Electronic device and method for providing content

Abstract

An electronic device of the present disclosure may comprise: a display; a communication circuit; at least one processor; and a memory for storing instructions, wherein the instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to: acquire communication information; identify an external electronic device around the electronic device or geographical information on the basis of the communication information; identify personal information related to the identified external electronic device; generate content on the basis of a user command for generating the content and the personal information; and provide the generated content.

Description

Method of providing electronic devices and content

[0001] The present disclosure relates to an electronic device and a method for providing the contents of the electronic device.

[0002] Various portable electronic devices such as smartphones, tablet PCs, portable multimedia players (PMPs), personal digital assistants (PDAs), laptop personal computers (Laptop PCs), and wearable devices such as wristwatches and head-mounted displays (HMDs) can provide various content.

[0003] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure.

[0004] The electronic device of the present disclosure may include a display.

[0005] The electronic device of the present disclosure may include a communication circuit.

[0006] The electronic device of the present disclosure may include at least one processor.

[0007] The electronic device of the present disclosure may include a memory for storing instructions.

[0008] When the instructions of the present disclosure are executed individually or collectively by at least one processor, the electronic device may obtain communication information.

[0009] When the instructions of the present disclosure are executed individually or collectively by the at least one processor, the electronic device may be able to identify external electronic devices or geographical information around the electronic device based on the communication information.

[0010] When the instructions of the present disclosure are executed individually or collectively by the at least one processor, the electronic device may be able to identify personal information associated with the identified external electronic device.

[0011] When the instructions of the present disclosure are executed individually or collectively by the at least one processor, the electronic device may generate content based on user commands for content generation and the personal information.

[0012] When the instructions of the present disclosure are executed individually or collectively by at least one processor, the electronic device may provide the generated content.

[0013] The method for providing content of an electronic device of the present disclosure may include an operation of acquiring communication information.

[0014] The method for providing content of an electronic device according to the present disclosure may include an operation of identifying an external electronic device or location information around the electronic device based on the communication information.

[0015] The method for providing content of an electronic device of the present disclosure may include an operation of verifying personal information related to the identified external electronic device.

[0016] The method for providing content of an electronic device of the present disclosure may include a user command for creating content and an operation to create content based on the geographical information.

[0017] The method for providing content of an electronic device of the present disclosure may include the operation of providing the generated content.

[0018] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0019] FIG. 1 is a block diagram of an exemplary electronic device capable of performing the operations described in the present disclosure.

[0020] FIG. 2 is a drawing showing a computer program stored in the memory of an electronic device according to one embodiment of the present disclosure.

[0021] FIG. 3 is a flowchart illustrating a method for providing content according to an embodiment of the present invention.

[0022] FIG. 4 is a flowchart illustrating a method for providing content according to an embodiment of the present invention.

[0023] FIG. 5 is a diagram illustrating a method of generating a profile using an electronic device according to one embodiment of the present disclosure.

[0024] FIG. 6 is a diagram illustrating a method of an electronic device generating content according to one embodiment of the present disclosure.

[0025] FIG. 7 is a diagram illustrating the operation of generating personal information about a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0026] FIG. 8 is a diagram illustrating the operation of providing content based on personal information of a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0027] FIG. 9 is a diagram illustrating the operation of providing content based on personal information of a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0028] FIG. 10 is a diagram illustrating the operation of generating content based on personal information of a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0029] FIG. 11 is a diagram illustrating the operation of generating content based on personal information of a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0030] FIG. 12 is a diagram illustrating the operation of recreating content based on personal information of a user of an external electronic device in an electronic device according to one embodiment of the present disclosure.

[0031] FIG. 13 is a diagram showing the notification operation of an electronic device when a person nearby approaches, according to one embodiment of the present disclosure.

[0032] FIG. 14 is a diagram illustrating the operation of an electronic device according to one embodiment of the present disclosure providing content based on geographical information.

[0033] FIG. 15 is a diagram showing the operation of an electronic device according to one embodiment of the present disclosure confirming geographical information from an SSID.

[0034] FIG. 16 is a diagram illustrating the operation of an electronic device according to one embodiment of the present disclosure changing the exposure of content based on geographical information.

[0035] FIG. 17 is a diagram showing the operation of displaying content when an electronic device according to an embodiment of the present disclosure is a wearable device.

[0036] FIG. 18 is a drawing illustrating a content provision operation when an electronic device according to one embodiment of the present disclosure includes a foldable or multi-foldable housing.

[0037] FIG. 19 is a diagram illustrating a method for a user of an electronic device and a user of an external electronic device to identify people nearby and share personal information using the same cloud server (e.g., Samsung Cloud Server) according to one embodiment of the present disclosure.

[0038] FIG. 20 is a block diagram of an electronic device in a network environment according to one embodiment.

[0039] FIG. 21 is a block diagram of a generative artificial intelligence (AI) system according to one embodiment.

[0040] FIG. 22 is a block diagram of an AI Framework according to one embodiment.

[0041] Conventional electronic devices can provide different content depending on the user. For example, conventional electronic devices offer features such as multi-profiles, allowing them to provide different lists of recommended content for each profile once the user selects one. Conventional electronic devices provided users with methods to automatically generate or organize content based on the user or owner. Consequently, owners of conventional electronic devices faced the difficulty of having to regenerate or organize content through user input in order to enjoy content with those around them.

[0042] The electronic device and the method for providing content of the present invention can generate or display content based on personal information (e.g., user profile) and geographical information of users of external electronic devices as well as users of the electronic device.

[0043] The method of providing electronic devices and content of the present invention can generate and analyze personal information including the preferences and non-preferences of users of personal external electronic devices.

[0044] The method of providing electronic devices and content according to the present invention can generate and analyze personal information including the preferences and non-preferences of a user of a personal external electronic device to generate or display content.

[0045] The electronic device and the method of providing content according to the present invention can provide various content depending on the relationship with the user as well as the electronic device user by generating or displaying necessary content according to situations such as places and surrounding people.

[0046] The electronic device and content-providing method of the invention can provide a personalized experience to the user and filter out unnecessary information by generating or displaying necessary content according to the situation, such as the location and surrounding people.

[0047] The electronic device and the method of providing content according to the present invention can protect the privacy of the electronic device user by generating or displaying necessary content depending on the situation, such as the location and surrounding people.

[0048] FIG. 1 is a block diagram of an exemplary electronic device (100) capable of performing the operations described in the present disclosure.

[0049] Referring to FIG. 1, the electronic device (100) may be one of various forms of electronic devices, such as a notebook (190), smartphones (191) having various form factors (e.g., a bar-type smartphone (191-1), a foldable-type smartphone (191-2), or a sliderable (or rollable)-type smartphone (191-3)), a tablet (192), a cellular phone (not shown), and other similar computing devices (not shown). The components, their relationships, and their functions illustrated in FIG. 1 are illustrative only and are not intended to limit the implementations described or claimed in this disclosure. The electronic device (100) may be referred to as a mobile device, a user device, a multifunction device, a portable device, or a server.

[0050] The electronic device (100) may include components comprising at least one processor (110) (hereinafter referred to as processor (110)), at least one memory (120) (hereinafter referred to as memory (120)), at least one display (140) (hereinafter referred to as display (140)), at least one image sensor (150) (hereinafter referred to as image sensor (150)), at least one communication circuit (160) (hereinafter referred to as communication circuit (160)), and / or at least one sensor (170) (hereinafter referred to as sensor (170)). The components are merely exemplary. For example, the electronic device (100) may include other components (e.g., power management integrated circuitry (PMIC), audio processing circuit, antenna, rechargeable battery, or input / output interface). For example, some components may be omitted from the electronic device (100). For example, some components may be integrated into a single component.

[0051] The processor (110) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing operations. The processor (110) may include at least one electrical circuit and may process instructions (or programs, data, etc.) stored in memory (120) individually or collectively in a distributed manner. The processor (110) may include a processor assembly comprising one or more processing circuits. The processor (110) may include any processing circuit that is operative to control the performance and operations of one or more components of the electronic device (100) (e.g., memory (120), display (140), image sensor (150), communication circuit (160), and / or sensor (170)). For example, the processor (110) (e.g., application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or chipset). For example, the processor (110) may be implemented with a plurality of cores (or at least one core circuit), a plurality of chips, or a plurality of chipsets. For example, the processor (110) may include one or more processing circuits. For example, the processor (110) may include one or more processing circuits configured to perform the various functions of the present disclosure individually and / or collectively. As an example without limitation, at least a portion of the processor (110) may be included in a first chip of the electronic device (100), and at least another portion of the processor (110) may be included in a second chip of the electronic device (100) different from the first chip of the electronic device (100).

[0052] For example, the processor (110) may include a central processing unit (111), a graphics processing unit (112), a neural processing unit (113), an image signal processor (114), a display controller (115), a memory controller (116), a storage controller (117), a communication processor (118), and / or a sensor interface (119). These components of the processor (110) are merely exemplary. For example, the processor (110) may include other components. For example, some components of the processor (110) may be omitted from the processor (110). For example, some components of the processor (110) may be included as separate components of the electronic device (100) outside of the processor (110). For example, some components of the processor (110) (e.g., memory controller (116)) may be included in other components (e.g., at least part of memory (120), an interface (e.g. available for connection to at least one component of the electronic device (100)), a display (140) and / or an image sensor (150)).

[0053] The processor (110) may cause other components of the electronic device (100) to perform various operations by executing instructions stored in memory (120). The CPU (111) (or central processing circuit) may be configured to control the components of the processor (110) based on the execution of instructions stored in memory (120) (e.g., volatile memory (121) and / or non-volatile memory (122)). The GPU (112) (or graphics processing circuit) may be configured to execute parallel operations (e.g., rendering). The NPU (113) (or neural processing circuit, or AI (artificial intelligence) chip) may be configured to execute operations for an artificial intelligence model (e.g., convolution computation). An ISP (114) (or image signal processing circuit) may be configured to process a raw image acquired through an image sensor (150) into a format suitable for a component within the electronic device (100) or a component of the processor (110). A display controller (115) (or display control circuit, or DPU (display processing unit)) may be configured to process an image acquired from a CPU (111), GPU (112), ISP (114), or memory (120) (e.g., volatile memory (121)) into a format suitable for a display (140). A memory controller (116) (or memory control circuit) may be configured to control reading data from the volatile memory (121) and writing data to the volatile memory (121). A storage controller (117) (or storage control circuit) may be configured to control reading data from the non-volatile memory (122) and writing data to the non-volatile memory (122).The CP (118) (communication processing circuit) may be configured to process data obtained from a component of the processor (110) into a format suitable for transmitting to another electronic device via the communication circuit (160), or to process data obtained from another electronic device via the communication circuit (160) into a format suitable for processing by the component of the processor (110). For example, the communication circuit (160) may include one or more communication circuits. The sensor interface (119) (or sensing data processing circuit, sensor hub) may be configured to process data regarding the state of the electronic device (100) and / or the state around the electronic device (100), obtained through the sensor (170), into a format suitable for the component of the processor (110).

[0054] Memory (120) may include one or more storage media (or one or more storage devices). For example, memory (120) may include a memory assembly comprising one or more storage media. For example, the one or more storage media may include a hard drive, a permanent memory such as flash memory, read-only memory (ROM) (e.g., non-volatile memory (122)), a semi-permanent memory such as random access memory (RAM) (e.g., volatile memory (121)), any other suitable type of storage (or storage assembly), or any combination thereof. Memory (120) may include a 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 (100). As an example not limited to, the cache memory may be included within the processor (110). The memory (120) may be fixedly embedded within the electronic device (100) or incorporated into one or more suitable types of components (e.g., a SIM (subscriber identity module) card and / or an SD (secure digital) card) that can be repeatedly inserted into and removed from the electronic device (100).

[0055] For example, memory (120) may store one or more software applications, such as operating system (or system) software applications, firmware software applications, driver software applications, plugin (e.g., add-in, add-on, and / or applet) software applications, and / or any other suitable software applications. For example, the one or more software applications may include instructions executable by the processor (110). For example, memory (120) may store instructions that can be called by an application programming interface (API). For example, memory (120) may store instructions within a library.

[0056] FIG. 2 is a drawing showing a computer program stored in a memory (120) of an electronic device (100) according to one embodiment of the present disclosure.

[0057] In one embodiment, the electronic device (100) may include an artificial intelligence agent (210) and an artificial intelligence assistant (230).

[0058] In one embodiment, the electronic device (100) can store an AI agent (210) and an AI assistant (220) in memory (120).

[0059] In one embodiment, the electronic device (100) may include one AI agent (210) or a plurality of AI agents (210). The AI ​​agent (210) may include a program that includes instructions.

