clear, the server starts the image generation process. It runs a generative AI model using the original data that has passed copyright inspection to generate a new image. This generated image is then passed on to the next step in the process.

[1162] Step 8:

[1163] The server embeds a digital fingerprint into the generated image. The server then embeds copyright information into the generated image using digital watermarking technology. This process clearly identifies the copyright information for the image.

[1164] Step 9:

[1165] The server sends the generated image to the user's device. The image data with the embedded fingerprint is transferred to the user's device, where it can be downloaded and displayed by the user. The image sent to the device is then confirmed by the user.

[1166] Step 10:

[1167] The emotion engine analyzes the user's emotions. It monitors the user's reaction to the images sent to the device and feeds that data back to the server. The user's emotional data is analyzed and used for further processing.

[1168] Step 11:

[1169] The server receives feedback from the emotion engine and optimizes the image generation process. Based on the user's emotion data, it adjusts the parameters of the AI ​​model and prompts to optimize the generation process from the next time onwards. This improves user satisfaction.

[1170] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1171] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1172] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1173] [Fourth embodiment]

[1174] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1175] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1176] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1177] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1178] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1179] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1180] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1181] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1182] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1183] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1184] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1185] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1186] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1187] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes various means such as importing the original data, inspecting the copyright information, comparing it with a copyright information database, generating and sending a warning message, the image generation process, assigning a digital fingerprint, and providing the generated image.

[1188] Detailed system description

[1189] Users can generate new images using generated AI.

[1190] The user accesses the generative AI application and makes a request to generate a new image, for example, "I want you to generate an illustration of a cat."

[1191] Importing original data and checking copyright information

[1192] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[1193] Copyright Infringement Warning

[1194] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[1195] Image generation when there are no problems

[1196] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[1197] Digital fingerprinting

[1198] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[1199] Providing generated images

[1200] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[1201] Specific examples

[1202] Example 1: Copyright Infringement Warning Process

[1203] When a user requests an "illustration of a famous character" using the generation AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The device displays a warning saying, "This content is copyrighted and cannot be used," and the user inputs a new request.

[1204] Example 2: Normal image generation process

[1205] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data has no copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device, which then displays the image to the user. The user then downloads the resulting landscape painting.

[1206] The above is a detailed description of the embodiment of the present invention. This system allows users to use AI generation with peace of mind and avoids the risk of copyright infringement.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[1210] Step 2:

[1211] The terminal sends the user's request to the server.

[1212] Step 3:

[1213] The server receives the request and retrieves the raw data required to generate the image.

[1214] Step 4:

[1215] After the server retrieves the original data, it checks the copyright information of the original data.

[1216] Step 5:

[1217] The server checks the original data against a copyright information database to see if the original data contains copyright.

[1218] Step 6:

[1219] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[1220] Step 7:

[1221] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[1222] Step 8:

[1223] Sends server-generated warning messages to the terminal.

[1224] Step 9:

[1225] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[1226] Step 10:

[1227] The user confirms the warning message and enters a new request.

[1228] Step 11:

[1229] The server receives the request again and inspects the original data (resume from step 3).

[1230] Step 12:

[1231] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[1232] Step 13:

[1233] A generation AI built into the server generates a new image based on the request.

[1234] Step 14:

[1235] The server will double-check the copyright information on the generated image.

[1236] Step 15:

[1237] If the server generates an image containing copyright, it embeds a digital fingerprint.

[1238] Step 16:

[1239] The server verifies that the digital fingerprint embedding was completed successfully.

[1240] Step 17:

[1241] The server transmits the generated image to the terminal.

[1242] Step 18:

[1243] The terminal displays the generated image to the user and allows the user to download it.

[1244] Step 19:

[1245] The user can review the generated images and download or request new ones as needed.

[1246] Example 1

[1247] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1248] In recent years, the use of generative AI models to generate images has been increasing, but there is a need to properly manage copyright information for the original data. If generated images are distributed without verifying whether the original data is copyrighted, the risk of copyright infringement increases. Furthermore, if warnings and countermeasures against copyright infringement are insufficient, users may feel uneasy about using the generated images. The purpose of this invention is to solve these problems and provide a system that reliably manages copyright when generating images using generative AI models.

[1249] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1250] In this invention, the server includes means for a user to input a prompt sentence, means for starting import of original data, means for inspecting copyright information of the original data, means for checking the copyright existence by comparing the original data with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn the user, means for starting an image generation process if there is no copyright issue, means for embedding a digital fingerprint in the generated image, and means for sending the generated image to the terminal. This makes it possible to properly manage copyright information and safely generate images using a generative AI model while avoiding the risk of copyright infringement.

[1251] The "means for the user to input a prompt sentence" is an interface through which the user inputs a text-based request for image generation by the generative AI model.

[1252] "Means to start importing original data" refers to the function by which the generative AI model obtains initial data in response to a user request and imports it into the system.

[1253] The "means for inspecting copyright information of original data" is a function for analyzing and checking the copyright information contained in the imported original data.

[1254] "Means for checking copyright by comparing with copyright information database" is a function for checking the copyright information of the original data against an existing database to confirm whether the original data is protected by copyright.

[1255] The "means for generating a warning message for original data containing copyright" is a function for generating a warning message for original data that is protected by copyright.

