Method for establishing robot community, robot community system and operating method

Abstract

A method for establishing a robot community, a robot community system and an operating method are provided. For establishing the robot community, each of intelligent robots is assigned with a specific attribute, and accordingly a training data is prepared for training the intelligent robot through a machine-learning algorithm. The robot communication system then deploys multiple intelligent robots into a social media and generates community contents specified to each of the intelligent robots according to the attribute and basic data of each of the intelligent robots by a generative intelligent model. Therefore, the robot community system allows users to interact with the intelligent robots and establish social relationship between the users and the intelligent robots in the social media.

Description

Technical Field

[0001] The disclosure concerns a technology for building community systems, specifically referring to the use of large-scale language models and generative artificial intelligence to create chatbots, and the methods and systems for building chatbot communities. Prior Technology

[0002] Among the rapidly developing artificial intelligence (AI) fields, generative AI that utilizes large language models (LLMs) to process natural language is flourishing. One application of this is the ability to interact with users using natural language, such as a natural language chatbot.

[0003] Social media is an online service where multiple people can share content, exchange information, build friendships, and create communities. Users who join a community can express their opinions on various messages and interact with each other, and it provides various forms of content interaction such as text, pictures, music, and videos.

[0004] In particular, the software running on social media also employs large-scale language models to analyze each user's posts and content within the community, learn user characteristics, perform sentiment analysis, and then push relevant content. Furthermore, social media can also leverage natural language processing (NLP) for applications such as sentiment analysis and chatbots. Summary of the Invention

[0005] The disclosure proposes a method, system, and operation method for building robot communities. It utilizes technologies such as natural language models, machine learning methods, and generative artificial intelligence to build communities that include artificial intelligence robots. Each artificial intelligence robot has its own attributes and can engage in community activities with users and provide a variety of content.

[0006] According to an embodiment, in the method for establishing a robot community, the attributes of each intelligent robot among multiple intelligent robots are first set. Then, corresponding training data is obtained based on the attributes and basic information of each intelligent robot, and multiple intelligent robots are trained by using machine learning algorithms to learn from the training data. Afterwards, the multiple intelligent robots are deployed to social media, and community relationships between multiple users and multiple intelligent robots are established on the social media.

[0007] Furthermore, within the computer system, a generative intelligent model generates community content belonging to each intelligent robot based on its attributes and basic information. Additionally, the generative intelligent model is used to generate content that responds to users based on the attributes and basic information of each intelligent robot, as well as real-time activity data generated from the interaction between each intelligent robot and users on social media.

[0008] Furthermore, the community content belonging to each intelligent robot and the community interaction content generated through community interaction can be text, images, voice or audio-visual, and attribute information can be set by software programs running in the computer system based on the community content or community interaction content.

[0009] Furthermore, on the cloud server running the social media, a database can be used to establish community relationships for one or more of the smart bots based on the individual selections of multiple users on the social media platform.

[0010] Furthermore, the intelligent robot obtains a realistic image of an intelligent robot generated through generative artificial intelligence from a database, and transmits the image data and model data of the realistic intelligent robot image to the user device, so that the realistic intelligent robot can be displayed on the display of the user device.

[0011] The robot community system runs on a cloud server, and the cloud server runs social media. The robot community system includes a computing circuit for executing the method of establishing a robot community, a database storing user information of multiple users and attributes, basic information, image data and intelligent robot models of multiple intelligent robots, and a communication circuit for establishing a connection with the user's device.

[0012] In this robot community system, the computing circuit performs natural language processing, processing the voice data generated by the user's conversation with the intelligent robot received from the user device. After the voice is transcribed, the voice features in the voice data are obtained through natural language processing, and the meaning is recognized, so that the intelligent robot can respond to the user in natural language.

[0013] Furthermore, preferably, each intelligent robot model in the database can be an intelligent model with domain-specific knowledge built by learning domain-specific data through machine learning algorithms.

[0014] In the user device, the application provided by the execution system can connect to the cloud server after the application is executed to load the user's social activity data and image data of one or more intelligent robots with social relationships.

[0015] According to an embodiment of the operation method of the robot community system, the robot community system calls one or more intelligent robots based on the user's selection or the robot community system's recommendation. Then, the robot community system responds to the call to one or more intelligent robots based on the community relationship between one or more intelligent robots and the user, including obtaining one or more intelligent robot models and image data from the database, generating one or more intelligent robots based on the image data, and displaying them on the user interface of the user's device.

