Cooperative work project management method using generative artificial intelligence and electronic device therefor

Abstract

Disclosed is an electronic device comprising a display, at least one processor, and a memory for storing instructions. The electronic device may: acquire an input prompt for a first project; identify a common prompt configured for the first project; generate a modified prompt by using the common prompt and the input prompt; and acquire result data by inputting the modified prompt to at least one generative AI model configured for the first project.

Description

Collaborative project management method using generative artificial intelligence and electronic device therefor

[0001] Embodiments disclosed in this document relate to a method for managing a cooperative work project using generative artificial intelligence and an electronic device therefor.

[0002] Various services are being used to support collaborative projects. Collaborative projects can be carried out by multiple users sharing data related to a single project. For collaborative projects, a virtual workspace can be provided. For example, collaborative projects can be carried out by users sharing data through shared storage. Users can upload data to the shared workspace and leave comments on other users' uploads.

[0003] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art in connection with the present disclosure.

[0004] An electronic device according to an embodiment disclosed in the present document may include a display, a memory, and at least one processor communicatively connected to the display and the display. The memory may store instructions that, when individually or collectively executed by the at least one processor, cause the electronic device to obtain an input prompt for a first project, identify a common prompt set for the first project, generate a modified prompt using the common prompt and the input prompt, and input the modified prompt into at least one generative artificial intelligence (AI) model set for the first project, thereby obtaining result data.

[0005] In addition, a method for managing a collaborative project of an electronic device according to an embodiment disclosed in the present document may include an operation of obtaining an input prompt for a first project, an operation of identifying a common prompt set for the first project, an operation of generating a modified prompt using the common prompt and the input prompt, and an operation of obtaining result data by inputting the modified prompt into at least one generative AI model set for the first project.

[0006] A computer-readable storage medium according to an embodiment disclosed in this document can store instructions that, when executed by a processor of an electronic device, cause the electronic device to perform a method for managing the collaborative project.

[0007] Figure 1 illustrates a collaboration system according to one embodiment.

[0008] FIG. 2A illustrates a block diagram of an electronic device according to one embodiment.

[0009] Figure 2b illustrates the structure of a collaborative system according to one embodiment.

[0010] Figure 2c illustrates the structure of a collaborative system according to one embodiment.

[0011] Figure 3 illustrates the structure of an AI model according to one embodiment.

[0012] Figure 4 is a flowchart of a task performing method according to one embodiment.

[0013] Figure 5 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0014] Figure 6 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0015] Figure 7 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0016] Figure 8 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0017] Figure 9 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0018] Figure 10 illustrates an example of a user interface (UI) for setting common policies.

[0019] Figure 11 is a flowchart of a prompt processing method according to one embodiment.

[0020] Figure 12 illustrates an example of a UI for showing results according to a common policy.

[0021] FIG. 13 illustrates a flowchart of a method for collaborative project management using generative artificial intelligence according to one embodiment.

[0022] FIG. 14 is a block diagram of an exemplary electronic device capable of performing the operations described in this document.

[0023] In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0024] Hereinafter, various embodiments of the present invention will be described with reference to the attached drawings. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention encompasses various modifications, equivalents, and / or alternatives of the embodiments.

[0025] Figure 1 illustrates a collaboration system according to one embodiment.

[0026] Referring to FIG. 1, according to one embodiment, a collaboration system (200) may include a plurality of electronic devices associated with a collaboration project (30). The structure and configuration of the collaboration system (200) described with respect to FIG. 1 are merely examples, and those skilled in the art will appreciate that modified structures and configurations may be utilized. For example, the number of electronic devices associated with the collaboration system (200) may differ from that illustrated in FIG. 1. For example, the illustrated configurations of the first electronic device (10a), the second electronic device (10b), the third electronic device (10c), and the server device (20) are merely examples for illustrative purposes.

[0027] A collaborative project (30) may include any project (e.g., a work project, a music project, and / or an advertising project) associated with multiple entities or multiple users. A collaborative project (30) may be referred to as a logical task agreed upon between multiple users. In one example, a collaborative project (30) may be referred to as a database stored on a non-transitory computer-readable medium. In the present disclosure, the term “collaborative project” may be referred to as a data set stored in association with a project or an index referring to the data set.

[0028] For example, a collaborative project (30) may be associated with multiple electronic devices. The multiple electronic devices may include, for example, a server device (20), a first electronic device (10a), a second electronic device (10b), and / or a third electronic device (30c).

[0029] In one example, the collaboration system (200) may include a server device (20) and client devices. For example, the first electronic device (10a), the second electronic device (10b), and the third electronic device (10c) may be client devices that can access a collaboration project (30) stored in the server device (20). Each client device may store at least a portion of data associated with the collaboration project (30).

[0030] In one example, the collaboration system (200) may have a distributed network structure. Each of a plurality of electronic devices (10a, 10b, 10c) may be configured to manage data. For example, data from a collaboration project (30) by a first electronic device (10a) may be shared with a second electronic device (10b) and a third electronic device (10c). The second electronic device (10b) and the third electronic device (10c) may use data received from the first electronic device (10a) to update data associated with the collaboration project (30).

[0031] According to one embodiment, the collaboration system (200) may utilize artificial intelligence. For example, a user may add data generated using an AI model to a collaboration project (30). The user may edit data in the collaboration project (30) using the AI ​​model. The data in the collaboration project (30) may include, for example, images, videos, text, structured text, documents, formatted documents, and / or music.

[0032] When generating outputs using an AI model, the output may vary depending on the input prompts of each user. Prompts may be referenced as input data to the AI ​​model. Prompts may include text, structured text, and / or images (or feature information extracted from images). For example, multiple users may create documents related to the same project. In this case, the output may vary depending on the prompts entered by each user. Due to these different outputs, a common tone and / or code may not be maintained within a single document. For example, the tone of a document may include the format, background, font, alignment, and / or layout of the document. For example, the code of a document may include the subject matter of the document, prohibited content, and / or narrative style within the document.

[0033] According to one embodiment of the present disclosure, prompts can be generated based on common policies (e.g., common rules) for collaborative projects (30). By generating prompts based on common policies, results with identical tones and / or codes can be generated. By maintaining the tones and / or codes, the post-processing required to integrate AI model results can be reduced.

[0034] FIG. 2A illustrates a block diagram of an electronic device according to one embodiment.