[1256] The "means for sending a warning message to a terminal to warn a user" is a function for sending a generated warning message to a user's terminal and notifying the user of the warning.

[1257] "Means for initiating the image generation process if there are no copyright issues" refers to a function that starts the process of generating a new image using a generative AI model if it is confirmed that there are no copyright issues.

[1258] "Means for embedding a digital fingerprint into the generated image" refers to a function that embeds a digital fingerprint (e.g., a digital watermark) into the generated image to clearly indicate the copyright information of the image.

[1259] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal so that the user can view, save or use the image.

[1260] This invention is a system that properly manages copyright information of original data when a user generates an image using a generative AI model, thereby avoiding the risk of copyright infringement. The main components of this system are a server, a terminal, and a user. The specific hardware and software configuration and data processing procedures are described below.

[1261] System Configuration

[1262] User

[1263] Users access the generative AI application and request the generation of a new image. Examples of prompts include "I want you to generate an illustration of a cat" or "I want you to generate a landscape painting of a sunset."

[1264] server

[1265] The server is equipped with hardware and software for receiving user requests and performing the following processes:

[1266] Hardware: Server equipment with a powerful CPU, GPU, and sufficient storage.

[1267] Software: Programming environments including Python and JavaScript, PIL (Pillow) and OpenCV for metadata analysis, database management systems (e.g., MySQL and PostgreSQL) for copyright information management, and APIs for accessing generative AI models (e.g., DALL-E and Stable Diffusion).

[1268] Terminal

[1269] A web browser is installed on the user's device, which displays instructions from the server and accepts user operations. The device supports HTML and JavaScript to display warning messages in a pop-up format.

[1270] Specific examples

[1271] Example 1: Copyright Infringement Warning Process

[1272] When a user requests an "illustration of a famous character" using the generation AI, the server checks the copyright information of the original data and compares it with the copyright information database. If the server detects that the original data contains the copyright of "Character A," it generates a warning message and sends it to the device. The device displays a warning saying, "This content is copyrighted and therefore unavailable," and the user must re-enter a new request.

[1273] Example 2: Normal image generation process

[1274] When a user requests a "sunset landscape painting," the server checks the copyright information of the original data and compares it with a copyright information database. If the original data is found to have no copyright issues, the server activates a generative AI model to generate an image based on the user's request. The server then embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. After the fingerprint has been embedded, the server sends the generated image to the user's device. The device displays the image to the user and makes it available for download.

[1275] This allows users to use generative AI models safely and securely, and generate images with copyright information managed.

[1276] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1277] Step 1:

[1278] The user enters a prompt statement

[1279] The user inputs a prompt through the interface of the generation AI application. For example, they might input "I want a cat illustration generated" and click the send button. Input: Prompt text "I want a cat illustration generated." Output: The prompt text is sent to the server. Specifically, the user inputs a request text into the text box and clicks the send button.

[1280] Step 2:

[1281] The server retrieves the original data

[1282] The server receives the prompt sentence sent by the user and retrieves the related original data from the storage system. This original data is temporarily stored in memory. Input: User's prompt sentence. Output: Related original data. Specifically, the server retrieves the original data from storage (e.g., cloud storage) and stores it in memory.

[1283] Step 3:

[1284] The server checks the copyright information of the original data

[1285] The server analyzes the metadata of the imported original data using PIL (Pillow) or OpenCV and extracts copyright information. Input: Original data. Output: Copyright information. Specifically, the server runs a program and uses a metadata analysis library to obtain copyright information from the original data.

[1286] Step 4:

[1287] The server checks the copyright information against a database

[1288] The server compares the extracted copyright information with a dedicated database to determine whether the original data is copyrighted. Input: Copyright information. Output: Determination result regarding copyright status. Specifically, the server uses an SQL query to check the compatibility of the database.

[1289] Step 5:

[1290] The server generates a warning message and sends it to the device.

[1291] If copyrighted original data is detected, the server generates a warning message and sends it to the user's device. Input: Judgment result on whether copyright is included. Output: Warning message. Specifically, the server creates a warning message using HTML and JavaScript and sends it to the device as an HTTP response.

[1292] Step 6:

[1293] The device displays a warning message

[1294] The user's device displays the warning message sent from the server in a pop-up format. Input: Warning message. Output: Pop-up warning message. Specifically, the browser executes JavaScript and displays the warning on the screen.

[1295] Step 7:

[1296] The user enters a new prompt.

[1297] Upon receiving the warning, the user re-enters a new prompt. Input: New prompt. Output: Send the new prompt to the server. Specifically, the user re-enters the request text in the text box and clicks the send button.

[1298] Step 8:

[1299] If the server has no copyright issues, it starts the image generation process.

[1300] If the server confirms that there are no copyright issues, it begins generating images using a generative AI model (for example, DALL-E or Stable Diffusion). Input: Prompt text. Output: Generated image. Specifically, the server sends a request to the API of the generative AI model to generate an image.

[1301] Step 9:

[1302] The server embeds a digital fingerprint into the generated image.

[1303] The server embeds a digital fingerprint (e.g., digital watermarking technology) into the generated image. Input: Generated image. Output: Image with embedded fingerprint. Specifically, the server uses libraries such as OpenCV or PyMuPDF to add a digital watermark to the image.