[0060] In one embodiment, the AI ​​agent (210) may include at least one of an LLM (large language model) AI (artificial intelligence) engine, an MLLM (multi-modal large language model) AI (artificial intelligence) engine, or an LVM (large vision model) AI (artificial intelligence) engine.

[0061] For example, the AI ​​agent (210) may include a machine learning framework, algorithm, model, software library, application and / or service.

[0062] In one embodiment, the machine learning framework may include software for developing and training artificial intelligence models. The algorithm may include deep learning algorithms and reinforcement learning algorithms. The model may include software such as a neural network model. The algorithm and the model can learn the characteristics and distribution of data and perform probabilistically probable decisions based on the learned characteristics and distribution of data.

[0063] In one embodiment, the AI ​​agent (210) may include a generative AI.

[0064] In one embodiment, the LLM AI engine may include software regarding a large-scale language model. The LLM AI engine may perform natural language processing (NLP) tasks based on learned text data. The LLM AI engine may perform text generation, translation, summarization, and / or question answering tasks.

[0065] In one embodiment, the LLM AI engine can perform sentence writing, storytelling, article writing, and text generation operations. The LLM AI engine can perform language understanding operations such as question answering, document summarization, and translation. The LLM AI engine can perform operations such as answering questions or supporting tasks through conversation with a user. The LLM AI engine can perform code generation and analysis operations such as automatically generating programming code. The LLM AI engine can perform knowledge retrieval operations such as searching for information in a large database and responding.

[0066] In one embodiment, the MLLM AI engine may include software regarding a multimodal large-scale language model. The MLLM AI engine can process various forms of data, such as images, voice, and video, as well as text, in an integrated manner. The MLLM AI engine can, for example, analyze and explain text and images simultaneously, or perform interactions that combine voice and text. The MLLM AI engine can maintain consistency between different data types and process data in an integrated format. The MLLM AI engine can learn and process various forms of data, such as text, images, audio, and video, simultaneously.

[0067] In one embodiment, the MLLM AI engine can perform text and image combination operations, such as providing a text answer based on an image to a question. The MLLM AI engine can perform image captioning operations, such as generating a text description for an image. The MLLM AI engine can perform image creation and editing operations, such as generating an image based on text. The MLLM AI engine can perform speech and text integration operations, such as speech-to-text conversion operations and text-to-speech generation operations.

[0068] In one embodiment, the LVM AI engine may include software regarding a large-scale visual model. The LVM AI engine can process visual data based on learned images and videos. The LVM AI engine can collect, learn, and / or generate visual data. The LVM AI engine can perform operations that process visual tasks by learning visual data such as images. The LVM AI engine can perform image classification operations, such as object recognition operations and image classification operations. The LVM AI engine can perform image generation operations, such as text-to-image generation operations. The LVM AI engine can perform video analysis operations, such as object tracking operations in video and action recognition operations. The LVM AI engine can perform multimodal operations, such as search and generation operations combining text and images.

[0069] In one embodiment, the AI ​​agent (210) may include software capable of understanding and analyzing screen context. The AI ​​agent (210) may provide information and / or functions to the user based on the analyzed screen context.

[0070] In one embodiment, the screen context may include information displayed on a screen on the display (140) and the environment and situation in which the information is used. The screen context may include not only the content displayed on the screen, but also information regarding interaction with the user, the state of the application, and the surrounding environment.

[0071] In one embodiment, the screen context may include various user interface elements displayed on the screen, such as buttons, menus, icons, and text fields. The screen context may include actions by which a user interacts with the screen, such as touching, clicking, swiping, or gestures on the display (140). The screen context may include the task currently being performed by the application, the state of data, or the state of a network connection. The screen context may include physical environment information, such as the user's location, time zone, ambient noise, or lighting conditions. The screen context may include information regarding various types of content displayed on the screen, such as text, images, videos, or animations.

[0072] In one embodiment, the AI ​​agent (210) may collect data (224) regarding information displayed on the screen, the environment and situation in which the information is used, content displayed on the screen, interaction with the user, the state of the application, and the surrounding environment, and store it in memory (120).

[0073] In one embodiment, the AI ​​agent (210) can collect personal information used in the electronic device (100) based on a personalized data core (PDC).

[0074] In one embodiment, a personal data core (PDC) may generate personal information or personalized data from collected data (e.g., app data, usage data, system data). The personal information or personalized data may include context, preferences, and memory.

[0075] In one embodiment, the context may include personal context information. For example, personal context information may include the regularity, repetition, or frequent movements and stays of the user of the electronic device (100) as context information measured or calculated from collected data. Personal context information may include spatial context, behavior context, and temporal context.

[0076] In one embodiment, preferences may include information about an individual's profile and relationships, such as age, occupation, and gender, titles and profiles of others, and an individual's interests and preferences.

[0077] In one embodiment, the memory may include an activity (e.g., movement), content (e.g., a destination) containing information about the object that is the purpose of the activity (e.g., an object, a person, a destination, or a preference), and an engram (e.g., travel) containing a set of connections between the activity and the content that constitute a meaningful experience.

[0078] In one embodiment, the AI ​​agent (210) can generate content based on data.

[0079] In one embodiment, the AI ​​agent (210) can check a user's command (e.g., prompt) based on user input received through the electronic device (100).

[0080] In one embodiment, the AI ​​agent (210) may provide content based on data and user commands (e.g., prompts). For example, user commands may be obtained through various inputs, such as voice, text, or handwriting input. User commands may be obtained through an AI assistant (220).

[0081] In one embodiment, the AI ​​assistant (220) may include a program that includes instructions. The AI ​​assistant (220) may perform voice assistant actions that can perform natural language interaction with the user.

[0082] The AI ​​assistant (220) can understand the user's request and perform digital assistant actions such as providing answers or performing tasks. The AI ​​assistant (220) can respond based on various inputs such as voice, text, and screen recognition. The AI ​​assistant (220) can perform natural language interactions with the user. The AI ​​assistant (220) can perform digital assistant actions based on natural language interactions with the user.

[0083] In one embodiment, the AI ​​assistant (220) can transmit natural language or user commands obtained through natural language interaction with the user to the AI ​​agent (210).

[0084] In one embodiment, the AI ​​agent (210) may provide content based on user commands obtained through the AI ​​assistant (220). The content may be provided through the electronic device (100) in various ways, such as text, voice, and video. The content may be provided through the AI ​​agent (210), AI assistant (220), or application stored in the electronic device (100).

[0085] FIG. 3 is a flowchart illustrating a method for providing content according to an embodiment of the present invention.

[0086] In one embodiment, the memory (120) can store computer program(s) including instructions.

[0087] In one embodiment, instructions stored in memory (120) can cause an electronic device (100) to perform the content providing method of FIG. 3 when executed individually or collectively by at least one processor (110).

[0088] In one embodiment, in operation 301, instructions stored in memory (120) can enable an electronic device (100) to acquire communication information when executed individually or collectively by at least one processor (110).

[0089] For example, communication information may include wireless communication information such as cellular communication information (e.g., 5G, LTE), Wi-Fi communication information, and short-range communication information (e.g., Bluetooth communication, NFC (near field communication) communication, UWB (ultra-wide band) communication).

[0090] For example, communication information may include not only wireless communication information but also satellite communication information such as GNSS (Global Navigation Satellite System) information.

[0091] In one embodiment, in operation 301, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain communication information through the communication circuit (160).

[0092] In one embodiment, in operation 303, instructions stored in memory (120) can enable the electronic device (100) to identify external electronic devices or geographical information of the electronic device (100) based on communication information when executed individually or collectively by at least one processor (110).

[0093] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices around the electronic device (100) based on connectivity communication when executed individually or collectively by at least one processor (110).

[0094] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices in the vicinity of the electronic device based on connectivity communication through an AI agent (210) when executed individually or collectively by at least one processor (110).

[0095] For example, the surroundings of the electronic device (100) may include a preset distance from the electronic device.

[0096] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine AP channel congestion information from beacon frame data received from a Wi-Fi AP (access point). For example, the congestion information may include channel utilization or station count.

[0097] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether there is one or more external electronic devices connected to the same AP based on AP channel congestion information.

[0098] In one embodiment, in operation 303, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can check MAC address information in header information within a packet communicated by an AP of Wi-Fi connected to the electronic device (100).

[0099] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether there is one or more external electronic devices connected to the same AP based on MAC address information.

[0100] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to monitor Wi-Fi communication packets for a specific period of time when executed individually or collectively by at least one processor (110).

[0101] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether an AP connected to the electronic device (100) performs packet transmission with one or more external electronic devices based on monitored Wi-Fi communication packets.

[0102] In one embodiment, in operation 303, instructions stored in memory (120) may cause the electronic device (100) to check for the presence of one or more external electronic devices based on confirming that an AP connected to the electronic device (100) performs packet transmission with one or more external electronic devices when executed individually or collectively by at least one processor (110).

[0103] For example, the operation of identifying an external electronic device connected to the AP may be based on the operation of identifying it through the short-range communication-based signal strength detected by the electronic device (100). The accuracy of the operation of identifying an external electronic device connected to the AP may be improved in detecting an external electronic device that stays in the same space for a long time.

[0104] In one embodiment, in operation 303, instructions stored in memory (120) can enable an electronic device (100) to obtain identification information of an external electronic device based on near-field communication information (e.g., Bluetooth communication, NFC (near field communication) communication, UWB (ultra-wide band) communication) when executed individually or collectively by at least one processor (110).

[0105] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether one or more external electronic devices exist around the electronic device (100) based on identification information (e.g., ID) of the external electronic devices.

[0106] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether there is an external electronic device around the electronic device, the number of external electronic devices present, or the type of external electronic devices present based on identification information (e.g., ID) of the external electronic device.

[0107] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to check the pre-shared key (PSK) information of the Wi-Fi device when executed individually or collectively by at least one processor (110).

[0108] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether one or more external electronic devices exist around the electronic device (100) based on the pre-shared key (PSK) information of the Wi-Fi device.

[0109] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether there is an external electronic device around the electronic device (100), the number of external electronic devices present, or the type of external electronic devices present based on the PSK (pre-shared key) information of the Wi-Fi device.

[0110] In one embodiment, in operation 303, instructions stored in memory (120) can enable the electronic device (100) to identify geographical information of the electronic device (100) based on wireless communication information when executed individually or collectively by at least one processor (110).

[0111] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to identify geographical information of the electronic device (100) based on satellite communication information such as GNSS (Global Navigation Satellite System) information when executed individually or collectively by at least one processor (110).

[0112] In one embodiment, in operation 303, instructions stored in memory (120) can enable the electronic device (100) to identify geographical information based on Wi-Fi-based zone detection when executed individually or collectively by at least one processor (110).

[0113] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify the location where the electronic device (100) is located based on identified geographical information.

[0114] In one embodiment, in operation 303, instructions stored in memory (120) can enable the electronic device (100) to obtain geographical information based on location information-based map information, RAG (Retrieval-Augmented Generation), or web crawling when executed individually or collectively by at least one processor (110).

[0115] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify the location where the electronic device (100) is located based on location information-based map information, RAG (Retrieval-Augmented Generation), or web crawling.

[0116] In one embodiment, in operation 303, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to infer the location where the electronic device (100) is located based on the SSID.

[0117] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to identify the location where the electronic device (100) is located based on the Service Set Identifier (SSID) when executed individually or collectively by at least one processor (110).

[0118] For example, in operation 303, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can identify whether the place where the electronic device (100) is located is a private place or a public place based on identified geographical information.

[0119] For example, in operation 303, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can identify the location where the electronic device (100) is located based on geographical information verified through the AI ​​agent (210).

[0120] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element corresponding to an identified external electronic device on a display (140) when executed individually or collectively by at least one processor (110).

[0121] In one embodiment, in operation 303, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element on a display (140) indicating that there is an external electronic device around the electronic device (100) when executed individually or collectively by at least one processor (110).

[0122] For example, the graphic element may include an image or icon similar to the shape of an external electronic device. The graphic element may be displayed on the display (140) in a direction corresponding to the direction in which the external electronic device is located relative to the electronic device (100). However, it is not limited thereto, and the operation of displaying a graphic element on the display (140) indicating that there is an external electronic device around the electronic device (100) may be performed regardless of the order of FIG. 3.

[0123] In one embodiment, in operation 305, instructions stored in memory (120) can cause the electronic device (100) to check personal information related to an external electronic device when executed individually or collectively by at least one processor (110).

[0124] In this document, the user of the electronic device (100) may be referred to as the user, and a person related to the user or geographical information regarding the external electronic device may be referred to as a person nearby. However, it is not limited thereto.

[0125] In one embodiment, personal information may include profile information about a user of an external electronic device. Personal information may include profile information about a person related to geographical information.

[0126] In one embodiment, in operation 305, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can obtain profile information about the user of the external electronic device based on the identification information of the external electronic device, if the identification information of the external electronic device (e.g., MAC address information, PSK information) is already stored in memory (120).