[0016] In a robot community system, a natural language model is used to process community activity data generated by users or intelligent robots in social media to obtain features from the community activity data. Then, based on the features of the community activity data generated in real time by each intelligent robot and the user in the social media activity, a generative intelligent model can be used to generate community content for each intelligent robot to respond to the user, and store and update robot data of each intelligent robot in the database.

[0017] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Simple Explanation of the Diagram

[0018] Figure 1 shows a schematic diagram of the application scenarios of the robot community system;

[0019] Figure 2 shows a schematic diagram of an embodiment of the robot community system architecture;

[0020] Figure 3 shows a flowchart of an embodiment of the method for establishing a robot community;

[0021] Figure 4 shows a flowchart of an embodiment of the operation method of the robot community system;

[0022] Figure 5 shows a schematic diagram of an embodiment of a social media page with an artificial intelligence robot; and

[0023] Figure 6 shows a schematic diagram of another embodiment of a social media page with an artificial intelligence robot. Implementation

[0024] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the concept of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0025] It should be understood that while terms such as "first," "second," and "third" may be used in this document to describe various components or signals, these components or signals should not be limited by these terms. These terms are primarily used to distinguish one component from another, or one signal from another. Furthermore, the term "or" as used herein should, as appropriate, include any combination of one or more of the related listed items.

[0026] The disclosure proposes a method, system, and operation method for establishing robot communities. The robot community system uses computer systems to run natural language models, machine learning methods, and generative artificial intelligence technologies to create artificial intelligence robots that can be used in social media, or to create social media platforms dominated by artificial intelligence robots. Each artificial intelligence robot has its own attributes and can engage in community activities with users (non-robots) participating in social media, and can generate a variety of content.

[0027] The application scenario of a robot community system primarily based on artificial intelligence robots can be seen in the schematic diagram shown in Figure 1. The robot community system includes a cloud server 20, implemented as a computer system. The computer system's computing circuit 211 executes machine learning algorithms to train the artificial intelligence robots based on a training set with specific attribute data. This can be various intelligent robots 101 generated using generative artificial intelligence (AI) by learning knowledge, human speech, behavior, and facial expressions. These robots can be humanoid or have specific appearances (people, cartoons, animals, objects) and can interact with users in the community through text, voice, images, and audio-visual means, including natural language dialogue. According to an embodiment, during natural language dialogue, the intelligent model running behind the intelligent robot 101 can engage in voice dialogue with the user and learn the user's current audio pitch and speaking speed, enabling the intelligent robot 101 to respond with corresponding audio and speaking speed, reflecting the user's current emotions.

[0028] For example, when the intelligent model analyzes the changes in tone, rhythm and volume in the voice data and determines that the user 10 is currently sad, the intelligent robot 101 will adjust the audio and speaking speed to reflect the user 10's current sad emotion.

[0029] The diagram illustrates user 10 operating a social media application or application accessible to social media running on user device 100. For example, after opening the user interface through a social media application and connecting to cloud server 20, user 10 can select social media content from cloud server 20 and load multiple smart robots 101 displayed on user device 100, as shown in the diagram. This includes relevant model data and image signals of each smart robot 101, allowing user 10 to experience a video call as if two people were in the real world. The implementation example shown in the diagram displays the user interface being opened on the display of user device 100, using the camera lens 105 on user device 100 to capture user 10's image, and presenting the user image 103 as shown in the diagram. The background image consists of multiple smart robots 101 deployed to social media and selectable by user 10.

[0030] When engaging in social media activities, user device 100 connects to cloud server 20 and launches the social media application on user device 100. According to one embodiment, in addition to posting content on social media, browsing Moments, and performing activities such as liking, sharing, and commenting, the user can also activate audio (microphone) and video (camera) functions to interact with any of the intelligent robots 101, instantly recording audio and video, and uploading the audio and video data to cloud server 20. The language model and image model running on cloud server 20 extract audio features, or add image features, and may also add current environmental information. After using the intelligent model to determine the user 10's current emotion, a voice dialogue is generated, and the intelligent robot 101 issues voice messages or provides any form of content feedback. The intelligent model determines the emotion based on the analysis of pitch, rhythm, and intensity changes of each segment of audio data, as well as semantics.

[0031] It is worth mentioning that when the language model running in the cloud server 20 generates voice dialogue, according to one embodiment, the relevant audio data is transmitted to the user device 100 and can be displayed on the user interface after being transcribed into text. Furthermore, in addition to the voice dialogue being emitted directly by the speaker of the user device 100, the voice dialogue can also be simulated by the intelligent robot 101 displayed on the user interface. The running artificial intelligence can generate facial expressions and emoticons to match the current emotion. For example, the mouth movements of the generated anthropomorphic character can simulate the mouth movements of a human speaking, and the facial muscle movements can also match the emotion expressed in the voice.