[1304] Step 10:

[1305] The server provides the generated image to the user's device

[1306] After the fingerprint embedding is complete, the server sends the generated image to the user's device. Input: Image with embedded fingerprint. Output: Image displayed to the user. Specifically, the server sends the image as an HTTP response, and the browser displays it.

[1307] This is the specific processing flow of the system. Through these steps, users can use the generative AI model with confidence and obtain images with properly managed copyright information.

[1308] (Application example 1)

[1309] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1310] Conventional image generation systems using generative AI have insufficient management of copyright information, which means that images generated by users may unknowingly infringe copyrights. Furthermore, digital fingerprints to protect the copyright of generated images are often not assigned. This increases the risk of copyright infringement, making it difficult for users to use image generation services with peace of mind. Furthermore, similar security services are needed when users use various devices, such as smartphones, smart glasses, head-mounted displays, and robots, but previous systems have not been able to provide sufficient security.

[1311] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1312] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information, means for checking against a copyright information database to confirm the presence or absence of copyright, means for generating a warning message for original data that includes copyright, means for sending a warning message to a terminal to warn the user, means for starting an image generation process if the copyright is not an issue, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, and means for operating various means such as import of original data, inspection of copyright information, checking against the copyright information database, generation and transmission of a warning message, image generation process, assignment of a digital fingerprint, and provision of the generated image using an application installed on a smartphone, smart glasses, a head-mounted display, and a robot.

[1313] This allows users to properly manage copyright information when creating images, preventing copyright infringement and ensuring that the copyright of the created images is protected. It also supports a variety of devices, including smartphones, smart glasses, head-mounted displays, and robots, providing consistent security services regardless of the device the user uses.

[1314] "Original data" refers to information such as images and text that serves as the basis for use by the generating AI.

[1315] "Copyright information" refers to legal rights information regarding the ownership and usage rights of the original data.

[1316] A "copyright information database" is a database that holds information on content for which copyrights are registered.

[1317] A "warning message" is a message that notifies the user of a possible copyright infringement.

[1318] A "terminal" is a device operated by a user, and includes a smartphone, smart glasses, a head-mounted display, a robot, etc.

[1319] The "image generation process" is the process of using generative AI to generate a new image based on a user request.

[1320] "Digital fingerprinting" refers to techniques such as digital watermarking for embedding copyright information into generated images.

[1321] A "smartphone" is a mobile phone equipped with internet connectivity and various applications.

[1322] "Smart glasses" are glasses-type information terminals that provide visual information.

[1323] A "head-mounted display" is an information display device that is worn on the head and provides visual information.

[1324] A "robot" is a mechanical device used to perform automated operations or tasks.

[1325] An "application" is a software program designed to perform a specific function or task.

[1326] This invention is a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system operates through an application installed on information terminals such as smartphones, smart glasses, head-mounted displays, and robots.

[1327] The server receives an image generation request from the user and begins to import the original data. It then performs a copyright information check on the imported original data and compares it with a copyright information database. This comparison confirms whether the original data is copyrighted. If it is confirmed to be copyrighted, the server generates a warning message and sends it to the terminal to notify the user. This warning message is displayed in a pop-up format, stating, "This content cannot be used because it contains copyright information."

[1328] On the other hand, if it is confirmed that there are no copyright issues, the server begins the image generation process. It uses a generative AI model (e.g., a model using TensorFlow or PyTorch) to generate a new image based on the user's request. The generated image is then checked for copyright information again, and a digital fingerprint (e.g., digital watermarking technology) is embedded if necessary. After the digital fingerprint has been embedded, the generated image is sent to the user's device, where it can be viewed and downloaded.

[1329] As an example of how this system can be used, consider the case where a user makes a request from their smartphone to "generate an illustration of a cathedral." The server inspects the original data, checks it against a copyright information database to ensure there are no violations, and then generates an illustration of the cathedral using a generative AI model. A digital fingerprint is embedded in the generated illustration, which is sent to the user's smartphone. The user can then view and download the generated illustration.

[1330] An example prompt is:

[1331] "I want to generate an illustration of a cathedral."

[1332] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1333] Step 1:

[1334] A user sends an image generation request from a smartphone, smart glasses, head-mounted display, or robot. A prompt sentence (e.g., "Please generate an illustration of a cathedral") is sent as input. The server receives this request. The request content is passed to the server as output.

[1335] Step 2:

[1336] The server starts fetching raw data based on the received prompt statement. The prompt statement is used as input. The server retrieves the relevant raw data from a database or storage. The raw data is fetched as output.

[1337] Step 3:

[1338] The server checks the copyright information of the imported original data. The imported original data is used as input. The server compares the original data with the copyright information database to check whether the copyright is included. The output is the check result (whether or not the copyright exists).

[1339] Step 4:

[1340] The server generates a warning message if copyright is included based on the inspection result. The inspection result is used as input. The server generates a warning message saying "This content is copyrighted and therefore unavailable." The warning message is obtained as output.

[1341] Step 5:

[1342] The server sends the generated warning message to the terminal and notifies the user. The warning message is used as input. The terminal displays the received warning message in a popup format. The warning message is displayed to the user as output.