[0127] In one embodiment, the electronic device (100) can store profile information for a user of an external electronic device in advance in memory (120).

[0128] However, it is not limited to this, and a cloud server capable of communicating with the electronic device (100) can store profile information about the user of the external electronic device in advance.

[0129] For example, profile information regarding a user of an external electronic device may include age, preferences, gender, and relationship information with the user. Profile information regarding a person related to geographical information may include age, preferences, gender, and relationship information with the user.

[0130] In one embodiment, the electronic device (100) can generate a profile of a user of an external electronic device based on information related to a person or application usage history related to a person.

[0131] In one embodiment, the electronic device (100) can collect information related to a person or application usage history related to a person and store it in memory (120).

[0132] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to generate a profile of a person based on information related to the person or application usage history related to the person, when executed individually or collectively by at least one processor (110).

[0133] In one embodiment, instructions stored in memory (120) can be obtained by the electronic device (100) through a database search stored in memory (120) when executed individually or collectively by at least one processor (110).

[0134] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to generate a profile of a person based on information related to the person or application usage history related to the person through an AI agent (210) when executed individually or collectively by at least one processor (110).

[0135] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to update a profile of a person based on information collected after generating a profile of a person, when executed individually or collectively by at least one processor (110).

[0136] In one embodiment, in operation 305, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), and the electronic device (100) can determine a person associated with geographical information when identification information of an identified external electronic device (e.g., MAC address information, PSK information) is not stored in memory (120).

[0137] In one embodiment, if the identification information of the identified external electronic device (e.g., MAC address information, PSK information) is not stored in the memory (120), it may include a case where the external electronic device cannot be identified using the identification information.

[0138] In one embodiment, in operation 305, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain a profile of a person associated with geographical information when identification information of an identified external electronic device (e.g., MAC address information, PSK information) is not stored in memory (120).

[0139] In one embodiment, in operation 307, instructions stored in memory (120) can cause the electronic device (100) to create content based on at least one of user input, geographical information, or personal information for content creation when executed individually or collectively by at least one processor (110).

[0140] In one embodiment, in operation 307, instructions stored in memory (120) can cause the electronic device (100) to verify user commands based on user input for content creation when executed individually or collectively by at least one processor (110).

[0141] In one embodiment, the user command may include a prompt transmitted to the AI ​​agent (210). Instructions stored in memory (120), when executed individually or collectively by at least one processor (110), may cause the electronic device (100) to generate content based on at least one of prompt input, geographical information, or personal information through the AI ​​agent (210).

[0142] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may generate a prompt based on at least one of acquired communication information or personal information related to an external electronic device and transmit it as input to an AI agent (210).

[0143] In one embodiment, a user command may be received via an AI assistant (220) and transmitted to an AI agent (210). However, this is not limited thereto, and user input may be transmitted to the AI ​​agent (210) via an application capable of communicating with the AI ​​agent (210). User input may include various inputs such as voice, text, or screen recognition.

[0144] In one embodiment, in operation 307, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), so that when the electronic device (100) receives user input for content creation, it can create content based on at least one of geographical information or personal information.

[0145] In one embodiment, personal information may include at least one of the user's profile information and the profile information of people around them.

[0146] In one embodiment, in operation 307, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), and when the electronic device (100) receives user input for content creation, it can generate user commands based on personal information.

[0147] For example, user commands based on personal information may include at least one of negative prompts, such as controlling the level of exposure of sensitive information or age restrictions, preferred style (or preference), or personalized data.

[0148] In one embodiment, in operation 307, instructions stored in memory (120) can cause the electronic device (100) to generate content according to user commands generated based on personal information when executed individually or collectively by at least one processor (110).

[0149] In one embodiment, in operation 307, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element indicating that the generated content is content generated by reflecting the personal information of a person nearby when executed individually or collectively by at least one processor (110).

[0150] For example, the generated content may include at least one of text, images, audio, or video.

[0151] In one embodiment, the electronic device (100) may store personal information (or, profile) about the person by analyzing the voice signal of the person by prior analysis. If personal information (or, profile) about the person by prior analysis is stored, then even if the person by prior accesses the electronic device (100) without accompanying an external electronic device, in operation 307, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby enabling the electronic device (100) to generate content based on the person by prior's personal information, user commands, and geographical information.

[0152] In one embodiment, in operation 309, instructions stored in memory (120) can provide the electronic device (100) with generated content when executed individually or collectively by at least one processor (110).

[0153] In one embodiment, in operation 309, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to display content generated through the display (140).

[0154] In one embodiment, in operation 309, instructions stored in memory (120) can cause the electronic device (100) to play content generated through a speaker when executed individually or collectively by at least one processor (110).

[0155] In one embodiment, in operation 309, instructions stored in memory (120) can cause the electronic device (100) to play content generated through a speaker and a display (140) when executed individually or collectively by at least one processor (110).

[0156] FIG. 4 is a flowchart illustrating a method for providing content according to an embodiment of the present invention.

[0157] In one embodiment, the memory (120) can store computer program(s) including instructions.

[0158] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to perform the content providing method of FIG. 4 when executed individually or collectively by at least one processor (110). In describing FIG. 4, content that overlaps with FIG. 3 may be omitted.

[0159] In one embodiment, in operation 401, instructions stored in memory (120) can enable the electronic device (100) to acquire communication information when executed individually or collectively by at least one processor (110).

[0160] For example, communication information may include wireless communication information such as cellular communication information (e.g., 5G, LTE), Wi-Fi communication information, and short-range communication information (e.g., Bluetooth communication, NFC (near field communication) communication, UWB (ultra-wide band) communication).

[0161] For example, communication information may include not only wireless communication information but also satellite communication information such as GNSS (Global Navigation Satellite System) information.

[0162] In one embodiment, in operation 401, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain communication information through the communication circuit (160).

[0163] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices or geographical information of the electronic device (100) around the electronic device based on communication information when executed individually or collectively by at least one processor (110).

[0164] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices around the electronic device (100) based on connectivity communication when executed individually or collectively by at least one processor (110).

[0165] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices around the electronic device (100) based on connectivity communication through an AI agent (210) when executed individually or collectively by at least one processor (110).

[0166] For example, the surroundings of the electronic device (100) may include an area within a preset distance from the electronic device (100).

[0167] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine AP channel congestion information from beacon frame data received from a Wi-Fi AP (access point). For example, the congestion information may include channel utilization or station count.

[0168] In one embodiment, in operation 403, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can determine whether there is one or more external electronic devices connected to the same AP based on AP channel congestion information.

[0169] In one embodiment, in operation 403, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can check MAC address information in header information within a packet communicated by an AP of Wi-Fi connected to the electronic device (100).

[0170] In one embodiment, in operation 403, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can determine whether there is one or more external electronic devices connected to the same AP based on MAC address information.

[0171] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to monitor Wi-Fi communication packets for a specific period of time when executed individually or collectively by at least one processor (110).

[0172] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to determine whether an AP connected to the electronic device (100) performs packet transmission with one or more external electronic devices based on a monitored Wi-Fi communication packet when executed individually or collectively by at least one processor (110).

[0173] In one embodiment, in operation 403, instructions stored in memory (120) may cause the electronic device (100) to check for the presence of one or more external electronic devices based on confirming that an AP connected to the electronic device (100) performs packet transmission with one or more external electronic devices when executed individually or collectively by at least one processor (110).

[0174] For example, the operation of identifying an external electronic device connected to the AP may be based on the operation of identifying it through the short-range communication-based signal strength detected by the electronic device (100). The accuracy of the operation of identifying an external electronic device connected to the AP may be improved in detecting an external electronic device that stays in the same space for a long time.

[0175] In one embodiment, in operation 403, instructions stored in memory (120) can enable an electronic device (100) to obtain identification information of an external electronic device based on near-field communication information (e.g., Bluetooth communication, NFC (near field communication) communication, UWB (ultra-wide band) communication) when executed individually or collectively by at least one processor (110).

[0176] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether one or more external electronic devices exist around the electronic device (100) based on identification information (e.g., ID) of the external electronic devices.

[0177] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether there is an external electronic device around the electronic device (100), the number of external electronic devices present, or the type of external electronic devices present based on identification information (e.g., ID) of the external electronic device.

[0178] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to check the pre-shared key (PSK) information of the Wi-Fi device when executed individually or collectively by at least one processor (110).

[0179] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to determine whether one or more external electronic devices exist around the electronic device (100) based on the pre-shared key (PSK) information of the Wi-Fi device.

[0180] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether there is an external electronic device around the electronic device (100), the number of external electronic devices present, or the type of external electronic devices present based on the PSK (pre-shared key) information of the Wi-Fi device.

[0181] In one embodiment, in operation 403, instructions stored in memory (120) can enable the electronic device (100) to identify geographical information of the electronic device (100) based on wireless communication information when executed individually or collectively by at least one processor (110).

[0182] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to identify geographical information of the electronic device (100) based on satellite communication information such as GNSS (Global Navigation Satellite System) information when executed individually or collectively by at least one processor (110).

[0183] In one embodiment, in operation 403, instructions stored in memory (120) can enable the electronic device (100) to identify geographical information based on Wi-Fi-based zone detection when executed individually or collectively by at least one processor (110).

[0184] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify the location where the electronic device (100) is located based on identified geographical information.

[0185] In one embodiment, in operation 403, instructions stored in memory (120) can enable the electronic device (100) to obtain geographical information based on location information-based map information, RAG (Retrieval-Augmented Generation), or web crawling when executed individually or collectively by at least one processor (110).

[0186] In one embodiment, in operation 403, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify the location where the electronic device (100) is located based on location information-based map information, RAG (Retrieval-Augmented Generation), or web crawling.

[0187] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to infer the location of the electronic device (100) based on the SSID when executed individually or collectively by at least one processor (110).

[0188] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to identify the location of the electronic device (100) based on the Service Set Identifier (SSID) when executed individually or collectively by at least one processor (110).

[0189] For example, in operation 403, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can identify whether the place where the electronic device (100) is located is a private place or a public place based on identified geographical information.

[0190] For example, in operation 403, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can identify the location where the electronic device (100) is located based on geographical information verified through the AI ​​agent (210).

[0191] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element corresponding to an identified external electronic device on a display (140) when executed individually or collectively by at least one processor (110).

[0192] In one embodiment, in operation 403, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element on a display (140) indicating that there is an external electronic device around the electronic device (100) when executed individually or collectively by at least one processor (110).

[0193] For example, the graphic element may include an image or icon similar to the shape of an external electronic device. The graphic element may be displayed on the display (140) in a direction corresponding to the direction in which the external electronic device is located relative to the electronic device (100). However, it is not limited thereto, and the operation of displaying a graphic element on the display (140) indicating that there is an external electronic device around the electronic device (100) may be performed regardless of the order of FIG. 3.

[0194] In one embodiment, in operation 405, instructions stored in memory (120) can cause the electronic device (100) to check personal information related to an external electronic device when executed individually or collectively by at least one processor (110).

[0195] In this document, the user of the electronic device (100) may be referred to as the user, and a person related to the user or geographical information regarding the external electronic device may be referred to as a person nearby. However, it is not limited thereto.

[0196] In one embodiment, personal information may include profile information about a user of an external electronic device. Personal information may include profile information about a person related to geographical information.

[0197] In one embodiment, in operation 405, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can obtain profile information about the user of the external electronic device based on the identification information of the external electronic device, if the identification information of the external electronic device (e.g., MAC address information, PSK information) is already stored in memory (120).

[0198] In one embodiment, the electronic device (100) can store profile information for a user of an external electronic device in advance in memory (120).

[0199] However, it is not limited to this, and a cloud server capable of communicating with the electronic device (100) can store profile information about the user of the external electronic device in advance.

[0200] For example, profile information regarding a user of an external electronic device may include age, preferences, gender, and relationship information with the user. Profile information regarding a person related to geographical information may include age, preferences, gender, and relationship information with the user.

[0201] In one embodiment, the electronic device (100) can generate a profile of a user of an external electronic device based on information related to a person or application usage history related to a person.

[0202] In one embodiment, the electronic device (100) can collect information related to a person or application usage history related to a person and store it in memory (120).

[0203] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to generate a profile of a person based on information related to the person or application usage history related to the person, when executed individually or collectively by at least one processor (110).

[0204] In one embodiment, instructions stored in memory (120) can be obtained by the electronic device (100) through a database search stored in memory (120) when executed individually or collectively by at least one processor (110).

[0205] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to generate a profile of a person based on information related to the person or application usage history related to the person through an AI agent (210) when executed individually or collectively by at least one processor (110).

[0206] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to update a profile of a person based on information collected after generating a profile of a person, when executed individually or collectively by at least one processor (110).