[0035] Referring to FIG. 2A, according to one embodiment, an electronic device (10) may include a processor (120), a memory (130), a display (160), an interface (180), and / or a communication circuit (190). The electronic device (10) may correspond to the first electronic device (10a), the second electronic device (10b), the third electronic device (10c) of FIG. 1, and / or the electronic device (1400) of FIG. 14. The electronic device (10) may include a configuration similar to the electronic device (1400) described below with reference to FIG. 14. For example, the processor (120) may correspond to at least one processor (1410) of FIG. 14. For example, the memory (130) may correspond to the memory (1420) of FIG. 14. For example, the display (160) may correspond to the display (1440) of FIG. 14. For example, the communication circuit (190) may correspond to the communication circuit (1460) of FIG. 14. The configuration of the electronic device (10) illustrated in FIG. 2A is exemplary, and the configuration of the electronic device (10) is not limited thereto. For example, the electronic device (10) may further include configurations not illustrated in FIG. 2A. For example, the electronic device (10) may not include at least one of the configurations illustrated in FIG. 2A.

[0036] The processor (120) may be communicatively, electrically, operatively, or functionally connected to the memory (130), the display (160), the interface (180), and / or the communication circuitry (190). In various embodiments of the present disclosure, when a component is “operatively” connected to another component, it may mean that the component is connected so as to be able to operate the other component. For example, the component may operate the other component by transmitting a control signal to the other component, either directly or via another component. In various embodiments of the present disclosure, when a component is “functionally” connected to another component, it may mean that the component is connected so as to be able to execute a function of the other component. For example, the component may execute a function of the other component by transmitting a control signal to the other component, either directly or via another component.

[0037] The processor (120) may include at least one processor. For example, the processor (120) may include an application processor (AP), a central processing unit (CPU), a graphics processing unit (GPU), a neural processing unit (NPU), a tensor processing unit (TPU), and / or a communication processor (CP). The processor (120) may include at least one chip or one chipset. In the present disclosure, the processor (120) may be referred to as a hardware component having an architecture by at least one processing circuit. For example, the processor (120) may be mounted on a substrate (e.g., a printed circuit board) located within the electronic device (10) and may communicate with other components of the electronic device (10) through at least one conductive path formed on the substrate.

[0038] The memory (130) can store instructions. When executed by the processor (120), the instructions can cause the electronic device (10) to perform various operations. For example, the instructions can be individually or collectively executed by at least one processor to cause the electronic device (10) to perform various operations. In various embodiments of the present disclosure, the operation of the electronic device (10) can be referred to as an operation performed by the processor (120) by executing instructions stored in the memory (130). The memory (130) can be referred to as a hardware component for data storage.

[0039] The display (160) may include at least one pixel configured to display an image. In one example, the display (160) may include multiple displays. For example, the display (160) may include a left-eye display and a right-eye display. The display (160) may include a front display and / or a rear display. The display (160) may include at least one of a see-through display, a flexible display, a rollable display, a foldable display, and / or a rigid display.

[0040] The interface (180) may include at least one device configured to receive input. For example, the interface (180) may include a touch sensor (e.g., a touch screen display) configured to receive touch input. The interface (180) may include at least one microphone configured to receive voice input. The interface (180) may include at least one camera configured to receive image input. The interface (180) may include at least one device for output. For example, the interface (180) may include a haptic module for tactile output, at least one microphone for sound output, and / or an indicator. The interface (180) may include any human interface device (HID). According to one embodiment, the processor (120) may be configured to receive input using the interface (180) and process the received input.

[0041] The communication circuit (190) may be configured to perform short-range wireless communication and / or long-range wireless communication. The communication circuit (190) may include a network interface card (NIC). The processor (120) may communicate with other external electronic devices based on wireless communication and / or wired communication, for example, using the communication circuit (190). The processor (120) may communicate with an external device via an IP (Internet Protocol) network, for example, using the communication circuit (190).

[0042] According to one embodiment, the electronic device (10) may be configured to implement a collaborative system (200a). For example, the components of the collaborative system (200a) may be software modules (e.g., threads, functions, databases, and / or programs) implemented by the electronic device (10) executing instructions stored in the memory (130) using the processor (120).

[0043] For example, the collaboration system (200a) may include an application (210), a prompt manager (240), a collaboration prompt database (DB) (250), a personal prompt DB (260), and / or an artificial intelligence (AI) module (270). The components of the collaboration system (200a) are examples, and at least some of the components may be implemented as a single software module.

[0044] The application (210) may be an application associated with a project installed on the electronic device (10). The application (210) may manage projects (e.g., personal projects and / or collaborative projects) associated with the electronic device (10) (or an account of the electronic device (10)) and control access to the projects. The application (210) may operate as a user interface (e.g., a front-end). For example, the processor (120) may obtain input from an external electronic device using the interface (180) or using the communication circuit (190). The application (210) may provide a user interface for obtaining input. The application (210) may include a project manager (220) and an account manager (230).

[0045] A project manager (220) can manage a project associated with an electronic device (10) or an account of the electronic device (10) (e.g., an account logged in using the electronic device (10). The project manager (220) can store information about a project associated with an electronic device (10) or an account of the electronic device (10). For example, information about a project can include a name of the project, a period of the project, a type of project, an AI model associated with the project, common policies associated with the project, and / or information about a user associated with the project.

[0046] The type of project may include, for example, a personal project and / or a collaborative project. The processor (120) can use project type information managed by the project manager (220) to distinguish whether a specific project is a personal project or a collaborative project.

[0047] Information about AI models associated with a project may include information about at least one AI model configured for use in connection with a specific project. For example, if an AI model configured for a specific project exists, the processor (120) may use that AI model to process a prompt for the specific project.

[0048] A common policy associated with a project may include at least one common prompt set for the project. Information about the common prompt may be stored in the collaboration prompt database (250). For example, the common prompt may include information about guidelines to be input into the artificial intelligence in relation to the project. For example, the common prompt may include the format of the document, table items, graph types, colors, common objects in the image (e.g., watermarks, people), text items, image tone, and / or image style. For example, the format of the document may include the structure of the document (e.g., the arrangement of the title and content), font type, font size, common content to be included in the document, content to be controlled, and / or layer style.

[0049] Information about users associated with a project may include information about accounts and / or electronic devices associated with the project. Information about users may include permission information set for the user (e.g., access rights to a specific project and / or permissions to edit common policies). Information about users associated with a project may include information about an organization (e.g., a department) associated with the project. Common policies may be set for the project and / or for the organization. For example, if a first common policy is set for a project and a second common policy is set for an organization associated with the project, the processor (120) may generate a prompt based on the first common policy and the second common policy.

[0050] The account manager (230) can identify the user of the electronic device (10). For example, the account manager (230) may be configured to process a user's login to the application (210). The account manager (230) can process the user's login by transmitting the entered login information to an external server (not shown) and receiving the login information processing result from the external server. For example, the processor (120) can process the user's login request using the account manager (230) and, if the login result is successful, provide information about a project associated with the logged-in account.