[1343] Step 6:

[1344] The server starts the image generation process if there are no copyright issues. The prompt and inspection results are used as input. The server uses a generative AI model (e.g., TensorFlow or PyTorch) to generate an image based on the user's request. The generated image is obtained as output.

[1345] Step 7:

[1346] The server embeds a digital fingerprint into the generated image. The generated image is used as input. The server embeds the fingerprint into the image using digital watermarking technology. The output is an image with the embedded digital fingerprint.

[1347] Step 8:

[1348] The server sends the generated image with the embedded digital fingerprint to the terminal, which uses the fingerprinted image as input and displays the received image to the user and makes it available for download, providing the generated image as output, viewable by the user.

[1349] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1350] This invention is a system that combines a system for properly managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI with an emotion engine that recognizes the user's emotions. This system includes means for importing original data, means for inspecting copyright information, means for comparing with a copyright information database, means for generating and transmitting warning messages, an image generation process, means for assigning digital fingerprints, means for providing generated images, and an emotion engine.

[1351] Detailed system description

[1352] Users can generate new images using generated AI.

[1353] The user accesses the generative AI application and makes a request to generate a new image. For example, they input a request such as "I want you to generate an illustration of a cat."

[1354] Importing original data and checking copyright information

[1355] When the server receives the user's request, it starts to fetch the original data. The server checks the copyright information against the original data and compares it with the copyright information database, thereby confirming whether the original data is copyrighted or not.

[1356] Copyright Infringement Warning

[1357] If the server finds that the original data contains copyrighted material, it will generate a warning message in the form of a pop-up and send it to the user's device, warning them that "This content is copyrighted and cannot be used." The user will then need to re-enter their request.

[1358] Image generation when there are no problems

[1359] If the server verifies that there are no copyright issues, it starts the image generation process. The generation AI generates a new image based on the user's request.

[1360] Digital fingerprinting

[1361] The server checks the copyright information again for the generated image, and if copyright information is included, embeds a digital fingerprint (e.g., digital watermarking technology) into the image, thereby clearly indicating the copyright information for the image.

[1362] Providing generated images

[1363] After the fingerprint embedding is complete, the server sends the generated image to the user's device, which displays the generated image to the user and allows the user to download it.

[1364] Use of emotion engine

[1365] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[1366] The emotion engine also analyzes the user's emotional response to the warning message and provides information to the server if the user is feeling stressed or dissatisfied. The server can then use this information to provide an explanation or alternative solution that the user can understand.

[1367] Specific examples

[1368] Example 1: Copyright Infringement Warning Process

[1369] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains the copyright of "Character A." The server generates a pop-up message and sends it to the device. The emotion engine also monitors the user's reaction to the warning message, and if the user feels disappointed or dissatisfied, it sends that information to the server. The server can then suggest other materials and resources that the user can use.

[1370] Example 2: Normal image generation process

[1371] When a user requests a "sunset landscape painting," the server checks the database to ensure there are no copyright issues with the original data. The server then starts the image generation process and embeds a digital fingerprint into the generated landscape painting. After the embedding is complete, the server sends the generated landscape painting to the user's device. The emotion engine monitors the user's reaction and checks whether the user is satisfied. This information is fed back to the server and reflected in future image generation processes.

[1372] The above is a detailed description of an embodiment of the present invention. This system allows users to use generative AI with peace of mind and avoids the risk of copyright infringement. In addition, the use of an emotion engine can increase user satisfaction.

[1373] The processing flow will be explained below.

[1374] Step 1:

[1375] A user opens a generative AI application and makes a request to generate a new image. For example, a user might request, "I want an illustration of a cat."

[1376] Step 2:

[1377] The terminal sends the user's request to the server.

[1378] Step 3:

[1379] The server receives the request and retrieves the raw data required to generate the image.

[1380] Step 4:

[1381] After the server retrieves the original data, it checks the copyright information of the original data.

[1382] Step 5:

[1383] The server checks the original data against a copyright information database to see if the original data contains copyright.

[1384] Step 6:

[1385] The server analyzes the matching results and, if there is original data containing copyright, creates a list of the original data.

[1386] Step 7:

[1387] If the server finds that the original data contains copyright information, it will generate a warning message in the form of a popup.

[1388] Step 8:

[1389] Sends server-generated warning messages to the terminal.

[1390] Step 9:

[1391] The terminal receives the warning message and displays a warning to the user saying, "This content is copyrighted and cannot be used."

[1392] Step 10:

[1393] The emotion engine monitors the user's reaction to the warning message on the device and collects the user's emotion data.

[1394] Step 11:

[1395] The user enters a new request or takes the appropriate action.

[1396] Step 12:

[1397] The server receives the request again and inspects the original data (resume from step 3).

[1398] Step 13:

[1399] If the server verifies that there are no copyright issues with the original data, it starts the image generation process.

[1400] Step 14:

[1401] A generation AI built into the server generates a new image based on the request.

[1402] Step 15:

[1403] The emotion engine analyzes the user's emotions while executing the request and sends the information to the server.

[1404] Step 16:

[1405] The server will double-check the copyright information on the generated image.

[1406] Step 17:

[1407] If the server generates an image containing copyright, it embeds a digital fingerprint.