[0207] In one embodiment, in the 405 operation, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may determine a person associated with geographical information if identification information of an identified external electronic device (e.g., MAC address information, PSK information) is not stored in memory (120).

[0208] In one embodiment, if the identification information of the identified external electronic device (e.g., MAC address information, PSK information) is not stored in the memory (120), it may include a case where the external electronic device cannot be identified using the identification information.

[0209] In one embodiment, in operation 405, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain a profile of a person associated with geographical information when identification information of an identified external electronic device (e.g., MAC address information, PSK information) is not stored in memory (120).

[0210] In one embodiment, in operation 407, instructions stored in memory (120) may cause the electronic device (100) to determine a method of providing content based on at least one of user input, geographical information, or personal information when executed individually or collectively by at least one processor (110).

[0211] In one embodiment, in operation 407, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to extract keywords for preference / non-preference based on at least one of current location characteristic information or user profile information of an external electronic device.

[0212] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to check preference / non-preference information based on at least one of current location characteristic information or user profile information of an external electronic device when executed individually or collectively by at least one processor (110).

[0213] In one embodiment, in operation 407, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can determine whether there is a preference / non-preference for a plurality of contents based on keywords for preference / non-preference.

[0214] In one embodiment, in operation 407, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can determine whether there is a preference / non-preference for a plurality of contents based on preference / non-preference information.

[0215] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to filter multiple contents based on preference / non-preference information when executed individually or collectively by at least one processor (110).

[0216] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to sort multiple contents according to priority based on preference / non-preference information when executed individually or collectively by at least one processor (110).

[0217] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to regenerate content by processing actual data based on at least one of user input, geographical information, or personal information when executed individually or collectively by at least one processor (110).

[0218] In one embodiment, the operation of determining a method for providing content may include an operation of filtering multiple pieces of content based on preference / non-preference information, an operation of sorting multiple pieces of content according to priority based on preference / non-preference information, or an operation of recreating content.

[0219] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to verify user commands based on user input for providing content when executed individually or collectively by at least one processor (110).

[0220] In one embodiment, the user command may include a prompt transmitted to the AI ​​agent (210). Instructions stored in memory (120), when executed individually or collectively by at least one processor (110), may cause the electronic device (100) to determine a method of providing content based on at least one of prompt input, geographical information, or personal information through the AI ​​agent (210).

[0221] In one embodiment, a user command may be received via an AI assistant (220) and transmitted to an AI agent (210). However, this is not limited thereto, and user input may be transmitted to the AI ​​agent (210) via an application capable of communicating with the AI ​​agent (210). User input may include various inputs such as voice, text, or screen recognition.

[0222] In one embodiment, in operation 407, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), so that when the electronic device (100) receives user input, it can determine a method of providing content based on at least one of geographical information or personal information.

[0223] In one embodiment, personal information may include at least one of the user's profile information and the profile information of people around them.

[0224] In one embodiment, in operation 407, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), and when the electronic device (100) receives user input, it can generate user commands based on personal information.

[0225] For example, user commands based on personal information may include at least one of negative prompts, such as controlling the level of exposure of sensitive information or age restrictions, preferred style (or preference), or personalized data.

[0226] In one embodiment, in operation 407, instructions stored in memory (120) can cause the electronic device (100) to determine how to provide content according to user commands generated based on personal information when executed individually or collectively by at least one processor (110).

[0227] In one embodiment, in operation 407, if personal information (or profile) about a person is stored by analyzing the voice signal of a person in advance, even if the person in the vicinity accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine a method of providing content based on the person in the vicinity's personal information, user commands, and geographical information.

[0228] In one embodiment, in operation 407, if personal information (or profile) about a person is stored by analyzing the voice signal of a person in advance, even if the person in the vicinity accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby causing the electronic device (100) to regenerate content based on the person in the vicinity's personal information, user commands, and geographical information.

[0229] In one embodiment, in operation 407, if personal information (or profile) about a person is stored by analyzing the voice signal of a person in advance, even if the person in the vicinity accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby enabling the electronic device (100) to provide content based on the person in the vicinity's personal information, user commands, and geographical information.

[0230] In one embodiment, in operation 407, if personal information (or profile) about a person is stored by analyzing the voice signal of a person in advance, even if the person in the vicinity accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby enabling the electronic device (100) to sort content based on the person in the vicinity's personal information, user commands, and geographical information.

[0231] In one embodiment, in operation 409, instructions stored in memory (120) can cause the electronic device (100) to provide content based on a determined method when executed individually or collectively by at least one processor (110).

[0232] In one embodiment, in operation 409, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to display content through a display (140).

[0233] In one embodiment, in operation 409, instructions stored in memory (120) can cause the electronic device (100) to play content through a speaker when executed individually or collectively by at least one processor (110).

[0234] In one embodiment, in operation 409, instructions stored in memory (120) can cause the electronic device (100) to play content through a speaker and a display (140) when executed individually or collectively by at least one processor (110).

[0235] In one embodiment, in operation 409, instructions stored in memory (120) may cause the electronic device (100) to display a graphic element indicating that the content being provided is content that reflects the personal information of a person nearby when executed individually or collectively by at least one processor (110). For example, the content may include at least one of text, images, voice, or video.

[0236] FIG. 5 is a diagram illustrating a method in which an electronic device (100) according to one embodiment of the present disclosure generates a profile.

[0237] In one embodiment, in operation 510, instructions stored in memory (120) can cause the electronic device (100) to identify the location of the user of the electronic device (100) when executed individually or collectively by at least one processor (110).

[0238] In one embodiment, in operation 510, instructions stored in memory (120) can cause the electronic device (100) to identify the location where the user of the electronic device (100) is located when executed individually or collectively by at least one processor (110).

[0239] In one embodiment, in operation 510, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain information about the location where the user of the electronic device (100) is located.

[0240] In one embodiment, in the 511 operation, instructions stored in memory (120) may enable the electronic device (100) to obtain geographic information based on wireless communication information (e.g., satellite communication, short-range wireless communication, cellular communication) when executed individually or collectively by at least one processor (110). For example, the wireless communication information may include GNSS information and Wi-Fi-based zone detection (or geofence) information.

[0241] In one embodiment, in operation 512, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify places frequently visited by the user based on geographical information.

[0242] In one embodiment, in operation 512, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to check information about places frequently visited by the user based on geographical information.

[0243] In one embodiment, in operation 512, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to perform labeling of places (or information about places) that a user frequently visits based on geographical information.

[0244] In one embodiment, in operation 512, instructions stored in memory (120) can enable the electronic device (100) to identify (or obtain) the location where the user is currently located (or information about the location) based on geographical information when executed individually or collectively by at least one processor (110).

[0245] In one embodiment, in operation 512, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify (or obtain) the location where the user is currently located (or information about the location) based on geographical information through the AI ​​agent (210).

[0246] In one embodiment, in operation 520, instructions stored in memory (120) can cause the electronic device (100) to generate a profile of a person in the vicinity when executed individually or collectively by at least one processor (110). The person in the vicinity may include a user of an external electronic device.

[0247] In one embodiment, in operation 523, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to collect usage history of an application related to a user (or person nearby) of an external electronic device.

[0248] In one embodiment, in operation 523, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to collect (or acquire) data related to the user (or surrounding person) of the external electronic device.

[0249] For example, data related to the user (or people around) of an external electronic device may include data regarding item recommendations such as like / dislike on social media.

[0250] For example, data related to the user (or person nearby) of an external electronic device may include call content.

[0251] For example, the collected application usage history may include various application usage histories such as gallery, SMS, screenshots, calendar, or file sharing.

[0252] For example, referring to screen 521, an application related to a user (or person nearby) of an external electronic device includes a chat application, and instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to collect conversation content between the user of the electronic device (100) and a person nearby through the chat application.

[0253] For example, referring to screen 522, the application related to the user (or person nearby) of the external electronic device includes a chat application, and the instructions stored in memory (120) can cause the electronic device (100) to collect (or acquire) the object preferred by the person nearby (e.g., object, person, purpose or preference) when executed individually or collectively by at least one processor (110).

[0254] In one embodiment, in operation 524, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to enable the electronic device (100) to generate a profile of the user (or person) of the external electronic device based on the usage history of applications related to the user (or person) of the external electronic device. For example, the profile of the user (or person) of the external electronic device may include preference information, non-preference information, or information about associated places.

[0255] In one embodiment, in operation 524, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to generate a profile of the user (or person) of the external electronic device based on the usage history of an application related to the user (or person) of the external electronic device through an AI agent (210).

[0256] In one embodiment, in operation 524, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to analyze data on item recommendations such as like / dislike through an AI agent (210) and to identify preference information and non-preference information for specific types of content.

[0257] In the embodiment, in operation 524, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to analyze the content of a call through an AI agent (210) to determine the emotions of a person nearby.

[0258] In an embodiment, in operation 524, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to check preference information through photos or message content of people around it via an AI agent (210).

[0259] In one embodiment, in operation 525, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify an external electronic device that has a connection record with the electronic device (100) based on connectivity communication information.

[0260] In one embodiment, in operation 525, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to check information about a person nearby based on connectivity communication information.

[0261] In one embodiment, in operation 525, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to check the communication detection record for an external electronic device.

[0262] In one embodiment, in operation 526, instructions stored in memory (120) can cause the electronic device (100) to identify a location associated with the user of the external electronic device based on a communication detection record for the external electronic device when executed individually or collectively by at least one processor (110).

[0263] In one embodiment, in operation 526, instructions stored in memory (120) can cause the electronic device (100) to identify a location associated with a user of an external electronic device based on connectivity communication information when executed individually or collectively by at least one processor (110).

[0264] In one embodiment, in operation 526, instructions stored in memory (120) can cause the electronic device (100) to identify the space where the electronic device (100) and the external electronic device are most detected as a place associated with the user of the external electronic device when executed individually or collectively by at least one processor (110).

[0265] In one embodiment, in operation 527, the instructions stored in memory (120), when executed individually or collectively by at least one processor (110), may cause the electronic device (100) to generate a profile of the user (or person) of the external electronic device based on a profile of the user (or person) of the external electronic device and a location associated with the user of the external electronic device generated based on operations 526 and 524.

[0266] In one embodiment, in operation 527, instructions stored in memory (120) can cause the electronic device (100) to add information about a place associated with the user of the external electronic device to a profile about the user (or person around) of the external electronic device when executed individually or collectively by at least one processor (110).

[0267] In one embodiment, in operation 527, instructions stored in memory (120) can cause the electronic device (100) to store a profile of a user (or person nearby) of an external electronic device in memory (120) when executed individually or collectively by at least one processor (110).

[0268] In one embodiment, in operation 527, instructions stored in memory (120) can cause the electronic device (100) to store a profile of a user (or person nearby) of an external electronic device on a cloud server when executed individually or collectively by at least one processor (110).

[0269] FIG. 6 is a diagram illustrating a method in which an electronic device (100) according to one embodiment of the present disclosure generates content.

[0270] In one embodiment, in operation 610, instructions stored in memory (120) can cause the electronic device (100) to check the surrounding context of the electronic device (100) when executed individually or collectively by at least one processor (110).

[0271] In one embodiment, the 610 operation may include at least one of the 611 operation, the 612 operation, or the 613 operation.

[0272] In one embodiment, in the 611 operation, instructions stored in memory (120) can enable the electronic device (100) to identify geographical information of the electronic device (100) based on communication information when executed individually or collectively by at least one processor (110).

[0273] In one embodiment, in the 611 operation, instructions stored in memory (120) can enable the electronic device (100) to recognize the space where the electronic device (100) is located based on geographical information when executed individually or collectively by at least one processor (110).

[0274] In one embodiment, in operation 612, instructions stored in memory (120) can cause the electronic device (100) to identify external electronic devices around the electronic device (100) based on communication information and communication signals when executed individually or collectively by at least one processor (110).

[0275] In one embodiment, in operation 613, instructions stored in memory (120) can cause the electronic device (100) to identify personal information about the user of the external electronic device corresponding to the identified external electronic device when executed individually or collectively by at least one processor (110).

[0276] In one embodiment, in operation 614, instructions stored in memory (120) can cause the electronic device (100) to generate context information based on geographical information, communication information, and personal information about the user of an external electronic device when executed individually or collectively by at least one processor (110).

[0277] In one embodiment, in operations 614 and 615, the instructions stored in memory (120) can enable the electronic device (100) to obtain preference information based on geographical information, communication information, and personal information about the user of an external electronic device when executed individually or collectively by at least one processor (110).

[0278] In one embodiment, in operations 614 and 615, the instructions stored in memory (120) can enable the electronic device (100) to obtain keywords regarding preferences based on geographical information, communication information and personal information about the user of an external electronic device when executed individually or collectively by at least one processor (110).