[0051] The prompt manager (240) can generate at least one prompt using information received from the application. When an input is received from the application (210), the prompt manager (240) can be configured to generate a prompt based on a common policy set for the input and the related project. The prompt manager (240) can obtain information about a project associated with the input from the application (210). The prompt manager (240) can identify at least one common prompt associated with the project from the collaboration prompt database (250) using the project information. The prompt manager (240) can generate a prompt including the prompt generated from the input and the common prompt. In one example, the collaboration prompt database (250) can be stored in an entity external to the electronic device (10) (e.g., the server (20) of FIG. 1). The electronic device (10) can identify a common project based on information received from the external entity.

[0052] In the present disclosure, processing may be performed on the input in the process of generating a prompt from the input. For example, if the input is a voice input, text conversion and natural language understanding may be performed on the voice input. For example, if the input includes an image, feature extraction or object identification may be performed on the image. The prompt manager (240) may generate a prompt using text information, feature information, and / or object information extracted from the voice input. In one example, the prompt manager (240) may generate a prompt using an AI model. The prompt manager (240) may generate a prompt by processing text information, feature information, and / or object information extracted from the voice input using an AI model.

[0053] In one example, input received from an application (210) may take the form of a prompt. In this case, the prompt manager (240) may generate a modified prompt by merging an input prompt and a common prompt. Hereinafter, the input prompt and the prompt derived from the input may be referred to as an input-based prompt. A prompt generated based on the input-based prompt and the common prompt may be referred to as a modified prompt.

[0054] The AI ​​module (270) can process the modified prompt generated by the prompt manager (240) using an AI model associated with the project. For example, the AI ​​model can be stored in the memory (130) of the electronic device (10). The AI ​​model can include, for example, an AI model (e.g., ) described below with reference to FIG. 3. The AI ​​module (270) can input a prompt into the AI ​​model to obtain a result, and provide the obtained result to another service (e.g., a service associated with the application (210)). The processor (120) can provide the result processed by the AI ​​model using the application (210). For example, the processor (120) can display the result using the display (160).

[0055] The personal prompt DB (260) can store information on prompts generated in relation to personal projects. In one example, the personal prompt DB (260) can be omitted from the collaboration system (200a).

[0056] With reference to FIG. 2A, an example in which the collaboration system (200a) is implemented by the electronic device (10) has been described, but embodiments of the present disclosure are not limited thereto. For example, at least some of the information that the electronic device (10) can acquire may be acquired from an external device (e.g., the server (20) of FIG. 1) through an application (210). For example, as described below with reference to FIG. 2B, the collaboration system (200a) may have a server-client architecture.

[0057] Figure 2b illustrates the structure of a collaborative system according to one embodiment.

[0058] Referring to FIG. 2b, according to one embodiment, a collaboration system (200b) may include an electronic device (10) and a server device (20). The electronic device (10) may include an application (210). The application (210) may operate as a client module for the server device (20). The server device (20) may include a prompt manager (240), a collaboration prompt DB (250), a personal prompt DB (250), and / or an AI module (270). Unless otherwise described, descriptions of components having the same reference numerals as those in FIG. 2b may be referred to by the description of FIG. 2a.

[0059] When a task request input related to a collaborative project is acquired, the project manager (220) can transmit the input and information about the project related to the input to the server device (20). The server device (20) can identify the received input and project information related to the input. The server device (20) can generate a modified prompt using a common policy (e.g., a common prompt) related to the received input and the project. The server device (20) can process the modified prompt using an AI model (e.g., an AI model stored in the server device (20)) and transmit the processing result to the electronic device (10).

[0060] Figure 2c illustrates the structure of a collaborative system according to one embodiment.

[0061] Referring to FIG. 2c, the collaboration system (200c) may include a first electronic device (10a) and a second electronic device (10b). Each of the first electronic device (10a) and the second electronic device (10b) may include software modules corresponding to the collaboration system (200a) of FIG. 2a. For example, the application (210a) and the application (210b) may correspond to the application (210) of FIG. 2a. The prompt manager (240a) and the prompt manager (240b) may correspond to the prompt manager (240) of FIG. 2a.

[0062] The collaboration prompt DB (250a) and the collaboration prompt DB (250b) may correspond to the collaboration prompt DB (250) of FIG. 2A. For example, a first electronic device (10a) and a second electronic device (10b) may be associated with a first project. In this case, the collaboration prompt DB (250a) of the first electronic device (10a) and the collaboration prompt DB (250b) of the second electronic device (10b) may each store the same prompt associated with the first project.

[0063] The personal prompt DB (260a) and the personal prompt DB (260b) may correspond to the personal prompt DB (260) of FIG. 2A. For example, a first electronic device (10a) and a second electronic device (10b) may be associated with a first project. The personal prompt DB (260a) of the first electronic device (10a) may store prompts input by the user of the first electronic device (10a). The personal prompt DB (260b) of the second electronic device (10b) may store prompts input by the user of the second electronic device (10b). Even when the first electronic device (10a) and the second electronic device (10b) are associated with the same first project, the personal prompt DB (260a) and the personal prompt DB (260b) may store different prompts. In one example, when a single user uses a first electronic device (10a) and a second electronic device (10b), the personal prompt DB (260a) and the personal prompt DB (260b) can store data that integrates the prompt input history of the user (e.g., data synchronized between the first electronic device (10a) and the second electronic device (10b). In one example, even when a single user uses a first electronic device (10a) and a second electronic device (10b), the personal prompt DB (260a) and the personal prompt DB (260b) can be managed separately by each of the first electronic device (10a) and the second electronic device (10b).

[0064] The AI ​​module (270a) and the AI ​​module (270b) may correspond to the AI ​​module (270) of FIG. 2A. The first electronic device (10a) and the second AI electronic device (10b) may store a first AI model associated with the first project. In one example, each of the first electronic device (10a) and the second electronic device (10b) may download the first AI model associated with the first project from an external server.

[0065] The account manager (230a) and the account manager (230b) may correspond to the account manager (230) of FIG. 2A. The project manager (220a) and the project manager (220b) may correspond to the project manager (220) of FIG. 2A. In the example of FIG. 2C, the project managers (220a, 220b) and the account managers (230a, 230b) are depicted as separate components from the application (210a, 210b). However, in one example, the project managers (220a, 220b) and the account managers (230a, 230b) may be implemented as part of the application (210a, 210b).

[0066] Figure 3 illustrates the structure of an AI model according to one embodiment.