[1408] Step 18:

[1409] The server verifies that the digital fingerprint embedding was completed successfully.

[1410] Step 19:

[1411] The server transmits the generated image to the terminal.

[1412] Step 20:

[1413] The terminal displays the generated image to the user and allows the user to download it.

[1414] Step 21:

[1415] The emotion engine monitors the user's reactions as they view the generated images and collects their emotion data.

[1416] Step 22:

[1417] The collected emotion data is fed back to the server and used to optimize future image generation processes.

[1418] Step 23:

[1419] The user can review the generated images and download or request new ones as needed.

[1420] Example 2

[1421] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1422] Conventional generative AI systems often lacked methods for properly managing copyright information on the original data and effectively preventing violations. Furthermore, they were unable to incorporate the emotions felt by users during the image generation process, which hindered efforts to improve user satisfaction. Furthermore, there was an insufficient method for clearly indicating copyright information on generated images, making copyright protection of images difficult.

[1423] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1424] In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the existence of copyright by comparing it with a copyright information database, means for generating a warning message for original data containing copyright, means for sending the warning message to a terminal to warn a user, means for starting an image generation process if the copyright is not an issue, means for using a generative AI model in the image generation process, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, means for using an emotion engine for recognizing user emotions, and means for analyzing emotion data obtained from the emotion engine to optimize the image generation process. This makes it possible to appropriately manage the copyright of the original data and improve user satisfaction, while avoiding the risk of copyright infringement and effectively indicating copyright information on generated images.

[1425] 1. "Original Data" refers to the initial data used to generate an image, including user-entered text and image files.

[1426] 2. "Copyright Information" refers to information that describes the legally protected rights and details of such rights regarding data and content.

[1427] 3. "Copyright Information Database" refers to a database that stores copyright-related information and makes it searchable and collatable.

[1428] 4. "Warning Message" means an alert message that notifies the user of a possible copyright infringement.

[1429] 5. "Terminal" refers to a device such as a computer, smartphone, or tablet that a user uses to operate an image generation system.

[1430] 6. “Image generation process” refers to the general procedure for using a generative AI model to create a new image based on a user request.

[1431] 7. "Generative AI model" refers to algorithms or software that use artificial intelligence techniques to generate new images from user input data.

[1432] 8. "Digital fingerprint" refers to identification information applied to a generated image, and refers to a method of clearly indicating copyright information using digital watermarking technology, etc.

[1433] 9. "Emotion engine" refers to technology or software for recognizing and analyzing user emotions.

[1434] 10. "Emotion Data" refers to data regarding a user's emotions obtained by the emotion engine.

[1435] The present invention provides a system for appropriately managing copyright information of original data and avoiding the risk of copyright infringement when a user generates an image using generative AI. This system includes a means for importing original data, a means for inspecting copyright information, a means for comparing with a copyright information database, a means for generating and transmitting a warning message, an image generation process, a means for assigning a digital fingerprint, a means for providing the generated image, and an emotion engine. The embodiments of each element are described in detail below.

[1436] Importing original data and checking copyright information

[1437] The server receives a request from the user and starts to retrieve the original data. Specifically, the user accesses the generation AI application and inputs a request such as "I want you to generate an illustration of a cat." The request is sent to the server as an HTTP request.

[1438] After the original data is imported into the server, the server checks it for copyright information. To do this, the server uses specialized analysis software to extract metadata and existing copyright information from the original data. The extracted copyright information is then checked against internal or external copyright information databases via API.

[1439] Copyright strike and re-entry request

[1440] If the original data contains copyright, the server generates a warning message and sends it to the terminal. This message states, "This content is copyrighted and cannot be used," and the user must re-enter the request. This warning message is displayed in a pop-up format.

[1441] Image Generation Process

[1442] When a user inputs a request that does not have copyright issues, the server starts the image generation process. The server launches a generative AI model and inputs the user's prompt (e.g., "I want you to generate a landscape painting of a sunset") into the model. Technologies such as Stable Diffusion and DALL-E are used as the generative AI model.

[1443] Digital fingerprinting

[1444] If the generated image is verified as legitimate, the server embeds a digital fingerprint into the image, using digital watermarking technology, which clearly identifies the copyright information for the generated image.

[1445] Providing generated images

[1446] The image with the embedded digital fingerprint is then sent back from the server to the user's device, where the generated image is displayed and made available for download.

[1447] Use of emotion engine

[1448] The system includes an emotion engine that recognizes the user's emotions. The emotion engine monitors the user's reactions when making an image generation request and when receiving a warning message, and analyzes the emotional data. For example, if the user expresses joy or excitement in response to a request, feedback is sent to the server to optimize the image generation process. This allows the generated image to be adjusted to increase user satisfaction.

[1449] The emotion engine also analyzes the user's emotional response to the warning message and provides information about stress or frustration to the server, which can then provide a more understandable explanation or alternative, such as suggesting the use of other permitted material.

[1450] This invention allows users to use generative AI with peace of mind, avoiding the risk of copyright infringement, and increases user satisfaction through the use of an emotion engine.

[1451] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1452] Step 1:

[1453] Description: A user accesses the generative AI application and enters a request to generate an image.

[1454] Input: The user enters the prompt "I want an illustration of a cat."