[0279] In one embodiment, in operations 614 and 615, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain preference information based on geographical information, communication information, and personal information about the user of an external electronic device through an AI agent (210).

[0280] In one embodiment, in operations 614 and 615, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to obtain keywords regarding preferences based on geographical information, communication information, and personal information about the user of an external electronic device through an AI agent (210).

[0281] In one embodiment, in operation 620, instructions stored in memory (120) can cause the electronic device (100) to generate content based on the surrounding context of the identified electronic device (100) when executed individually or collectively by at least one processor (110).

[0282] In one embodiment, in operation 621, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to receive user commands for content creation.

[0283] In one embodiment, in operation 622, instructions stored in memory (120) can cause the electronic device (100) to generate content based on information regarding user commands and preferences when executed individually or collectively by at least one processor (110). Information regarding user commands and preferences can be input as a prompt to the AI ​​agent (210).

[0284] In one embodiment, in operation 622, instructions stored in memory (120) can cause the electronic device (100) to generate content based on information regarding user commands and preferences through an AI agent (210) when executed individually or collectively by at least one processor (110).

[0285] In one embodiment, in operation 622, instructions stored in memory (120) can cause the electronic device (100) to regenerate already generated content into new content based on information regarding user commands and preferences when executed individually or collectively by at least one processor (110).

[0286] In one embodiment, in 622 operation, instructions stored in memory (120) can enable the electronic device (100) to provide content based on information regarding user commands and preferences when executed individually or collectively by at least one processor (110).

[0287] In one embodiment, in 622 operation, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to provide multiple contents based on priority based on information regarding user commands and preferences.

[0288] In one embodiment, in 622 operation, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to filter and provide multiple contents based on information regarding user commands and preferences.

[0289] In one embodiment, in operation 622, instructions stored in memory (120) may cause the electronic device (100) to display a graphic element indicating that the content being provided is content that reflects the personal information of a person nearby when executed individually or collectively by at least one processor (110). For example, the content may include at least one of text, images, voice, or video.

[0290] In one embodiment, in 622 operation, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element on a display (140) indicating that there is an external electronic device around the electronic device (100) when executed individually or collectively by at least one processor (110).

[0291] In one embodiment, screen 631 may display content generated by the electronic device (100) before reflecting personal information regarding the user of the external electronic device, and screen 632 may display content generated by the electronic device (100) after reflecting personal information regarding the user of the external electronic device. For example, a user of the electronic device (100) may request the electronic device (100) to generate a “Halloween image.” If there is no user of the external electronic device around the electronic device (100), an image with a scary feeling, such as screen 631 based on the user’s preference of the electronic device (100), may be generated. If there is a user of the external electronic device around the electronic device (100), an image with a soft feeling, such as screen 632 based on the user’s preference of the electronic device (100), may be generated. For example, the user of the external electronic device may have a relationship with the user of the electronic device (100) that of a “minor child.”

[0292] FIG. 7 is a diagram illustrating the operation of generating personal information about a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0293] In one embodiment, personal information may include a profile.

[0294] In one embodiment, Kim (720) or Yoo (730) may be a person near the user (710) of the electronic device (100).

[0295] In one embodiment, the electronic device (100) can generate a profile of a user of an external electronic device based on information related to a person or application usage history related to a person.

[0296] In one embodiment, the electronic device (100) can generate a profile (740) for a user of an external electronic device based on information related to a person or application usage history related to a person.

[0297] In one embodiment, the electronic device (100) can generate a profile (740) for a user of an external electronic device based on information related to a person or application usage history related to a person through a plurality of AI agents (751, 752). The electronic device (100) can generate a profile (740) for a user of an external electronic device by selecting at least one of the plurality of AI agents (751, 752) according to the form of data used in the application.

[0298] For example, personal information (721) about Kim (720) can be generated based on data (e.g., text, images, screenshot captures) (760) collected through the history of various applications such as SNS, SMS, photo album, call save list, call history, or calendar with the user (710).

[0299] In one embodiment, instructions stored in memory (120) may, when executed individually or collectively by at least one processor (110), cause the electronic device (100) to generate and store personal information including relationship information (e.g., daughter of user (710), preference information (e.g., cat, flower), or non-preference information based on data (740) collected through a plurality of AI agents (751, 752).

[0300] For example, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may be able to generate and store relationship information, preference information, or non-preference information in a list.

[0301] For example, the electronic device (100) may include a dedicated AI agent (210) for generating personal information. However, it is not limited thereto, and the electronic device (100) may generate personal information using a general LLM (Large Language Model).

[0302] FIG. 8 is a diagram illustrating an operation of providing content based on personal information of a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0303] For example, when Yoo (730) is detected in the vicinity of a user (710), instructions stored in memory (120) can cause the electronic device (100) to check whether there is prior stored personal information about Yoo (730) when executed individually or collectively by at least one processor (110).

[0304] In one embodiment, the electronic device (100) can determine whether there is a user (or person in the vicinity) of an external electronic device around the electronic device (100) based on ambient voice information (811) or communication information (812) obtained through a microphone.

[0305] In one embodiment, in the 821 operation, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether there is a user (or person nearby) of an external electronic device around the electronic device (100) based on ambient voice information (811) or communication information (812) obtained through a microphone.

[0306] In one embodiment, in the 822 operation, instructions stored in memory (120) can cause the electronic device (100) to identify the user of an external electronic device based on communication information or a communication connection record when executed individually or collectively by at least one processor (110).

[0307] In one embodiment, in operation 823, instructions stored in memory (120) can cause the electronic device (100) to display a graphic element on the display (140) that an external electronic device or a user of an external electronic device is close to the electronic device (100) when executed individually or collectively by at least one processor (110).

[0308] In one embodiment, in operation 824, instructions stored in memory (120) can cause the electronic device (100) to check preference / non-preference information based on personal information about the user of the external electronic device when executed individually or collectively by at least one processor (110).

[0309] In one embodiment, in an 824 operation, instructions stored in memory (120) can cause the electronic device (100) to check a preference / non-preference list based on a profile of a user of an external electronic device when executed individually or collectively by at least one processor (110).

[0310] In one embodiment, in the 825 operation, instructions stored in memory (120) can cause the electronic device (100) to rearrange and display content based on preference / non-preference information when executed individually or collectively by at least one processor (110).

[0311] In one embodiment, in the 825 operation, instructions stored in memory (120) can cause the electronic device (100) to transmit preference / non-preference information to a third-party application when executed individually or collectively by at least one processor (110).

[0312] For example, if there is prior personal information stored about Yoo (730), instructions stored in memory (120) can cause the electronic device (100) to extract positive / negative keywords based on the personal information when executed individually or collectively by at least one processor (110). If there is prior personal information stored about Yoo (730), instructions stored in memory (120) can cause the electronic device (100) to check preference information based on the personal information when executed individually or collectively by at least one processor (110). Instructions stored in memory (120) can cause the electronic device (100) to display content on the display (140) based on Yoo (730)'s preference when executed individually or collectively by at least one processor (110).

[0313] For example, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may lower the content provision ranking for content that Yoo (730) has a low preference for or thinks negatively, and raise the content provision ranking for content that Yoo (730) has a high preference for or thinks positively.

[0314] For example, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may lower the content provision ranking for content regarding fears that Yoo (730) has a low preference for or thinks negatively.

[0315] For example, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can increase the content provision ranking for content regarding games that Yoo (730) has a high preference for or thinks positively about.

[0316] For example, the electronic device (100) can determine that keywords related to future events (e.g., travel plans) between the user and people around them are positive keywords or preference keywords.

[0317] For example, if the electronic device (100) is farther away from the user (710) of the electronic device (100) than a predetermined distance, the electronic device (100) may determine the proximity state of the external electronic device as State 1. If the electronic device (100) is closer than a predetermined distance from the user (710) of the electronic device (100), the electronic device (100) may determine the proximity state of the external electronic device as State 2.

[0318] Referring to screen 831, when it is determined to be state 1, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), causing the electronic device (100) to sort and display content based on the user profile of the electronic device (100).

[0319] Referring to screen 832, if it is determined to be state 2, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to sort and display content based on the user profile of the external electronic device.

[0320] FIG. 9 is a diagram illustrating an operation of providing content based on personal information of a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0321] For example, the situation in FIG. 9 may include a user (710) of an electronic device (100) having a travel plan with a user (720) of an external electronic device, and Kim (720)’s profile may include preference information that she dislikes fear-related content and likes dogs, as well as relationship information that she is the daughter of the user (710).

[0322] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can obtain information (950) about a travel destination based on travel destination travel route information (722) stored as a screenshot.

[0323] For example, the electronic device (100) can analyze images such as screenshots based on an AI agent (210), an LVM model, or a vision to text model (940).

[0324] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can determine whether the information (950) about the acquired travel destination corresponds to a place stored in a calendar application and classify it into a to-do item or a tag item among the associated data (or personal information) (930).

[0325] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can identify preference information and non-preference information on Kim (720)'s profile and classify and display images stored in the gallery.

[0326] For example, Kim's (720) associated data (or personal information) (930) may include to-do, preference information and non-preference information.

[0327] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may be able to manage to-do and preference information in Kim's (720) associated data (or personal information) (930) with high priority (922).

[0328] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may be able to manage non-preference information in Kim's (720) associated data (or personal information) (930) with a low priority (912).

[0329] Referring to the 911 screen, the gallery of the user (710) of the electronic device (100) may display images (912) related to airplanes, swimming, a lecturing teacher, and horror games in a storage order. When a person with a nearby profile is not found, the instructions stored in memory (120) can cause the electronic device (100) to display images in a storage order when executed individually or collectively by at least one processor (110).

[0330] Referring to screen 912, when a person with a nearby profile (e.g., Kim (720)) is found, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), causing the electronic device (100) to change the order of images displayed in the gallery based on to-do, preference information, and non-preference information. For example, when a person with a nearby profile (e.g., Kim (720)) is found, the electronic device (100) can lower the exposure ranking of images related to horror games (912) in the gallery and raise the exposure ranking of images related to dogs (923) to display the images.

[0331] FIG. 10 is a diagram illustrating the operation of generating content based on personal information of a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0332] In one embodiment, when no surrounding person is detected, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to generate content based on at least one of the user's commands or the user's personal information.

[0333] For example, when no surrounding person is detected, the electronic device (100) may receive a user command from the user (710) of the electronic device (100), such as “make a Halloween character and related image” (1001). Based on the user command, such as “make a Halloween character and related image” (1001), the electronic device (100) may generate an image (1010) containing a scary Halloween character and provide the user with information about the generated content in text. For example, the information about the generated content may include information such as “I made a character holding a Halloween pumpkin (1011).”

[0334] In one embodiment, when a person nearby is detected, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to generate content based on the user's commands and personal information about the user of the external electronic device.

[0335] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to transmit personal information about a user of an external electronic device to an AI agent (210) when executed individually or collectively by at least one processor (110).

[0336] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to transmit personal information about the user of an external electronic device as input to the AI ​​agent (210) (e.g., reflected in a prop) when executed individually or collectively by at least one processor (110).

[0337] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to enable the AI ​​agent (210) to generate content based on personal information about the user of the external electronic device when executed individually or collectively by at least one processor (110).

[0338] In one embodiment, when a person nearby is detected, the electronic device (100) can confirm that Kim (720) is present near the electronic device (100). If Kim (720) is the daughter of the user (710) of the electronic device (100) who dislikes scary things, instructions stored in memory (120) based on Kim (720)'s preference can cause the electronic device (100) to generate a hidden prompt (e.g., not scary) (1002) when executed individually or collectively by at least one processor (110).

[0339] In one embodiment, instructions stored in memory (120) can cause the electronic device (100) to generate an image (1020) containing a non-frightening Halloween character based on a user's command and a hidden prompt when executed individually or collectively by at least one processor (110).

[0340] In one embodiment, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to provide information to the user regarding content created as text. For example, information regarding content created may include information such as “I made a cute character holding a Halloween pumpkin (1012).”

[0341] FIG. 11 is a diagram illustrating the operation of generating content based on personal information of a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0342] In one embodiment, when no surrounding person is detected, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to generate content based on at least one of the user's commands or the user's personal information.

[0343] For example, when no surrounding person is detected, the electronic device (100) may receive a user command from the user (710) of the electronic device (100), such as “make a story for a lullaby” (1131). Based on the user command, such as “make a story for a lullaby” (1001), the electronic device (100) may generate and provide a story (1110) preferred by the user (710).

[0344] In one embodiment, when a person nearby is detected, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to generate content based on the user's commands and personal information about the user of the external electronic device.

[0345] In one embodiment, when a person nearby is detected, the electronic device (100) can confirm that Kim (720) is present near the electronic device (100). If Kim (720) is the daughter of the user (710) of the electronic device (100) who likes dogs, instructions stored in memory (120) based on Kim (720)'s lead can cause the electronic device (100) to generate a hidden prompt (e.g., on the subject of dogs) (1132) when executed individually or collectively by at least one processor (110).