[0067] Referring to FIG. 3, according to one embodiment, the AI ​​model described above with respect to FIGS. 2A to 2C may include at least one artificial neural network model (300). The artificial neural network model (300) may include a plurality of hidden layers (320). The hidden layers (320) may be positioned between an input layer (310) and an output layer (330), and may include at least one layer learned while transmitting data (x1, x2, x3, ..., xn) (n is an integer greater than or equal to 4) transmitted from the input layer (310) to the output layer (330). For example, the hidden layers (320) may include a first hidden layer (320-1), a second hidden layer (320-2), and third and Mth hidden layers (320-M) (M is an integer greater than or equal to 3). The number of hidden layers illustrated in FIG. 3 is an example, and embodiments of the present disclosure are not limited thereto. For example, the artificial neural network model (300) may include more hidden layers than the number of hidden layers illustrated in FIG. 3, or may include fewer hidden layers than the number of hidden layers illustrated in FIG. 3. In one example, the artificial neural network model (300) may correspond to a multi-layer perception (MLP) model. Each of the hidden layers (320) may include a plurality of nodes (N1, N2, ..., Nk). The weight values ​​of each node may be learned using input data.

[0068] For example, the electronic device (10) of FIG. 2A can input generated input data (e.g., input data generated from a prompt) as input data to an artificial neural network model (300). The input data is calculated by the artificial neural network model (300), and the artificial neural network model (300) can output output data (Y).

[0069] The artificial neural network model (300) is an example of an AI model, and embodiments of the present disclosure are not limited thereto. In the present disclosure, the term “AI model” may include a generative AI model. For example, the AI ​​model may include a large language model (LLM), a large multi-modal model (LMM), a large vision model (LVM), and / or a smaller LLM (sLLM).

[0070] LLM can refer to a language model based on an artificial neural network that has learned a large amount of text data through pre-training. LLMs can contain significantly more parameters (e.g., over 10 billion) than conventional language models. LLMs can utilize a transformer artificial neural network structure based on an attention mechanism.

[0071] The attention mechanism is a technology that helps AI models focus (attention) on important parts of input data. The attention mechanism predicts the extent to which a portion of time-series input data (e.g., input data such as voice or video, or input data from a neural network layer) contributes to the intermediate or final output of the neural network, and can predict output data based on the predicted contribution. Compared to recursive neural networks (RNNs), which process each element of a sequence sequentially, the attention mechanism can consider information dependencies across long time-series distances by controlling the degree of weight concentration (attention) within the context of the entire (or a portion) of the input data.

[0072] A transformer can be configured, for example, with an encoder-decoder structure. The encoder processes input data and outputs compressed information (e.g., a contextual representation), and the decoder processes the compressed information and outputs token-based data. Each encoder and decoder may include an independent attention network, and a cross-attention network connecting the encoder and decoder may be included.

[0073] For example, LLM training may involve pre-training and / or fine-tuning. Pre-training involves training the LLM to acquire general linguistic knowledge using large amounts of text data. For example, this may involve self-supervised learning, where the LLM predicts the next word based on the previous word sequence in the text string. Fine-tuning involves training the LLM to be suitable for a specific domain (e.g., chatbot, translation, summarization, Q&A) or task. The LLM may undergo additional supervised learning (or adaptive learning) based on the pre-trained model using a dataset tailored to the domain's purpose. The LLM can perform tasks with text inputs containing natural language, called prompts.

[0074] For example, fine-tuning can be omitted during LLM learning. The user can control the prompts provided to the LLM to enhance its performance on the desired task. Similar to in-context learning or zero-shot / few-shot learning, prompts can be supplemented with examples of the task and / or guidance for performing the task. Publicly available LLMs include BERT (Bidirectional Encoder Representations from Transformer) and GPT (generative pre-trained transformer).

[0075] In addition to text, LLM can also receive additional inputs, including visual information (including video). The visual information can be converted into text through separate preprocessing (e.g., image recognition, scene recognition) and included in the prompt to generate a response. Another example is a video encoder that converts the input image into text-aligned image embeddings. Using the text embeddings corresponding to the input text, a separately trained model (e.g., a large multimodal model) can generate a response.

[0076] In the present disclosure, the term "LLM" may refer to the language neural network model itself, but may also mean a model of an LLM-based application (e.g., chatbot, translation, summarization, text classification, sentence generation). For example, an LLM-based chatbot such as ChatGPT or an LLM-based translator may also be referred to as "LLM." The "LLM" may also include an inference engine using the LLM neural network model. For example, "inputting an input prompt into the LLM" may mean "inputting the input prompt into an inference engine based on the LLM." For example, "the output of the LLM for the input prompt" may mean the output information of the last neural network layer of the LLM (or the output information modified through additional processing) obtained when the input prompt is input into the LLM-based inference engine.

[0077] In one embodiment, the AI ​​models configured may differ depending on the project. For example, a first AI model may be configured for a first project, and a second AI model may be configured for a second project. If the current project uses the first AI model, the project manager (220, 220a, 220b) of FIGS. 2A to 2C may process user input (e.g., prompts) using the first AI model.

[0078] Hereinafter, various operations by the electronic device (10) of FIG. 2a may be described with reference to FIGS. 4 to 13. A person skilled in the art will understand that at least some of the operations of the electronic device (10) described below may be performed by the server device (20) of FIG. 2b, the first electronic device (10a) of FIG. 2c, or the second electronic device (10b) of FIG. 2c.

[0079] Figure 4 is a flowchart of a task performing method according to one embodiment.

[0080] Referring to FIGS. 2A and 4 , according to one embodiment, the electronic device (10) may generate a result based on user input. For example, the electronic device (10) may obtain user input requesting the performance of a task for a specific project.

[0081] The operations described below with respect to FIG. 4 may be referred to as operations of the electronic device (10) of FIG. 2A. According to one embodiment, operations 405 to 425 may be understood to be performed by the processor (120) of the electronic device (10). The order of the operations described below with respect to FIG. 4 is merely an example, and embodiments of the present disclosure are not limited thereto. For example, at least some of the operations may be performed differently from the order of FIG. 4, or may be performed substantially simultaneously with other operations of FIG. 4. At least some of the operations described below with respect to FIG. 4 may be omitted.

[0082] In operation 405, according to one embodiment, the electronic device (10) may obtain user input. For example, the electronic device (10) may obtain user input through the interface (180) or may obtain user input from an external electronic device using the communication circuit (190). For example, the user input may be an input requesting the performance of a task for a specified project.

[0083] In operation 410, the electronic device (10) may determine whether a task indicated by a user input is a task of a collaborative project. If the type of project associated with the task is a collaborative project, the electronic device (10) may determine that the indicated task is a task of the collaborative project. If the type of project associated with the task is a personal project, the electronic device (10) may determine that the indicated task is not a task of the collaborative project. For example, the electronic device (10) may identify the type of project using the project manager (220). If the workspace belongs to a collaborative project, the electronic device (10) may determine that the indicated task is a task of the collaborative project. In one example, if the task is designated as a task of the collaborative project by the user input, the electronic device (10) may determine that the indicated task is a task of the collaborative project.