[1455] How it works: The user launches a browser or a dedicated app, enters a prompt in the text box, and clicks the "Submit" button.

[1456] Output: The entered prompt text is sent to the server as an HTTP request.

[1457] Step 2:

[1458] Description: The server receives the user request and starts fetching the raw data.

[1459] Input: The prompt text included in the HTTP request received by the server.

[1460] What happens: The server parses the HTTP request and begins the process of retrieving the original data.

[1461] Output: The original data is temporarily saved.

[1462] Step 3:

[1463] Description: The server checks the original data for copyright information and matches it with a copyright information database.

[1464] Input: Temporarily saved original data.

[1465] How it works: The server uses analysis software to extract metadata and copyright information from the raw data, and sends API requests to a copyright information database for matching.

[1466] Output: The result of the copyright check.

[1467] Step 4:

[1468] Description: If the server verifies the copyright information and finds any problems, it generates a warning message and sends it to the user's device.

[1469] Input: If the copyright information check results in "problem".

[1470] Behavior: The server generates a warning message stating "This content is copyrighted and therefore unavailable" and sends it to the device as an HTTP response.

[1471] Output: A warning message is displayed on the terminal.

[1472] Step 5:

[1473] Description: If the server has no copyright issues, it will start the image generation process.

[1474] Input: If the copyright information check result is "OK".

[1475] How it works: The server launches a generative AI model (e.g., Stable Diffusion or DALL-E) and passes the prompt statement as input.

[1476] Output: The generative AI model generates new image data.

[1477] Step 6:

[1478] Description: The server double-checks the generated image for copyright information and embeds a digital fingerprint if copyright is present.

[1479] Input: The newly generated image data.

[1480] How it works: The server uses digital watermarking technology to embed copyright information into the image as a digital fingerprint.

[1481] Output: Image data with embedded digital fingerprint.

[1482] Step 7:

[1483] Description: The server sends the generated image to the user's device.

[1484] Input: Image data with embedded digital fingerprint.

[1485] Operation: The server sends the image data to the user's device as an HTTP response.

[1486] Output: The generated image is displayed on the device, ready for the user to download.

[1487] Step 8:

[1488] Description: The emotion engine monitors the user's reactions and provides this information to the server.

[1489] Input: Emotional data such as user behavior, facial expressions, and tone of voice.

[1490] How it works: The emotion engine analyzes the user's reactions using the camera and microphone, and sends the analysis results back to the server.

[1491] Output: The server receives the emotion data and uses the analysis results to improve the image generation process in the future.

[1492] By following the above steps, the system can safely generate images based on the user's prompt sentence, improving user satisfaction.

[1493] (Application example 2)

[1494] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1495] When generating images using generative AI technology, it is necessary to properly manage the copyright information of the original data to avoid the risk of copyright infringement by users and to increase user satisfaction. It is also important to understand how users feel about their experience during the generation process and provide feedback accordingly.

[1496] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for starting the import of original data, means for inspecting copyright information of the original data, means for checking the presence or absence of intellectual property by comparing the original data with a copyright information database, means for generating a warning message for original data that includes intellectual property, means for sending the warning message to the terminal to warn the user, means for starting the image generation process if the intellectual property is not a problem, means for embedding a digital fingerprint in the generated image, means for sending the generated image to the terminal, an emotion engine for analyzing the user's emotions, means for receiving feedback from the emotion engine, and means for optimizing the image generation process based on the feedback. This enables accurate management of intellectual property information and optimal image generation according to the user's emotions.

[1497] The "means for initiating the import of raw data" is a function for initiating a process based on data provided by the user.

[1498] The "means for inspecting copyright information of original data" is a function for checking copyright information included in the original data.

[1499] "Means for checking the existence of intellectual property by checking against the copyright information database" is a function for comparing the copyright information database with the original data to check whether intellectual property rights exist.

[1500] The "means for generating a warning message for original data containing intellectual property" is a function for generating a warning message to the user when intellectual property is included in the original data.

[1501] The "means for sending a warning message to the terminal to warn the user" is a function for sending a warning message to the user's terminal and notifying the user.

[1502] The "means for starting the image generation process when there are no intellectual property issues" is a function for starting image generation based on original data that has no copyright issues.

[1503] The "means for embedding a digital fingerprint in the generated image" is a function for embedding a digital fingerprint in the generated image to identify the ownership and origin of the image.

[1504] The "means for transmitting the generated image to the terminal" is a function for transmitting the generated image to the user's terminal.

[1505] The "emotion engine that analyzes user emotions" is a component that analyzes the user's emotions and provides feedback based on that data.

[1506] The "means for receiving feedback from the emotion engine" is a function for receiving emotion information analyzed by the emotion engine and adjusting the process based on that information.

[1507] The "means for optimizing the image generation process based on feedback" is a function for optimizing the image generation process based on feedback information obtained from the emotion engine, thereby increasing user satisfaction.

[1508] The system of the present invention implements a series of processes, including the import of original data, the search for copyright information, the image generation process, the assignment of a digital fingerprint, and feedback by an emotion engine. Specific embodiments will be described below.

[1509] Program Generation and Processing Description

[1510] This system is a combination of a server, a user terminal, and an emotion engine, and each function works in cooperation with the others.