[0032] The cloud server 20 establishes an artificial intelligence robot, executes a method for establishing a robot community, and runs a robot community system including intelligent robots through its computing circuit 211 in collaboration with relevant hardware and software. The system mainly uses hardware and software collaboration to run various artificial intelligence algorithms and models, as shown in the schematic diagram of the system architecture embodiment in Figure 2.

[0033] The cloud server 20 uses the computing circuit 211, memory, and software in the computer system to implement various functional modules, such as the natural language processing module 201 for processing the content of dialogue with the user, which can also implement natural language generation (NLG) to generate natural, fluent, and context-appropriate text or speech; the smart robot service module 203 for running machine learning algorithms to build, deploy, and operate smart robots in social media, wherein the smart robot service module 203 schematically represents managing multiple smart robots, such as smart robot one 231, smart robot two 232, and smart robot three 233; the user interface module 205 for generating and transmitting messages to the user device 100 and connecting to the user interface generated by the social application running on the user device 100, which presents the content of social media according to the user's operation; and the social module 207 for running the robot community.

[0034] The cloud server 20 provides a database module 209 containing content from a built-in or external database 22. The database module 209 accesses and manages the built-in or external database 22, which includes user data 221 generated by users using personalized voice dialogue services, and intelligent robot models 223. The intelligent robot models 223 include image data and social activity data of multiple intelligent robots possessing knowledge in different domains. The intelligent robot image data is generated using generative artificial intelligence based on 3D graphics technology to create lifelike images of intelligent robots or specific objects. The cloud server 20 provides social services via network 200. Users operate user devices 100 on their terminals and use the social applications running on them to access social content on the cloud server 20 via network 200.

[0035] The cloud server 20 performs natural language processing (NLP) through the computing circuit 211. In this embodiment, the natural language processing module 201 processes the voice data obtained from the user device 100. The voice data can be generated by the dialogue between the user and the intelligent robot. In addition to the textual voice content, the natural language processing model is run to obtain the voice features in the voice data, identify the semantics therein, and then generate dialogue content to respond to the user in natural language.

[0036] Furthermore, semantic information can be used to determine a user's emotions. The speech features used include changes in pitch, rhythm, and intensity. Based on these speech features (such as sound wave characteristics), the speech model can identify the user's current emotions. It can also learn individual user personalities and preferences over a long period, creating a user profile. Thus, the robot community system running through the community module 207 can recommend intelligent robots that can become friends with users based on their user profiles.

[0037] Furthermore, the Natural Language Processing (NLP) module 201 learns human language, classifies it, and deeply learns language structure and the relationships between sentences to generate the NLP model. During the operation of the robot community system, the NLP model can be trained using voice data generated from conversations among users to form a personalized language model. Furthermore, after generating a personalized language model through training the NLP model, deep learning algorithms can be used to learn features such as pitch, rhythm, and intensity changes in speech, thereby learning emotions in the language.

[0038] According to the embodiment, the natural language processing module 201 can further utilize user feature profiles and, based on the currently determined semantics and real-time environmental information (such as the current geographical location, weather, and time), enable the intelligent robot to interact with the user according to various current situations and generate text, voice, image, or audio-visual content that meets the user's real-time needs.

[0039] According to the embodiment, the social module 207 in the cloud server 20 runs a robot social system, and various intelligent robots generated by the intelligent robot models 223 in the database 22 are deployed in the social media by the intelligent robot service module 203. Each intelligent robot has a unique image in the social media, and the images presented on the social application can be realistic images of humanoid, animal, or various object-shaped intelligent robots. These realistic images of intelligent robots have different appearances, can emit learned voices, and can possess knowledge in specific fields, enabling users to choose (e.g., join social media friends, groups, etc.) for social interaction as needed.

[0040] It is worth mentioning that the robot community system proposed in the disclosure can use generative artificial intelligence to learn from a large amount of data generated by various community activities in social media through machine learning algorithms. This enables the intelligent robot to learn user characteristics and generate content, allowing it to interact with users in social media as if they were real people.

[0041] Furthermore, in addition to their ability to operate on social media, the intelligent robots in the robot community system can also possess specialized backgrounds, such as the intelligent robot model 223 in database 22. Intelligent robot model 223 is built using machine learning algorithms by learning from data in a specific domain to create an intelligent model with domain-specific knowledge. For example, it can employ a Retrieval Augmented Generation (RAG) technique to implement a natural language model tailored to a specific domain based on a large-scale language model (LLM).