[0084] If the instructed task is not a task of a collaborative project (e.g., operation 410-NO), in operation 415, according to one embodiment, the electronic device (10) may generate a user input-based prompt. In this case, the electronic device (10) may generate a prompt based solely on user input without using a separate common policy. For example, the electronic device (10) may generate a user input-based prompt using the prompt manager (240). The electronic device (10) may store the generated user-based prompt in a personal prompt DB (260).

[0085] If the instructed task is a task of a collaboration project (e.g., operation 410-YES), in operation 420, according to one embodiment, the electronic device (10) may generate a prompt (e.g., a modified prompt) based on user input and a common policy. The electronic device (10) may obtain a common policy (e.g., a common prompt) of a collaboration project associated with the task from the memory (130) or an external server. For example, the electronic device (10) may obtain the common policy from the collaboration prompt DB (250). The electronic device (10) may generate a modified prompt by, for example, modifying a user input-based prompt based on the common policy. For example, the electronic device (10) may generate a modified prompt by adding a common prompt based on the common policy to a user input-based prompt.

[0086] In one example, there may not be a common policy established for a collaborative project. In this case, the electronic device (10) may generate a user input-based prompt.

[0087] In operation 425, according to one embodiment, the electronic device (10) can generate a prompt-based result. The electronic device (10) can generate the result by inputting the user input-based prompt generated according to operation 415 or the modified prompt generated according to operation 420 into an AI model. For example, the electronic device (10) can generate the result using an AI model stored in the electronic device (10). In the case of a collaborative project, since the prompt is generated using a common policy, a result that satisfies both the user input request and the common policy can be generated.

[0088] In one example, the electronic device (10) may provide a result. For example, the electronic device (10) may provide the result to the user using an interface (180) or a display (160).

[0089] Hereinafter, examples of results according to an embodiment of the present disclosure may be described with reference to FIGS. 5 to 9.

[0090] Figure 5 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0091] Referring to FIGS. 2A and 5, the electronic device (10) may generate a result based on a common policy. For example, the first presentation (510) may be a result of a second user (e.g., a user of the second electronic device (10b) of FIG. 1) generated based on the common policy. The common policy applied to the first presentation (510) may include, for example, document structure, writing style, and / or background formatting. For example, document structure may refer to the structure of text within the document (e.g., font size, font type, and / or position). Writing style may include the narrative style of text within the document (e.g., narrative, keyword summary, parentheses, or unparentheses). Writing style may also include the nuance of the text (e.g., politely, humorously, and / or businessly). Background formatting may include a background color, a background image, and / or a background effect. The first presentation (510) may include, for example, results generated based on document structure and style according to a common policy.

[0092] The second presentation (520) may be a result generated based on a user input-based prompt to which a common policy is not applied. Since the common policy is not applied, the second presentation (520) may have a different tone and code than the first presentation (510). For example, the position and font size of the title (521) of the second presentation (520) are different from those of the first presentation (510). The content (523) of the second presentation (520) is written in a descriptive manner, which is different from the summary and list-type description of the first presentation (510). The content (523) of the second presentation (520) has keywords (ABC, DEF, GHI) positioned in the middle of sentences, which is different in style from the first presentation (510) in which keywords are placed at the front in a summary manner.

[0093] The third presentation (530) may be a result generated based on the input-based prompts and common policy of the second presentation (520). Due to the application of the common policy, the size and position of the title (531) may be identical to those of the first presentation (510). Due to the application of the common policy, the content (533) is changed to a summary description in list format. Therefore, by applying the common policy, a common tone and code can be maintained between the first presentation (510) and the third presentation (530).

[0094] In one example, the electronic device (10) may provide a result using a personal input-based prompt and a result using a modified prompt (e.g., a personal input-based prompt with a common policy applied). For example, the electronic device (10) may provide both a second presentation (520) and a third presentation (530). By providing both results together, the electronic device (10) may enable the user to intuitively recognize the variation of the result based on the common rule.

[0095] In one example, the electronic device (10) may provide an example of a case where a personal project is integrated into a collaborative project. By providing a second presentation (520) and a third presentation (530) together, the electronic device (10) may provide a preview of what the second presentation (520) will look like when it has been modified by a common policy.

[0096] Figure 6 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0097] Referring to FIGS. 2A and 6 , the electronic device (10) may generate results based on a common policy. For example, the first image (610) and the second image (620) may be results generated based on a common policy. In one example, the common policy may include a background image, a font style, a font size, and / or a common object.

[0098] For example, images related to a collaborative project involving safety training may be generated. To facilitate the collaborative project, a first user and a second user may create images using an AI model. Regarding the collaborative project, the first user may have administrator privileges. The first user may set common policies to be used in the collaborative project. For example, Table 1 may represent common policies set by the first user.

[0099] Item Content Scope Safety Campaign Project Application Target 1st User, 2nd User Application Content Graphic Font Minimum Size 15 Background Image: Yeongtong-gu Cell Phone Image: Galaxy

[0100] After setting a common policy, a first user can input an input to a first electronic device (e.g., the first electronic device (10a) of FIG. 1) to generate a result. For example, the input may be, "Draw a woman using a cell phone while walking and draw 'danger' in English." The first electronic device can generate a first image (610) based on the user input-based prompt and the common policy. The first image (610) may include, for example, graphical text (611) titled "danger" set by the common policy.

[0101] In connection with a collaborative project, a second user may input an input for generating a result into a second electronic device (e.g., the second electronic device (10b) of FIG. 1 ). For example, the input may be, “Draw a picture of someone using a cell phone while driving and write ‘danger’ in English.” In this case, the second electronic device may generate a second image (620) based on a user input-based prompt and a common policy. The second image (620) may include, for example, graphical text (621) stating “danger” set by the common policy. The first image (610) and the second image (620) may include a common object (e.g., a cell phone) set by a common rule.

[0102] Figure 7 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0103] Referring to FIGS. 2A and 7, the electronic device (10) may generate results based on a common policy. For example, the first graph (710) and the second graph (720) may be results generated based on a common policy. In one example, the common policy may include a background image, a font style, a font size, a diagram type, and / or a layer style.

[0104] For example, graphs can be generated for a collaborative project related to the current state of the electric vehicle market. To facilitate the collaborative project, the first and second users can use AI models to generate graphs. Regarding the collaborative project, the graph type, colors used, font size, font type, alignment direction, and / or words used can be configured.

[0105] A first user may input annual vehicle sales information into a first electronic device (e.g., the first electronic device (10a) of FIG. 1 ) to generate a first graph (710). The first electronic device may generate the first graph (710) based on common policies and user input-based prompts.