[1511] Hardware and Software Configuration

[1512] Server: This is the main component that imports original data, checks and collates copyright information, generates images, assigns digital fingerprints, and processes feedback from the emotion engine. The server contains an image processing API (ImageProcessingAPI), an emotion analysis API (EmotionAPI), and a copyright information inspection API (CopyrightCheckAPI).

[1513] User terminal: A device on which a user inputs image generation requests and receives generated images and alert messages. Examples include mobile devices such as smartphones and tablets.

[1514] Emotion Engine: A component that analyzes the user's emotions and provides the feedback to the server. The emotion engine is designed to analyze the user's input data and reactions.

[1515] System operation explanation

[1516] 1. Importing original data: Receive an image generation request from the user device. For example, the user may input a request such as "I want an illustration of a cat to be generated."

[1517] 2. Copyright information inspection and matching: The server searches for the copyright information of the original data and matches it with the copyright information database. For example, if the original data is "Character A", it will compare it with the copyright database to see if the character is copyrighted.

[1518] 3. Generating a warning message: If the server detects that the original data contains copyrighted material, it generates a warning message and sends it to the user's device. For example, if a user requests an illustration of a famous character, the server sends a message stating, "This content is copyrighted and therefore unavailable."

[1519] 4. Image generation process: If there are no copyright issues, the server uses the generation AI to generate a new image based on the user request. For example, if a user requests a "sunset landscape painting," the server generates a landscape painting after confirming that there are no issues with the copyright database.

[1520] 5. Digital Fingerprinting: The server embeds a digital fingerprint into the generated image, using digital watermarking technology to clearly indicate copyright information for the image.

[1521] 6. Providing the generated image: The image with the embedded fingerprint is sent to the user's device, allowing the user to view and download the image.

[1522] 7. Use of Emotion Engine: The emotion engine analyzes the user's emotions regarding requests and warning messages and feeds the data back to the server, which then optimizes the image generation process based on this feedback to improve user satisfaction.

[1523] Specific examples

[1524] Copyright Strike Process

[1525] When a user requests an "illustration of a famous character" using the generative AI, the server checks the database and detects that the original data contains copyright. The server then sends a pop-up message to the user's device stating, "This content is copyrighted and cannot be used."

[1526] Normal image generation process

[1527] When a user requests a "sunset landscape painting," the server checks the database to ensure that the original data is free of copyright issues. The server then starts the image generation process and embeds a digital fingerprint into the resulting landscape painting. After the embedding is complete, the server sends the resulting landscape painting to the user's device.

[1528] Prompt Sentence Examples

[1529] "I want to generate a sunset landscape image."

[1530] "I want you to generate an illustration of a cat"

[1531] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1532] Step 1:

[1533] The user inputs an image generation request from the terminal. For example, the user inputs a prompt such as "I want an illustration of a cat." The input prompt is sent to the system. The input data is passed to the server as a user request.

[1534] Step 2:

[1535] The server starts capturing the original data, collects relevant image data based on the prompts from the user, and passes the captured original data to the inspection process, which then uses the captured original data as input data for copyright information inspection.

[1536] Step 3:

[1537] The server checks the copyright information of the original data, analyzes the imported data, and processes it to extract the copyright information. The results of this data processing are compared with a copyright information database.

[1538] Step 4:

[1539] The server checks the existence of intellectual property by checking against the copyright information database. The copyright information extracted from the original data is compared with the database to check whether the rights exist. Based on the results from the database, the existence of intellectual property is output.

[1540] Step 5:

[1541] If intellectual property is included, the server generates a warning message. If intellectual property is included, a message to warn the user is generated and sent to the terminal as a warning. Specifically, the message reads, "This content cannot be used because it contains copyright."

[1542] Step 6:

[1543] A warning message is displayed in a pop-up format on the user's device. The user can correct or re-enter the request. The displayed warning message is notified to the user, and the user's reaction is analyzed by the emotion engine.

[1544] Step 7:

[1545] If the intellectual property is clear, the server starts the image generation process. It runs a generative AI model using the original data that has passed copyright inspection to generate a new image. This generated image is then passed on to the next step in the process.

[1546] Step 8:

[1547] The server embeds a digital fingerprint into the generated image. The server then embeds copyright information into the generated image using digital watermarking technology. This process clearly identifies the copyright information for the image.

[1548] Step 9:

[1549] The server sends the generated image to the user's device. The image data with the embedded fingerprint is transferred to the user's device, where it can be downloaded and displayed by the user. The image sent to the device is then confirmed by the user.

[1550] Step 10:

[1551] The emotion engine analyzes the user's emotions. It monitors the user's reaction to the images sent to the device and feeds that data back to the server. The user's emotional data is analyzed and used for further processing.

[1552] Step 11:

[1553] The server receives feedback from the emotion engine and optimizes the image generation process. Based on the user's emotion data, it adjusts the parameters of the AI ​​model and prompts to optimize the generation process from the next time onwards. This improves user satisfaction.

[1554] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1555] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1556] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1557] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1558] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1559] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1560] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1561] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1562] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1563] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1564] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1565] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1566] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1567] 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.

[1568] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1569] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1570] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1571] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1572] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1573] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1574] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1575] The following is further disclosed regarding the above embodiment.