[0346] In one embodiment, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can generate and provide a lullaby story (1120) with a puppy theme based on a user's command and a hidden prompt.

[0347] FIG. 12 is a diagram illustrating the operation of recreating content based on personal information of a user of an external electronic device in an electronic device (100) according to one embodiment of the present disclosure.

[0348] In one embodiment, when a person nearby is detected, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to regenerate content based on the user's commands and personal information about the user of the external electronic device.

[0349] For example, actual image data (1210) may include the act of drinking alcohol. If preference / non-preference information indicating that a person (720) of the user (710) dislikes the act of drinking alcohol is included in the personal information of the person (720), the electronic device (100) may reprocess the actual image data (1210) including the act of drinking alcohol.

[0350] In one embodiment, in operation 1230, instructions stored in memory (120) can cause the electronic device (100) to regenerate an image (1220) including the act of drinking coffee based on the personal information of a person (720) of a person with a preference / non-preference for disliking the act of drinking alcohol, when executed individually or collectively by at least one processor (110).

[0351] For example, the person and place included in the image (1220) containing the act of drinking coffee are the same as those included in the actual image data (1210) containing the act of drinking alcohol, and the behavior of the person or the atmosphere of the place may be changed.

[0352] FIG. 13 is a diagram showing the notification operation of an electronic device (100) when a person nearby approaches according to one embodiment of the present disclosure.

[0353] In one embodiment, the electronic device (100) may include an edge light (1310) positioned at the corner of the display (140).

[0354] For example, the gallery of the user (710) of the electronic device (100) may display images related to airplanes, swimming, a lecturing teacher, and horror games in a stored order. When a person with a nearby profile is not found, the instructions stored in memory (120) may cause the electronic device (100) to display images (1321) in a stored order when executed individually or collectively by at least one processor (110). At this time, the edge light (1310) may not be turned on.

[0355] For example, when a person with a profile in the vicinity is searched, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to expose an image (1322) based on the personal information of the person (720, 730).

[0356] In one embodiment, when a person (720, 730) with a profile in the vicinity is searched, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to provide a notification based on wireless connection information.

[0357] In an embodiment, when a person (720, 730) with a profile in the vicinity is searched, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify the location corresponding to the person (720, 730) based on the difference in signal reception time through the Angle of Arrival (AoA) of a sensor such as UWB, or the signal difference (jitter) between communication antennas. Under the control of the processor (110), the electronic device (100) can control the edge light (1310) based on the identified location to display a notification (1311, 1312).

[0358] FIG. 14 is a diagram illustrating the operation of an electronic device (100) according to one embodiment of the present disclosure providing content based on geographical information.

[0359] In one embodiment, when there is no data (1440) associated with geographical information, instructions stored in memory (120) can cause the electronic device (100) to display images (1411) in a storage order when executed individually or collectively by at least one processor (110).

[0360] In one embodiment, the data (1440) associated with geographical information may include information about places frequently visited or places frequently stayed (e.g., home, workplace).

[0361] In one embodiment, when the detected geographical information matches the house information of the associated data (1440) (1420), the instructions stored in the memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to display images (1421) by arranging images stored in a gallery application based on personal information (e.g., preference / non-preference information) of a person (e.g., family) associated with the house.

[0362] For example, when the detected geographical information matches the house information of the associated data (1440) (1420), the instructions stored in memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to expose more images related to the house and less images unrelated to the house.

[0363] For example, when the detected geographical information matches the house information of the associated data (1440) (1420), the instructions stored in the memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to expose more images related to family members and less images unrelated to family members.

[0364] In one embodiment, when the detected geographical information matches the work information of the associated data (1440) (1430), the instructions stored in the memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to display images (1431) by arranging images stored in a gallery application based on personal information (e.g., preference / non-preference information) of a person (e.g., work colleague) associated with the home.

[0365] In one embodiment, using image-related data information included in the metadata (e.g., location information) of an image, instructions stored in memory (120) can cause an electronic device (100) to sort images stored in a gallery application when executed individually or collectively by at least one processor (110).

[0366] In one embodiment, using the result information obtained by performing image analysis through an AI agent (210) before displaying an image on a display (140), instructions stored in memory (120) can cause an electronic device (100) to sort images stored in a gallery application when executed individually or collectively by at least one processor (110).

[0367] In one embodiment, image-related data information may include result information of analyzing an image in an electronic device (100).

[0368] For example, image-related data information may include keywords representing information about objects or people contained in the image.

[0369] For example, image-related data information may include 'caption information expressing the mood or context of the image,' which is result information generated using an AI agent (210).

[0370] For example, when the detected geographical information matches the workplace information of the associated data (1440) (1420), the instructions stored in the memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to expose more images related to the workplace and less images unrelated to the workplace.

[0371] For example, when the detected geographical information matches the work information of the associated data (1440) (1420), the instructions stored in memory (120), when executed individually or collectively by at least one processor (110), can cause the electronic device (100) to expose more images related to work colleagues and less images unrelated to work colleagues.

[0372] In one embodiment, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to enable the electronic device (100) to detect wireless connectivity between devices and determine whether an external electronic device is present in the vicinity of the electronic device (100).

[0373] In one embodiment, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to determine whether an external electronic device is present around the electronic device (100) through a Wi-Fi beacon frame.

[0374] For example, a beacon frame is a broadcasting packet sent from the AP about 10 times per second, providing information about the AP and various communication parameters of the cell under the AP's jurisdiction. The electronic device (100) can check the station count within the QBSS load element in the beacon frame and, if it is determined that the number of existing connected devices has increased, detect that a person has entered the space and perform a change in the content display.

[0375] FIG. 15 is a diagram showing the operation of an electronic device (100) according to one embodiment of the present disclosure confirming geographical information from an SSID.

[0376] FIG. 16 is a diagram showing an operation in which an electronic device (100) according to one embodiment of the present disclosure changes the exposure of content based on geographical information.

[0377] In FIG. 15, the electronic device (100) may display a user interface (1510) regarding Wi-Fi settings on a display (140). The user interface (1510) regarding Wi-Fi settings may include a user interface (91511) regarding Wi-Fi connection on / off and an interface (1512) for displaying an SSID regarding the connected AP.

[0378] In one embodiment, the electronic device (100) can check the currently connected Wi-Fi information. For example, in public places, public Wi-Fi is generally used, and the name of the Wi-Fi is recorded in the SSID.

[0379] In one embodiment, the electronic device (100) can determine whether the current location is a public place or a non-public place by using an AI agent (210) that infers the location based on the SSID name of the Wi-Fi.

[0380] For example, most public Wi-Fi networks, such as those in cafes, subways, and buses, display the business name or whether it is public in the SSID to make it easy to find the AP.

[0381] In one embodiment, the electronic device (100) can estimate that it is a public place even when the channel utilization is higher than a specified value and the station count changes significantly more than a specified value through a beacon frame using an AI agent (210).

[0382] In FIG. 16, when geographical information is determined to be a public place, instructions stored in memory (120) can be set so that the electronic device (100) does not display highly sensitive information (or content) when executed individually or collectively by at least one processor (110).

[0383] For example, in the case of a quiet cafe even in a public place (1620), there is less need to change the content display level because there is less chance of others seeing my device. In the case of a quiet cafe (1620), the channel utilization through the beacon frame can be 0~10%.

[0384] For example, in the case of a crowded public place like a subway (1630), other people can easily observe the user's device, so there is a greater need to mask sensitive information. In the case of a crowded subway (1630), the channel utilization rate through the beacon frame can be 90-100%.

[0385] In one embodiment, when there is no data (1640) associated with geographical information, instructions stored in memory (120) can cause the electronic device (100) to display images (1611) in a storage order when executed individually or collectively by at least one processor (110).

[0386] In one embodiment, when geographical information is determined to be a public place, instructions stored in memory (120) can cause the electronic device (100) to change sensitivity and display content when executed individually or collectively by at least one processor (110).

[0387] For example, in the case of a quiet cafe (1620) even if it is a public place, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) determines that there is a low need to change the content display level and can expose an image (1621) containing sensitive information.

[0388] For example, in the case of a crowded public place subway (1630), instructions stored in memory (120), when executed individually or collectively by at least one processor (110), cause the electronic device (100) to determine that it must block highly sensitive information and expose an image (1631) that does not contain sensitive information.

[0389] FIG. 17 is a diagram illustrating an operation of displaying content when the electronic device (100) according to an embodiment of the present disclosure is an electronic device including a multi-foldable form factor. However, it is not limited thereto, and the electronic device (100) may include at least one of a bar-type form factor, a foldable form factor, and a multi-foldable form factor.

[0390] In FIG. 17, the electronic device (100) can be connected to a wearable device (1701), such as a VST (video see-through) device or AI glasses.

[0391] In one embodiment, the wearable device (1701) may include a device that allows the user to obtain information about the current field of vision, such as a VST (video see-through) device or AI glasses.

[0392] In one embodiment, when a user (710) is wearing a wearable device (1701), the electronic device (100) can detect the approach of an external electronic device by checking a voice signal. The electronic device (100) can obtain a voice signal through an acoustic device (e.g., a microphone) included in the electronic device (100). Based on whether the voice signal corresponds to the voice of the user of the external electronic device, the electronic device (100) can detect the approach of an external electronic device by checking the voice signal. The electronic device (100) can obtain a voice signal through an acoustic device (e.g., a microphone) included in the wearable device (1701). When a user is wearing a wearable device (1701), the electronic device (100) can detect the approach of an external electronic device by checking communication information.

[0393] In one embodiment, the electronic device (100) may store personal information (or, profile) (721) about the person by analyzing the voice signal of the person (720) in advance. If the personal information (or, profile) (721) about the person by analyzing the voice signal of the person (720) in advance is stored, then even if the person accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby causing the electronic device (100) to generate content based on the personal information, user commands, and geographical information of the person (720).

[0394] In one embodiment, if personal information (or profile) (721) regarding a person (720) is stored by analyzing the voice signal of the person (720) in advance, even if the person (720) accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can cause the electronic device (100) to regenerate content based on the personal information, user commands, and geographical information of the person (720) when executed individually or collectively by at least one processor (110).

[0395] In one embodiment, if personal information (or profile) (721) regarding a person (720) is stored by analyzing the voice signal of the person (720) in advance, even if the person (720) accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can be executed individually or collectively by at least one processor (110), thereby enabling the electronic device (100) to provide content based on the personal information, user commands, and geographical information of the person (720).

[0396] In one embodiment, if personal information (or profile) of a person (720) is stored by analyzing the voice signal of the person (720) in advance, even if the person (720) accesses the electronic device (100) without accompanying an external electronic device, the instructions stored in the memory (120) can cause the electronic device (100) to sort content based on the personal information, user commands, and geographical information of the person (720) when executed individually or collectively by at least one processor (110).

[0397] In one embodiment, in operation 1721, when the user (710) is wearing the electronic device (100), instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), causing the electronic device (100) to display scene information on the display (140) based on an image obtained through the wearable device (1701).

[0398] In one embodiment, in operation 1721, when the user (710) is wearing the electronic device (100), the instructions stored in the memory (120) are executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify whether a person in the vicinity is located in a certain direction relative to the electronic device, is in a close position, or is looking toward the user, based on an image or video information obtained through the wearable device (1701), thereby changing the method of displaying content within the electronic device (100). For example, the electronic device (100) can identify the surroundings and display or generate content based on an image or video information obtained through the wearable device (1701) without voice information.

[0399] In one embodiment, in operation 1721, when the user (710) is equipped with the electronic device (100), instructions stored in memory (120) can cause the electronic device (100) to display scene information on the display (140) when executed individually or collectively by at least one processor (110).

[0400] In one embodiment, in operation 1722, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to identify a person (720) within the field of view of the wearable device (1701) based on scene information using an AI agent (210).

[0401] In one embodiment, in operation 1723, instructions stored in memory (120) can cause the electronic device (100) to retrieve personal information (or, profile information) (721) about a specific person (720) when executed individually or collectively by at least one processor (110).

[0402] In one embodiment, in operation 1723, instructions stored in memory (120) can cause the electronic device (100) to identify personal information (or, profile information) (721) about a specific person (720) when executed individually or collectively by at least one processor (110).

[0403] In one embodiment, in operation 1723, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), allowing the electronic device (100) to subsequently check whether a situation in which a person is located near the electronic device (100) is recognized.

[0404] In one embodiment, when a situation is recognized where a person (720) is located near the electronic device (100), in operation 1723, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110) to allow the electronic device (100) to recognize the location status of the person from the scene.