[0106] A second user may input vehicle sales information by manufacturer into a second electronic device (e.g., the second electronic device (10b) of FIG. 1) to generate a second graph (720). The second electronic device may generate the second graph (720) based on common policies and user input-based prompts.

[0107] The first graph (710) and the second graph (720) can describe data using text with a font and font size set by common rules. The first graph (710) and the second graph (720) can be created using a graph type set by common rules.

[0108] Figure 8 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0109] Referring to FIGS. 2A and 8 , the electronic device (10) may generate results based on a common policy. For example, the first image (810) and the second graph (820) may be results generated based on a common policy. In one example, the common policy may include a painting style, feature points, and / or non-editable objects. In the example of FIG. 8 , the common policy may be "Still Life in the Style of David Hockney."

[0110] For example, the first image (810) may be an image generated by a first user. The first user may generate the first image (810) using an AI model. The first electronic device (e.g., the first electronic device (10a) of FIG. 1 ) may generate the first image (810) based on a user input-based prompt and a common policy.

[0111] According to one embodiment, the collaborative system of the present disclosure can support editing of another user's work. A second user can make modifications to a first image (810). For example, the second user can make modifications to the first image (810) using a second electronic device (e.g., the second electronic device (10b) of FIG. 1 ). The second user can input an input to the second electronic device to include more objects in the first image (810). The second electronic device can generate a second image (820) based on the first image (810), the second user's input, and a common policy. Due to the common policy, the second image (820) can be generated in the same drawing style as the first image (810).

[0112] Figure 9 illustrates examples of results according to a collaborative project management method according to one embodiment.

[0113] Referring to FIGS. 2A and 9, the electronic device (10) can generate results based on a common policy. For example, the common policy may have a hierarchical structure. A common policy at a higher level may be applied to a wider range of users than a common policy at a lower level. For example, a common policy at a lower level may be applied only to some users in a collaborative project or when certain conditions are met.

[0114] In the example of FIG. 9, the upper-layer common policy may include “panda” as a common object. The lower-layer common policy may include two-dimensional images and three-dimensional images. When a first user creates an image for a first platform, “panda” and a “two-dimensional image” set for the first platform may be applied as common policies. For example, based on an input from the first user, the electronic device (10) may create a first image (910) including a two-dimensional panda image. When a second user creates an image for a second platform, “panda” and a “three-dimensional image” set for the second platform may be applied as common policies. For example, based on an input from the second user, the electronic device (10) may create a second image (920) including a three-dimensional panda image.

[0115] The common policy illustrated in the example of Figure 9 is an example, and embodiments of the present disclosure are not limited thereto. For example, a higher-level common policy may include text corresponding to the common policy, and a lower-level common policy may include translations for each country corresponding to the common policy.

[0116] Figure 10 illustrates an example of a user interface (UI) for setting common policies.

[0117] Referring to FIGS. 2A and 10 , according to an embodiment, an electronic device (10) may provide a UI for setting a common policy. For example, the UI may include a first image (1010). The electronic device (10) may receive an input for setting a first area (1020) of the first image (1010). The electronic device (10) may extract a common policy from the first area (1020). For example, the electronic device (10) may extract the common area based on image analysis of the first area (1020).

[0118] In the example of FIG. 10, the electronic device (10) may extract the material, color, shape of the sole, and / or shape of the shoe as features from the first region (1020). The electronic device (10) may establish a common policy based on the extracted features. For example, the electronic device (10) may provide a list of extracted features. Based on an input to the list, the electronic device (10) may identify features to be used as a common policy among the extracted features. The electronic device (10) may store the identified features as a common policy (e.g., in the collaboration prompt DB (250)).

[0119] With respect to FIG. 10, setting of a common policy based on an image is described, but a person skilled in the art will understand that a common policy can be set based on text input or voice input.

[0120] Figure 11 is a flowchart of a prompt processing method according to one embodiment.

[0121] Referring to FIGS. 2A and 11 , according to one embodiment, the electronic device (10) may provide a notification of a conflict between a user input-based prompt and a common policy.

[0122] The operations described below with reference to FIG. 11 may be referred to as operations of the electronic device (10) of FIG. 2A. According to one embodiment, operations 1105 to 1120 may be understood to be performed by the processor (120) of the electronic device (10). The order of the operations described below with reference to FIG. 1 is merely an example, and embodiments of the present disclosure are not limited thereto. For example, at least some of the operations may be executed differently from the order of FIG. 11, or may be executed substantially simultaneously with other operations of FIG. 11. At least some of the operations described below with reference to FIG. 11 may be omitted.

[0123] In operation 1105, according to one embodiment, the electronic device (10) may obtain user input. For example, the electronic device (10) may obtain user input according to operation 405 of FIG. 4.

[0124] In operation 1110, according to one embodiment, the electronic device (10) may determine whether a conflict exists between a user input-based prompt and a common policy. For example, the electronic device (10) may determine that a conflict exists if the user input-based prompt contradicts the common policy, requires the addition of content prohibited by the common policy, and / or requires a style different from the common policy.

[0125] For example, the user input may be "Draw a red apple." The common policy, on the other hand, may be "Draw the apple green." In this case, the electronic device (10) may determine that a conflict exists between the user input-based prompt and the common policy.

[0126] If no conflict exists (e.g., operation 1110-NO), at operation 1115, the electronic device (10) may generate a prompt based on user input and common policies. For example, the electronic device (10) may generate a prompt according to operation 420 of FIG. 4.

[0127] If a conflict exists (e.g., operation 1110-YES), in operation 1120, the electronic device (10) may provide a conflict notification. For example, the electronic device (10) may provide a notification indicating the existence of a conflict through the display (160). In one example, the conflict notification may include permission information for requesting modification of a common policy. For example, the permission information may include information about a user who has permission to modify the common policy. The permission information may include a UI for requesting an elevation of permission.

[0128] In one example, the electronic device (10) may provide a notification including a preview image. As described above with respect to FIG. 5, the electronic device (10) may provide a user input-based result and a result to which a common policy is applied as a preview image.

[0129] In one example, the electronic device (10) may provide a notification containing information about a conflicting common policy.

[0130] In one example, if the user of the electronic device (10) has the authority to modify the common policy, the notification may include a UI for modifying the common policy.

[0131] Figure 12 illustrates an example of a UI for showing results according to a common policy.

[0132] Referring to FIGS. 2A and 12 , according to one embodiment, the electronic device (10) may provide both results according to a common policy and results to which the common policy is not applied. When providing a notification according to operation 1120 of FIG. 11 , the electronic device (10) may provide both results according to a common policy and results to which the common policy is not applied.