[1576] (Claim 1)

[1577] a means for initiating the capture of the raw data;

[1578] means for inspecting the copyright information of the original data;

[1579] A means of checking whether or not a copyright exists by checking against a copyright information database;

[1580] a means for generating a warning message for original data containing copyright;

[1581] means for sending a warning message to the terminal to warn the user;

[1582] a means for initiating the image generation process if copyright is acceptable;

[1583] means for embedding a digital fingerprint in the generated image;

[1584] means for transmitting the generated image to a terminal;

[1585] A system including:

[1586] (Claim 2)

[1587] 2. The system according to claim 1, wherein the means for generating a warning message for original data containing copyright generates a message in a pop-up format.

[1588] (Claim 3)

[1589] 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology.

[1590] "Example 1"

[1591] (Claim 1)

[1592] a means for the user to input a prompt sentence;

[1593] a means for initiating the capture of the raw data;

[1594] means for inspecting the copyright information of the original data;

[1595] A means of checking whether or not a copyright exists by checking against a copyright information database;

[1596] a means for generating a warning message for original data containing copyright;

[1597] means for sending a warning message to the terminal to warn the user;

[1598] means for initiating the image generation process if there are no copyright issues;

[1599] means for embedding a digital fingerprint in the generated image;

[1600] means for transmitting the generated image to a terminal;

[1601] A system including:

[1602] (Claim 2)

[1603] 2. The system according to claim 1, wherein the means for generating a warning message for original data containing copyright generates a message in a pop-up format.

[1604] (Claim 3)

[1605] 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology.

[1606] "Application Example 1"

[1607] (Claim 1)

[1608] a means for initiating the capture of the raw data;

[1609] means for inspecting the copyright information of the original data;

[1610] A means of checking whether or not a copyright exists by checking against a copyright information database;

[1611] a means for generating a warning message for original data containing copyright;

[1612] means for sending a warning message to the terminal to warn the user;

[1613] a means for initiating the image generation process if copyright is acceptable;

[1614] means for embedding a digital fingerprint in the generated image;

[1615] means for transmitting the generated image to a terminal;

[1616] A means for operating various means, such as importing original data, inspecting copyright information, comparing with a copyright information database, generating and sending a warning message, image generation process, adding a digital fingerprint, and providing the generated image, on an application installed on a smartphone, smart glasses, a head-mounted display, or a robot;

[1617] A system including:

[1618] (Claim 2)

[1619] 2. The system according to claim 1, wherein the means for generating a warning message for original data containing copyright generates a message in a pop-up format.

[1620] (Claim 3)

[1621] 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology.

[1622] "Example 2: Combining Emotion Engines"

[1623] (Claim 1)

[1624] a means for initiating the capture of the raw data;

[1625] means for inspecting the copyright information of the original data;

[1626] A means of checking whether or not a copyright exists by checking against a copyright information database;

[1627] a means for generating a warning message for original data containing copyright;

[1628] means for sending a warning message to the terminal to warn the user;

[1629] a means for initiating the image generation process if copyright is acceptable;

[1630] A means for using a generative AI model in the image generation process; and

[1631] means for embedding a digital fingerprint in the generated image;

[1632] means for transmitting the generated image to a terminal;

[1633] means for using an emotion engine to recognize the emotion of a user;

[1634] means for analyzing the emotion data obtained from the emotion engine to optimize the generative image process;

[1635] A system including:

[1636] (Claim 2)

[1637] 2. The system according to claim 1, wherein the means for generating a warning message for original data containing copyright generates a message in a pop-up format.

[1638] (Claim 3)

[1639] 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology.

[1640] "Application example 2 when combining emotion engines"

[1641] (Claim 1)

[1642] a means for initiating the capture of the raw data;

[1643] means for inspecting the copyright information of the original data;

[1644] A means of checking the existence of intellectual property by checking against copyright information databases;

[1645] means for generating a warning message for the original data containing intellectual property;

[1646] means for sending a warning message to the terminal to warn the user;

[1647] means for initiating the image generation process if the intellectual property is clear;

[1648] means for embedding a digital fingerprint in the generated image;

[1649] means for transmitting the generated image to a terminal;

[1650] An emotion engine that analyzes the user's emotions,

[1651] a means of receiving feedback from the emotion engine; and

[1652] means for optimizing the image generation process based on the feedback;

[1653] A system including:

[1654] (Claim 2)

[1655] 2. The system of claim 1, wherein the means for generating the warning message generates a message in the form of a pop-up.

[1656] (Claim 3)

[1657] 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology. [Explanation of symbols]

[1658] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for initiating the capture of the raw data; means for inspecting the copyright information of the original data; A means of checking whether or not a copyright exists by checking against a copyright information database; a means for generating a warning message for original data containing copyright; means for sending a warning message to the terminal to warn the user; a means for initiating the image generation process if copyright is acceptable; means for embedding a digital fingerprint in the generated image; means for transmitting the generated image to a terminal; A system including:

2. 2. The system according to claim 1, wherein the means for generating a warning message for original data containing copyright generates a message in a pop-up format.

3. 2. The system of claim 1, wherein the means for embedding a digital fingerprint in the generated image uses digital watermarking technology.

Images