[0405] In one embodiment, in operation 1725, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) may determine an area to display / generate preferred content of a person based on the location state of a recognized person, and a display area (1711) close to the person.

[0406] For example, the electronic device (100) may include display areas (1711, 1712, 1713) that virtually divide the display (140) into three parts.

[0407] For example, when a person comes and sits on the left side of the electronic device (100), instructions stored in memory (120) are executed individually or collectively by at least one processor (110), causing the electronic device (100) to display / generate content (1721) preferred by the person in the left display area (1711) and content (1723) based on the user's preference of the electronic device (100) to be generated / displayed in the opposite area (or, right display area (1713)).

[0408] FIG. 18 is a drawing illustrating a content provision operation when an electronic device (100) according to one embodiment of the present disclosure includes a foldable or multi-foldable housing.

[0409] For example, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can use an AI agent (210) to recognize the state of the housing and determine a method to provide content based on the recognized state of the housing.

[0410] Referring to screen 1801, when instructions stored in memory (120) are executed individually or collectively by at least one processor (110), the electronic device (100) can recognize that the housing is fully unfolded.

[0411] When the recognized state of the housing is recognized as being fully unfolded, the instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), causing the electronic device (100) to determine that there is a low likelihood of attracting the attention of others.

[0412] In an embodiment, if it is determined that there is a low likelihood of attracting the attention of others, the instructions stored in memory (120) can cause the electronic device (100) to further expose sensitive content when executed individually or collectively by at least one processor (110).

[0413] Referring to screen 1802, if the recognized housing state is recognized as being partially folded (e.g., flex mode), the instructions stored in memory (120) can cause the electronic device (100) to determine that it is likely to attract the attention of others when executed individually or collectively by at least one processor (110).

[0414] In one embodiment, when it is determined that there is a high likelihood of attracting the attention of others, instructions stored in memory (120) can be executed individually or collectively by at least one processor (110), thereby allowing the electronic device (100) to expose sensitive content less.

[0415] FIG. 19 is a diagram illustrating a method in which a user (710) of an electronic device (100) and a user (720) of an external electronic device, according to one embodiment of the present disclosure, use the same cloud server (e.g., Samsung Cloud Server) to identify a person nearby (720) and share personal information.

[0416] Referring to screen 1901, the electronic device (100) can display information about a person (720) using the same cloud server (e.g., Samsung Cloud Server) on a sharing interface (1910) and display a user interface (1911) for a person (720) selected by the user. Upon receiving user input (1913) for the user interface (1911), the electronic device (100) can share personal information with an external electronic device owned by the person (720).

[0417] Referring to screen 1903, the electronic device (100) displays information about a person (720) using the same cloud server (e.g., Samsung Cloud Server) on a sharing interface (1920), and upon receiving user input (1914) regarding the selection of a person, the electronic device (100) can share personal information with an external electronic device owned by the person (720).

[0418] In one embodiment, in operation 1931, the electronic device (100) may broadcast a packet to a nearby network to recognize a person (720). The information included in the packet may include some information of a user fingerprint assigned through a cloud server account (e.g., Samsung account) and hash information of the packet sender.

[0419] In one embodiment, in operation 1932, an external electronic device (or packet receiving device) of a peripheral person (720) receives the broadcast packet, compares the sender's cloud server account information (e.g., Samsung account) within the packet with the information stored in the cloud server (e.g., Samsung Cloud Server), and compares a part of the hash value of the phone number with the hash values ​​of the numbers in the recipient's local phone number to confirm the relationship with the electronic device (100).

[0420] In one embodiment, in the 1932 operation, if the corresponding hash information exists in the external electronic device (or packet receiving device) of the peripheral person (720), the external electronic device (or packet receiving device) of the peripheral person (720) can transmit a response to the electronic device (e.g., packet sending device) (100).

[0421] In one embodiment, through packet exchange, an external electronic device (or packet receiving device) of an electronic device (100) and a person (720) can determine whether there is a target (e.g., object, person, purpose or preference) that has a specific relationship with itself nearby, and the electronic device (100) can retrieve a previously stored profile for a specific person.

[0422] FIG. 20 is a block diagram of an electronic device (2001) in a network environment (2000) according to various embodiments.

[0423] The electronic device (2001) of FIG. 20 may include components identical or similar to the electronic device (100) of FIG. 1. In describing the electronic device (2001) of FIG. 20, components identical or similar to the electronic device (100) of FIG. 1 may be replaced with the description of the electronic device (100) of FIG. 1.

[0424] Referring to FIG. 20, in a network environment (2000), an electronic device (2001) may communicate with an electronic device (2002) through a 20th network (2098) (e.g., a short-range wireless communication network) or with at least one of an electronic device (2004) or a server (2008) through a 2nd network (2099) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (2001) may communicate with the electronic device (2004) through a server (2008). According to one embodiment, the electronic device (2001) may include a processor (2020), memory (2030), input module (2050), sound output module (2055), display module (2060), audio module (2070), sensor module (2076), interface (2077), connection terminal (2078), haptic module (2079), camera module (2080), power management module (2088), battery (2089), communication module (2090), subscriber identification module (2096), or antenna module (2097). In some embodiments, at least one of these components (e.g., connection terminal (2078)) may be omitted from the electronic device (2001), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (2076), camera module (2080), or antenna module (2097)) may be integrated into a single component (e.g., display module (2060)).

[0425] The processor (2020) can, for example, execute software (e.g., program (2040)) to control at least one other component (e.g., hardware or software component) of the electronic device (2001) connected to the processor (2020) and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (2020) can store commands or data received from other components (e.g., sensor module (2076) or communication module (2090)) in volatile memory (2032), process the commands or data stored in volatile memory (2032), and store the resulting data in non-volatile memory (2034). According to one embodiment, the processor (2020) may include a main processor (2021) (e.g., a central processing unit or an application processor) or an auxiliary processor (2023) that can operate independently or together with it (e.g., a graphics processing unit, a neural processing unit (NPU), a secure processing unit (SPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if the electronic device (2001) includes a main processor (2021) and an auxiliary processor (2023), the auxiliary processor (2023) may be configured to use less power than the main processor (2021) or to be specialized for a specified function. The auxiliary processor (2023) may be implemented separately from the main processor (2021) or as part thereof.

[0426] The auxiliary processor (2023) may control at least some of the functions or states associated with at least one component of the electronic device (2001) (e.g., display module (2060), sensor module (2076), or communication module (2090)) on behalf of the main processor (2021) while the main processor (2021) is in an inactive (e.g., sleep) state, or together with the main processor (2021) while the main processor (2021) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (2023) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (2080) or communication module (2090)). According to one embodiment, the auxiliary processor (2023) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (2001) itself where the artificial intelligence is performed, or through a separate server (e.g., server (2008)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network (DQN), or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0427] The memory (2030) can store various data used by at least one component of the electronic device (2001) (e.g., a processor (2020) or a sensor module (2076)). The data may include, for example, input data or output data for software (e.g., a program (2040)) and related commands. The memory (2030) may include volatile memory (2032) or non-volatile memory (2034).

[0428] The program (2040) may be stored as software in memory (2030) and may include, for example, an operating system (2042), middleware (2044), or an application (2046). One or more related applications may form a service configured to handle a series of user requests.

[0429] The input module (2050) can receive commands or data to be used for a component of the electronic device (2001) (e.g., processor (2020)) from outside the electronic device (2001) (e.g., user). The input module (2050) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0430] The sound output module (2055) can output a sound signal to the outside of the electronic device (2001). The sound output module (2055) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0431] The display module (2060) can visually provide information to an external (e.g., user) of the electronic device (2001). The display module (2060) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (2060) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0432] The audio module (2070) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (2070) can acquire sound through an input module (2050) or output sound through an audio output module (2055) or an external electronic device (e.g., electronic device (2002)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (2001).

[0433] The sensor module (2076) can detect the operating state of the electronic device (2001) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (2076) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0434] The interface (2077) may support one or more specified protocols that can be used for the electronic device (2001) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (2002)). According to one embodiment, the interface (2077) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0435] The connection terminal (2078) may include a connector through which the electronic device (2001) can be physically connected to an external electronic device (e.g., electronic device (2002)). According to one embodiment, the connection terminal (2078) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0436] The haptic module (2079) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that can be perceived by the user through tactile or kinesthetic senses. According to one embodiment, the haptic module (2079) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0437] The camera module (2080) can capture still images and video. According to one embodiment, the camera module (2080) may include one or more lenses, image sensors, image signal processors, or flashes.

[0438] The power management module (2088) can manage power supplied to the electronic device (2001). According to one embodiment, the power management module (2088) may be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0439] The battery (2089) can supply power to at least one component of the electronic device (2001). According to one embodiment, the battery (2089) may include, for example, a non-rechargeable secondary battery, a rechargeable secondary battery, or a fuel cell.

[0440] The communication module (2090) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (2001) and an external electronic device (e.g., electronic device (2002), electronic device (2004), or server (2008)), and the performance of communication through the established communication channel. The communication module (2090) may include one or more communication processors that operate independently of the processor (2020) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (2090) may include a wireless communication module (2092) (e.g., cellular communication module, short-range wireless communication module, or global navigation satellite system (GNSS) communication module) or a wired communication module (2094) (e.g., local area network (LAN) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (2004) via a 20 network (2098) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a 2 network (2099) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (2092) can identify or authenticate the electronic device (2001) within a communication network such as the 20 network (2098) or the 2 network (2099) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (2096).

[0441] The wireless communication module (2092) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. The NR access technology can support enhanced mobile broadband (Embb), massive machine type communications (mMTC), or ultra-reliable and low-latency communications (URLLC). The wireless communication module (2092) can support high-frequency bands (e.g., mmWave bands) to achieve high data transmission rates, for example. The wireless communication module (2092) can support various technologies for securing performance in high-frequency bands, for example, beamforming, multiple-input and multiple-output (massive MIMO), full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, or large-scale antennas. The wireless communication module (2092) can support various requirements specified in the electronic device (2001), an external electronic device (e.g., electronic device (2004)), or a network system (e.g., a second network (2099)). According to one embodiment, the wireless communication module (2092) can support a Peak data rate (e.g., 20 Gbps or higher) for eMBB realization, loss coverage (e.g., 2064 dB or lower) for mMTC realization, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or lower, or round trip 20 ms or lower) for URLLC realization.

[0442] An antenna module (2097) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (2097) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (2097) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a 20th network (2098) or a 2nd network (2099), may be selected from the plurality of antennas, for example, by a communication module (2090). A signal or power may be transmitted or received between the communication module (2090) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (2097).

[0443] According to one embodiment, the antenna module (2097) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a 20th surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a 2nd surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0444] At least some of the above components can be connected to each other and exchange signals (e.g., commands or data) through a communication method between peripheral devices (e.g., bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI).

[0445] According to one embodiment, commands or data may be transmitted or received between an electronic device (2001) and an external electronic device (2004) through a server (2008) connected to a second network (2099). Each of the external electronic devices (2002, or 2004) may be the same or a different type of device as the electronic device (2001). According to one embodiment, all or part of the operations performed on the electronic device (2001) may be performed on one or more of the external electronic devices (2002, 2004, or 2008). For example, if the electronic device (2001) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (2001) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least a part of the requested function or service, or additional functions or services related to the request, and transmit the result of the execution to the electronic device (2001).

[0446] The electronic device (2001) may provide the above result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (2001) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (2004) may include an Internet of Things (IoT) device. The server (2008) may be an intelligent server using machine learning or a neural network. According to one embodiment, the external electronic device (2004) or the server (2008) may be included within a second network (2099). The electronic device (2001) may be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0447] FIG. 21 is a generative artificial intelligence (AI) system (2100) according to one embodiment. Referring to FIG. 21, the generative AI system (2100) may include a User Interface (2110), an AI Framework (2120), a Generative AI Model (2130), a Knowledge Repository (2140), and an Application / Service Module (2150). These components may be operated on one or more of an electronic device (2001), an external electronic device (2002 or 2004), or a server (2008). For example, the User Interface (2110) and the AI ​​Framework (2120) may be operated on the electronic device (2001), and the Knowledge Repository (240) and the Generative AI Model (2130) may be operated on the server (2008).

[0448] According to one embodiment, the User Interface (2110) may receive user input (e.g., user query). User input may be received in the form of text, images, voice (e.g., natural language), video, menu selection, or a combination thereof. The User Interface (2110) may include various context information (e.g., running application or user location) related to the generative artificial intelligence system (2100) at the time the user input is received, in addition to or instead of the user input. The User Interface (2110) may provide the user input or the context information to the AI ​​Framework (2120) and provide the result of processing therefrom to the user, for example, through the AI ​​Framework (2120). According to one embodiment, in addition to user input, the electronic device may provide context information obtained using information included on the screen to the AI ​​Framework (2120). The result may be provided in the form of text, images, voice, video, an action requested by the user (e.g., launching a specified function or app), or a combination thereof.