[0133] For example, according to the example of FIG. 10, a shoe may be set as a common object of a common policy. If the user's input is "Draw a man sitting on a sofa barefoot," the electronic device (10) can identify a conflict between the common policy and the user input-based prompt.

[0134] Based on the identification of the collision, the electronic device (10) may display a first image (1210) and a second image (1220). The first image (1210) may be an image generated using a user input-based prompt. In the first image (1210), the foot (1211) is not wearing shoes.

[0135] The electronic device (10) can generate a modified prompt by modifying a user input-based prompt using a common policy. The second image (1220) may be an image generated using the modified prompt. In the second image (1220), a shoe is worn on a foot (1221).

[0136] A user can visually recognize a conflict with a common policy by comparing the first image (1210) and the second image (1220).

[0137] FIG. 13 illustrates a flowchart of a method for collaborative project management using generative artificial intelligence according to one embodiment.

[0138] The operations described below with reference to FIG. 13 may be referred to as operations of the electronic device (10) of FIG. 2A. According to one embodiment, operations 1305 to 1320 may be understood to be performed by the processor (120) of the electronic device (10). The order of the operations described below with reference to FIG. 13 is merely an example, and embodiments of the present disclosure are not limited thereto. For example, at least some of the operations may be executed differently from the order of FIG. 13, or may be executed substantially simultaneously with other operations of FIG. 13. At least some of the operations described below with reference to FIG. 13 may be omitted.

[0139] In operation 1305, according to one embodiment, the electronic device (10) may obtain an input prompt for the first project. The electronic device (10) may obtain input from an external electronic device via the interface (180) or by using the communication circuit (190). The electronic device (10) may obtain the input prompt from the input. In one example, if the input is in the form of an input prompt, the electronic device (10) may use the input as an input prompt. In one example, the electronic device (10) may generate an input prompt from the input through analysis of the input (e.g., natural language understanding and / or image recognition). The input prompt may correspond to the user input-based prompt described above with respect to FIG. 4.

[0140] In operation 1310, according to one embodiment, the electronic device (10) may identify a common prompt set for the first project. The electronic device (10) may identify the common prompt (e.g., common policy) based on identification information and / or user information (e.g., account information) of the first project. For example, the electronic device (10) may identify the common prompt set for the first project from the collaboration prompt DB (250). For example, the electronic device (10) may identify an upper-level common prompt using information of the first project, and may identify a lower-level common prompt based on user information. For example, the common prompt may include at least one of a font type, a font size, a drawing style, a common object, or a text arrangement associated with the result data.

[0141] In one example, the electronic device (10) may generate a common prompt based on a designation for a portion of an image. The electronic device (10) may display the image using the display (160). The electronic device (10) may receive an input designating a portion of the image. The electronic device (10) may extract features for the designated area and generate a prompt based on the extracted features. The electronic device (10) may add the generated prompt to the common prompt. For example, the electronic device (10) may generate the common prompt using the method described above with respect to FIG. 10 .

[0142] According to one embodiment, the electronic device (10) may provide information about at least a portion of the input prompt that contradicts the common prompt, if at least a portion of the input prompt contradicts the common prompt. For example, the electronic device (10) may provide information about at least a portion of the contradictory input prompt by providing a notification according to operation 1120 of FIG. 11.

[0143] For example, a first project may be associated with multiple accounts. At least some of the multiple accounts may have editing privileges for a common prompt. If at least some of the input prompts contradict the common prompts, the electronic device (10) may transmit a modification request requesting modification of the common prompts. The electronic device (10) may transmit the modification request to an account with editing privileges using the communication circuit (190).

[0144] In operation 1315, according to one embodiment, the electronic device (10) can generate a modified prompt using a common prompt and an input prompt. The electronic device (10) can generate the modified prompt by modifying the input prompt using the common prompt. The electronic device (10) can generate the modified prompt by merging or combining the input prompt and the common prompt.

[0145] In operation 1320, according to one embodiment, the electronic device (10) can obtain result data by inputting the modified prompt into at least one generative AI model set for the first project.

[0146] If a common prompt does not exist, operation 1315 may be omitted. For example, the electronic device (10) may obtain result data based on the input prompt in operation 1320.

[0147] In one example, the electronic device (10) may generate comparison data by inputting an input prompt to at least one generative AI model. The electronic device (10) may display the result data and the comparison data using the display (160). For example, the comparison data may be referenced as a result to which the common prompt is not applied.

[0148] FIG. 14 is a block diagram of an exemplary electronic device (1400) capable of performing the operations described in this document.

[0149] Referring to FIG. 14, the electronic device (1400) may be one of various forms of electronic devices, such as a notebook (1490), smartphones (1491) having various form factors (e.g., a bar-type smartphone (1491-1), a foldable-type smartphone (1491-2), or a sliderable (or rollable) type smartphone (1491-3)), a tablet (1492), a cellular phone (not shown), and other similar computing devices (not shown). The components, their relationships, and their functions illustrated in FIG. 14 are exemplary only and do not limit the implementations described or claimed in this document. The electronic device (1400) may be referred to as a mobile device, a user device, a multi-function device, a portable device, or a server.

[0150] The electronic device (1400) may include components including at least one processor (1410) (hereinafter referred to as processor (1410)), at least one memory (1420) (hereinafter referred to as memory (1420)), at least one display (1440) (hereinafter referred to as display (1440)), at least one image sensor (1450) (hereinafter referred to as image sensor (1450)), at least one communication circuit (1460) (hereinafter referred to as communication circuit (1460)), and / or at least one sensor (1470) (hereinafter referred to as sensor (1470)). The above components are merely exemplary. For example, the electronic device (1400) may include other components (e.g., power management integrated circuitry (PMIC), audio processing circuitry, an antenna, a rechargeable battery, or an input / output interface). For example, some components may be omitted from the electronic device (1400). For example, several components can be combined into one component.

[0151] The processor (1410) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing. The processor (1410) may include at least one electrical circuit and may individually or collectively perform distributed processing of instructions (or programs, data, etc.) stored in the memory (1420). The processor (1410) may include a processor assembly including one or more processing circuits. The processor (1410) may include any processing circuit operative to control the performance and operations of one or more components of the electronic device (1400) (e.g., the memory (1420), the display (1440), the image sensor (1450), the communication circuit (1460), and / or the sensor (1470)). For example, the processor (1410) (e.g., an application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or chipset). For example, the processor (1410) may be implemented as multiple cores (or at least one core circuit), multiple chips, or multiple chipsets. For example, the processor (1410) may include one or more processing circuits. For example, the processor (1410) may include one or more processing circuits configured to individually and / or collectively perform various functions of the present disclosure. As a non-limiting example, at least a portion of the processor (1410) may be included in a first chip of the electronic device (1400), and at least another portion of the processor (1410) may be included in a second chip of the electronic device (1400) that is different from the first chip of the electronic device (1400).