[0449] According to one embodiment, the AI ​​Framework (2120) can identify (e.g., estimate) a user intent based on at least part of user input or context information received from the User Interface (2110), control each of the relevant modules (e.g., 2121, 2123, or 2125) to perform a function or action corresponding to the identified user intent, and coordinate collaboration between two or more modules. The AI ​​Framework (2120) may include a Prompt Design Module (2121), an API / Plug-in Management Module (2123), and an Output Modification Module (2125), as illustrated in FIG. 21.

[0450] According to one embodiment, the Prompt Design Module (2121) can generate a prompt to be input to the Generative AI Model (2130) based at least partially on user input or context information received from the User Interface (2110). For example, the Prompt Design Module (2121) can generate a prompt using user preferences, a prompt library, or prompt examples stored in the Knowledge Repository (2140) based at least partially on user input or context information.

[0451] According to one embodiment, the API / Plug-in Management Module (2123) may communicate, for example, via an API, with various resources (e.g., Knowledge Repository (2140)) that provide said additional information when there is a request for said additional information in relation to user input. Additionally or generally, when a specified action (e.g., function, app, or service) is performed in response to said user input, the API / Plug-in Management Module (2123) may request the Application / Service Module (2150) to perform said specified action via a corresponding API. The API / Plug-in Management Module (2123) may provide information obtained from the Knowledge Repository (2140), the Application / Service Module 2150, or another external resource to the Prompt Design Module (2121). That obtained information may be used by the Prompt Design Module (2121) to generate a prompt along with the user input, or provided to a generative AI model (2130).

[0452] According to one embodiment, the Output Modification Module (2125) can fine-tune the results obtained through the Generative AI Model (2130) as at least part of the response to user input (e.g., user query). For example, the Output Modification Module (2125) can determine whether the content of the response obtained through the Generative AI Model (2130) is appropriate as a response to a request made by the user input. For example, the Output Modification Module (2125) can determine the degree of relevance, degree of bias (e.g., political or social bias), or degree of harmfulness (e.g., sexual or profanity) of the difference between the response obtained through the Generative AI Model (2130) and the user input. Additionally or generally, the Output Modification Module (225) can request that additional AI processing be performed on the obtained response, or provide the user with a hint to avoid unwanted output. For example, additional prompts can be generated through the Prompt Design Module to obtain a response again through the Generative AI Model (2130).

[0453] According to one embodiment, the Generative AI Model (2130) may form at least part of an artificial intelligence neural network and may include a model that generates images or a model that generates language. The image generation model may include, for example, a generative adversarial network (GAN), a variational autoencoder (VAE), or a Diffusion-based model using a VAE and a Transformer. The language generation model may include, for example, a large language model (LLM), a large multimodal model (LMM), a large vision model (LVM), or a large action model (LAM). The LAM may automatically generate actions for an environment (e.g., a robot, a car, an electronic device (2001), or a program (2040)). Additionally, for at least some AI models (e.g., LLM), there may be a low-rank adaptation (LoRA) adaptor that is fine-tuned for, for example, a specific task or a specific situation.

[0454] FIG. 22 illustrates an AI Framework (2120) having on-device AI processing capabilities according to one embodiment. In this case, the AI ​​Framework (2120) may generate and learn a response to the user input using resources within the device, instead of sending the user input received through a User Interface (2110) operating on the same device (e.g., electronic device (2001)) to a Generative AI Model (2130) operating on an external electronic device (e.g., server (2008)), or additionally. Referring to FIG. 22, the AI ​​Framework (2120) may include a Cross-Application Action Module (2210), a Personal Data Managing Module (2230), an On-device AI Model (2250), and an Orchestration Module (2270).

[0455] According to one embodiment, the Cross-Application Action Module (2210) determines one or more additional applications required for the operation of an executed application (e.g., an assistant app) and may link or suggest operations between the app and at least one additional application, or between multiple additional applications. For example, the Cross-Application Actions Module (2210) may execute one or more additional applications to be used to respond to a user request through the assistant app sequentially or at least partially, simultaneously. Additionally, the Cross-Application Action Module (2210) may communicate with the additional applications so that the result of the execution of one additional application (e.g., content) can be shared with other additional applications.

[0456] According to one embodiment, the Personal Data Managing Module (2230) may provide personal information (e.g., schedule, contact, or message information) about a user of the application (e.g., assistant app) or the additional application running on the device (e.g., electronic device 2001) or other related individuals (e.g., family or friends) to another module of the AI ​​Framework (2120) or a related module (e.g., Generative AI Model 2130) running on another device.

[0457] According to one embodiment, the on-device AI model (2250) may include at least one model among one or more AI models (e.g., GAN, VAE, LLM, LMM, LVM, or LAM) operated on an external electronic device (e.g., server (2008)) or a corresponding lightweight AI model. Additionally, for said model or said lightweight model, there may be, for example, a LoRA adaptor.

[0458] According to one embodiment, the Orchestration Module (2270) may select one or more AI models to be used to obtain a response to user input (e.g., user query). For example, the Orchestration Module (2270) may select one or more AI models from among an On-Device AI Model (2250), an AI model operating on an external electronic device (e.g., a server (2008)) (e.g., a Generative AI Model (2130)), or a third AI model (not shown) operating on another external electronic device. If multiple AI models are selected, the Orchestration Module (2270) may communicate with the selected models or devices so that the operation between the selected AI models and the processing of the results thereof can be coordinated between the relevant models or devices.

[0459] According to one embodiment, two or more modules of a generative AI system (2100) (e.g., Cross-Application Action Module (2210) and Orchestration Module (2270)) may be implemented as a single module to maintain the same functionality. Various variations are possible.

[0460] In one embodiment, the electronic device (100) includes a display (140), a communication circuit (160), at least one processor (110), and a memory (120) for storing instructions, and when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may acquire communication information, identify external electronic devices or geographical information around the electronic device (100) based on the communication information, identify personal information related to the identified external electronic devices, create content based on at least one of user commands for content creation, personal information, or geographical information, and provide the created content.

[0461] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may generate personal information based on at least one of text information, image information, voice information, or video information related to an identified external electronic device user stored in memory (120).

[0462] In one embodiment, when instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may generate content based on at least one of user commands or geographical information, provided that there is an identified external electronic device corresponding to personal information.

[0463] In one embodiment, when instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may display a graphic element associated with an identified external electronic device on a display (140).

[0464] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may generate personal information including at least one of relationship information with the user of the electronic device (100) or preference information of the user of the identified external electronic device based on at least one of text information, image information, voice information, or video information related to the user of the identified external electronic device stored in memory (120).

[0465] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may determine the display priority of the content stored in the memory (120) based on personal information and display the stored content on the display (140) based on the determined priority.

[0466] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may identify keywords included in personal information and generate content based on the keywords and user commands.

[0467] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may display an indicator on an edge light corresponding to the direction of the identified external electronic device when the identified external electronic device corresponding to the personal information approaches.

[0468] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may be made to communicate with a wearable device and display content created in correspondence with field of view (FOV) information obtained through the wearable device.

[0469] In one embodiment, when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may generate a prompt based on at least one of the acquired communication information or personal information related to an external electronic device and transmit it as an input value to an AI agent.

[0470] In one embodiment, a method for providing content of an electronic device (100) may include the operation of acquiring communication information, the operation of identifying an external electronic device or location information around the electronic device (100) based on the communication information, the operation of identifying personal information related to the identified external electronic device, the operation of creating content based on at least one of a user command for content creation, personal information, or geographical information, and the operation of providing the created content.

[0471] In one embodiment, the content provision method of the electronic device (100) may further include an operation of generating personal information based on at least one of text information, image information, or voice information related to a user of an identified external electronic device stored in memory (120).

[0472] In one embodiment, the method of providing content of an electronic device (100) may further include an operation of generating content based on at least one of user commands or geographical information, if there is an identified external electronic device corresponding to personal information.

[0473] In one embodiment, the method for providing content of the electronic device (100) may further include the operation of displaying graphic elements related to the identified external electronic device on the display (140).

[0474] In one embodiment, the method for providing content of an electronic device (100) may further include the operation of generating personal information including at least one of relationship information with the user of the electronic device (100) or preference information of the user of the identified external electronic device based on at least one of text information, image information, or voice information related to the user of the identified external electronic device stored in memory (120).

[0475] In one embodiment, the content provision method of the electronic device (100) may include an operation of determining the display priority of content stored in memory (120) based on personal information, and an operation of displaying the stored content on a display (140) based on the determined priority.

[0476] In one embodiment, the electronic device (100) includes a display (140), a communication circuit (160), at least one processor (110), and a memory (120) for storing instructions, and when the instructions are executed individually or collectively by at least one processor (110), the electronic device (100) may establish a connection with an access point (AP) through the communication circuit (160), obtain AP channel information including geographical information and channel utilization information or station count information from the AP through the connection, identify at least one external electronic device using the AP channel information, display a graphic object representing at least one external electronic device based at least partially on the identification through the display (140), identify personal information related to at least one external electronic device in the memory (120), obtain a user command to create content through the display (140), and create content based on the personal information.

[0477] In one embodiment, the content provision method of the electronic device (100) can, when the instructions are executed individually or collectively by at least one processor (110), cause the electronic device (100) to generate personal information using one or more of images, messages, call information and voice information stored in memory (120), obtain identifier information from an external electronic device through a communication circuit (160), and identify the personal information using the identifier information.

[0478] An electronic device according to one embodiment disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiment of this document is not limited to the aforementioned devices.

[0479] The embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0480] As used in one embodiment of this document, the term “module” may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0481] One embodiment of the present document may be implemented as software (e.g., a program) comprising one or more instructions stored in a storage medium (e.g., internal memory) or external memory that is readable by a machine (e.g., an electronic device (100)). For example, a processor (e.g., a processor (110)) of the machine (e.g., an electronic device (100)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0482] According to one embodiment, the method according to one embodiment disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). TM It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0483] According to one embodiment, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to one embodiment, one or more of the components or operations among the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to one embodiment, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device, display; Communication circuit; At least one processor; and It includes memory for storing instructions, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, To obtain communication information, and Based on the above communication information, external electronic devices or geographical information are identified in the vicinity of the electronic device, and Verify personal information related to the aforementioned identified external electronic device, and Creating content based on at least one of user commands for content creation, the personal information, or the geographical information, and An electronic device that enables the provision of the above-mentioned generated content.

2. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that generates personal information based on at least one of text information, image information, voice information, or video information related to the user of the identified external electronic device stored in the memory.

3. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that generates the content based on at least one of the user command or the geographical information, provided that there is an identified external electronic device corresponding to the personal information.

4. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that displays graphic elements related to the aforementioned identified external electronic device on the display.

5. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that generates personal information including at least one of relationship information with the user of the electronic device or preference information of the user of the identified external electronic device, based on at least one of text information, image information, voice information, or video information related to the user of the identified external electronic device stored in the memory.

6. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Based on the above personal information, the display priority of the content stored in the memory is determined, and An electronic device that displays the stored content on the display based on a determined priority.

7. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Check the keywords included in the above personal information, and An electronic device that generates the content based on the above keywords and the above user commands.

8. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, An electronic device that displays an indicator on an edge light corresponding to the direction of the identified external electronic device when the identified external electronic device corresponding to the above personal information approaches.

9. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Connect to and communicate with the wearable device, An electronic device that displays the generated content in correspondence with field of view (FOV) information obtained through the wearable device.

10. In Paragraph 1, When the above instructions are executed individually or collectively by the at least one processor, the electronic device, Generate a prompt based on at least one of the acquired communication information or the personal information associated with the external electronic device, and An electronic device that passes a generated prompt as an input value to an AI agent.

11. In a method for providing content of an electronic device, Operation of acquiring communication information; An operation to identify external electronic devices or location information around the electronic device based on the above communication information; An operation to verify personal information related to the aforementioned identified external electronic device; An action of generating content based on at least one of a user command for content creation, the personal information, or the geographical information; and A method including the operation of providing the above-mentioned generated content.

12. In Paragraph 11, A method further comprising the operation of generating personal information based on at least one of text information, image information, or voice information related to the user of the identified external electronic device stored in the memory.

13. In Paragraph 11, A method further comprising, if there is an identified external electronic device corresponding to the personal information, an operation of generating the content based on at least one of the user command or the geographical information.

14. In Paragraph 11, A method further comprising the operation of displaying graphic elements related to the aforementioned identified external electronic device on the display.

15. In Paragraph 11, A method further comprising the operation of generating personal information including at least one of relationship information with the user of the electronic device or preference information of the user of the identified external electronic device based on at least one of text information, image information, or voice information related to the user of the identified external electronic device stored in the memory.

Images