[0152] For example, the processor (1410) may include a central processing unit (CPU) (1411), a graphics processing unit (GPU) (1412), a neural processing unit (NPU) (1413), an image signal processor (ISP) (1414), a display controller (1415), a memory controller (1416), a storage controller (1417), a communication processor (CP) (1418), and / or a sensor interface (1419). These components of the processor (1410) are merely exemplary. For example, the processor (1410) may further include other components. For example, some components of the processor (1410) may be omitted from the processor (1410). For example, some components of the processor (1410) may be included as separate components of the electronic device (1400) outside the processor (1410). For example, some components of the processor (1410) (e.g., memory controller (1416)) may be included within other components (e.g., at least a portion of memory (1420), an interface (e.g., available for connection to at least one component of the electronic device (100)), a display (1440) and / or an image sensor (1450)).

[0153] The processor (1410) may cause other components of the electronic device (1400) to perform various operations by executing instructions stored in the memory (1420). The CPU (1411) (or central processing circuit) may be configured to control components of the processor (1410) based on the execution of instructions stored in the memory (1420) (e.g., volatile memory (1421) and / or non-volatile memory (1422)). The GPU (1412) (or graphics processing circuit) may be configured to perform parallel operations (e.g., rendering). The NPU (1413) (or neural processing circuit, or artificial intelligence (AI) chip) may be configured to perform operations for an artificial intelligence model (e.g., convolution computation). The ISP (1414) (or image signal processing circuit) may be configured to process a raw image acquired through the image sensor (1450) into a format suitable for a component within the electronic device (1400) or a component of the processor (1410). The display controller (1415) (or display control circuit, or display processing unit (DPU)) may be configured to process an image acquired from the CPU (1411), the GPU (1412), the ISP (1414), or the memory (1420) (e.g., the volatile memory (1421)) into a format suitable for the display (1440). The memory controller (1416) (or memory control circuit) may be configured to control reading data from the volatile memory (1421) and writing data to the volatile memory (1421). The storage controller (1417) (or storage control circuit) may be configured to control reading data from and writing data to the nonvolatile memory (1422).The CP (1418) (communication processing circuit) may be configured to process data obtained from a component of the processor (1410) into a format suitable for transmitting to another electronic device via the communication circuit (1460), or to process data obtained from another electronic device via the communication circuit (1460) into a format suitable for processing by the component of the processor (1410). For example, the communication circuit (1460) may include one or more communication circuits. The sensor interface (1419) (or sensing data processing circuit, sensor hub) may be configured to process data on the state of the electronic device (1400) and / or the state of the surroundings of the electronic device (1400), obtained via the sensor (1470), into a format suitable for the component of the processor (1410).

[0154] The memory (1420) may include one or more storage media (or one or more storage devices). For example, the memory (1420) may include a memory assembly including one or more storage media. For example, the one or more storage media may include permanent memory (e.g., non-volatile memory (1422)) such as a hard drive, flash memory, read-only memory (ROM), semi-permanent memory (e.g., volatile memory (1421)) such as random access memory (RAM), any other suitable type of storage (or storage assembly), or any combination thereof. The memory (1420) may include cache memory, which is one or more different types of memory used to temporarily store data for a function or feature of the electronic device (1400). As a non-limiting example, the cache memory may be included within the processor (1410). The memory (1420) may be fixedly embedded within the electronic device (1400) or incorporated into one or more suitable types of components (e.g., a subscriber identity module (SIM) card and / or a secure digital (SD) card) that may be repeatedly inserted into and removed from the electronic device (1400).

[0155] For example, the memory (1420) may store one or more software applications, such as an operating system (or system) software application, a firmware software application, a driver software application, a plug-in (e.g., add-in, add-on, and / or applet) software application, and / or any other suitable software applications. For example, the one or more software applications may include instructions executable by the processor (1410). For example, the memory (1420) may store instructions callable by an application programming interface (API). For example, the memory (1420) may store instructions within a library.

Claims

1. In electronic devices, display; memory; and comprising the display and at least one processor communicatively connected to the display; The memory, when executed individually or collectively by the at least one processor, causes the electronic device to: Get an input prompt for the first project, Identify the common prompts established for the above first project, Create a modified prompt using the above common prompt and the above input prompt, An electronic device storing instructions for obtaining result data by inputting the modified prompt into at least one generative AI model set for the first project.

2. In paragraph 1, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: An electronic device that generates the modified prompt by merging the input prompt and the common prompt.

3. In paragraph 1, An electronic device wherein the common prompt includes at least one of a font type, a font size, a painting style, a common object, or a text arrangement associated with the result data.

4. In paragraph 1, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: An electronic device configured to provide information about at least a portion of the input prompt that contradicts the common prompt, if at least a portion of the input prompt contradicts the common prompt.

5. In paragraph 4, An electronic device, wherein at least some of the plurality of accounts associated with the first project have editing rights to the common prompt.

6. In paragraph 5, Further including communication circuits, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: An electronic device that transmits a modification request using the communication circuit to request modification of the common prompt to an account having editing authority for the common prompt, if at least a part of the input prompt contradicts the common prompt.

7. In paragraph 1, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: Display an image on the above display, An electronic device that generates said common prompt based on a designation for a certain area of ​​said image.

8. In paragraph 7, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: Extract feature points for the above-mentioned area, Generate a prompt based on the extracted feature points, An electronic device that adds the generated prompt to the common prompt.

9. In paragraph 1, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: By inputting the above input prompt into the at least one generative AI model, comparison data to which the common prompt is not applied is generated, An electronic device that displays the result data and the comparison data through the display.

10. In paragraph 1, The above instructions, when individually or in combination executed by the at least one processor, cause the electronic device to: Acquire input for the above first project, An electronic device that generates the input prompt based at least on natural language understanding or image recognition of the acquired input.

11. A method for managing a collaborative project of electronic devices, Action to obtain input prompt for project 1; An action to identify a common prompt set for the above first project; An operation of generating a modified prompt using the common prompt and the input prompt; and A method comprising the action of obtaining result data by inputting the modified prompt into at least one generative AI model set for the first project.

12. In paragraph 11, A method further comprising the action of generating the modified prompt by merging the input prompt and the common prompt.

13. In paragraph 11, A method wherein the common prompt includes at least one of a font type, a font size, a painting style, a common object, or a text arrangement associated with the result data.

14. In paragraph 11, A method further comprising the action of providing information about at least a portion of the input prompt that contradicts the common prompt, if at least a portion of the input prompt contradicts the common prompt.

15. In paragraph 14, A method wherein at least some of the plurality of accounts associated with the first project have editing rights to the common prompt.

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