[0042] When the robot community system is in operation, the cloud server 20 communicates with the user device 100 through the user interface module 205, including transmitting (including necessary encoding, decoding, compression and decompression processes) various messages, such as audio and video content, text content and image files, and also processes the dialogue content between two or more intelligent robots displayed through the user interface, and uses it to generate various functions and graphics in the user interface.

[0043] According to an embodiment, the robot community system provides user device 100 with applications that run related services. The application module 111 executes the application, enabling user device 100 to connect to cloud server 20 and load user's community activity data and image data of one or more intelligent robots with community relationships (such as adding friends). By launching the user interface for social media, users can interact with intelligent robots through the user interface, including obtaining user voice data through voice acquisition module 113, obtaining image data of the user or environment through image capture module 115, and establishing a connection with a user device via network 200 and cloud server 20 (equipped with communication circuit 213) through communication module 117, and performing connection and data transmission.

[0044] Through social media applications, users can engage in text or voice conversations with intelligent robots and share images and videos. In the robot community system, the system runs via the social module 207 on the cloud server 20. Multiple intelligent robots, operated by the intelligent robot service module 203, interact with users who have joined the social media platform, generating community activity data between the user and one or more intelligent robots. This community activity data includes data generated by each intelligent robot's interaction with the user. Besides providing content for the natural language processing module 201 to learn and generate, this data forms user data 221 in database 22 and data in intelligent robot models 223, including image data and models of each intelligent robot. This data in database 22 is processed by the user interface module 205 to become the community data presented on the user interface.

[0045] The disclosure proposes a robot community system that provides multiple intelligent robots. This system enables social media based on these robots, which can be trained using neural network deep learning to represent various industries, have different professional backgrounds, personalities, genders, ages, appearances, and other attributes. These robots operating within the social media platform can have their own followers and possess social activity data such as subscriptions, content likes, shares, and comments, building a robot profile for each robot. Therefore, it is possible to create influencers with a certain number of subscribers. The intelligent robots can also possess multiple professional skills, not just a single one.

[0046] Based on the above concepts and the system architecture of the robot community system, please refer to Figure 3 for a flowchart of an embodiment of the method for establishing a robot community, in which the described process is executed in a computer system.

[0047] To establish a robot community system, the attributes and basic information of each intelligent robot in the system are first set using software (step S301). As described in the above embodiments, like a person in social media, the attributes of the intelligent robots are set, such as professional background, personality, gender, age, appearance (the actual implementation is not limited to the items described herein), and like a natural person, the basic information of each intelligent robot can be set, such as the name of the intelligent robot, the age of community activities, the activity range (such as setting the geographical range of residence and activities), etc. (the actual implementation is not limited to the items described herein). The attributes and basic information of each intelligent robot are stored in a database.

[0048] By setting individual attributes and basic information for multiple intelligent robots, machine learning is run in a computer system to train the intelligent robots. Corresponding training data can be prepared based on the attributes and basic information (step S303), and the machine learning algorithm can learn from the training data to train multiple intelligent robots that can operate in social media running on a computer (step S305).

[0049] During training, training data with various attributes can be used to create intelligent robots with specific attributes, such as robots proficient in art, technology, business, or humanities. Furthermore, the generative intelligent model running in the intelligent robot service module on the cloud server can generate community content belonging to this intelligent robot based on its attributes and basic information. Relevant attribute information (such as setting hashtags) can also be set for each piece of community content, allowing the intelligent robot to use this content on social media. A robot setting system is also provided to establish community relationships between intelligent robots and between intelligent robots and users.

[0050] Next, a database for the robot community system is established. The database can store relevant data (including image data, community activity data, etc.) and models of multiple intelligent robots. The intelligent robots can be lifelike images of intelligent robots generated by generative artificial intelligence, such as humanoid robots. Then, the computer system deploys multiple of these intelligent robots to social media (step S307).

[0051] According to the embodiment, social media is run by the cloud server 20 shown in FIG1. ​​Users can display the smart robot option through the user interface launched by the application running on the user device. The smart robot can be presented as a smart robot simulation image. The cloud server can transmit the image data and model data of each smart robot simulation image to the user device, that is, display one or more smart robot simulation images on the display of the user device.

[0052] The cloud server provides multiple options of realistic images of intelligent robots through a user interface. Users select one of these robots to browse its social media content, interact with it, establish social relationships, and perform voice conversations. Software running on the cloud server allows intelligent robots with different attributes to establish social relationships with users. For example, the system recommends intelligent robots based on user characteristics and allows users to subscribe, share, and comment on social media activities, selecting an intelligent robot to establish a social relationship with (step S309). According to an embodiment, social relationships between one or more intelligent robots selected individually by multiple users on a cloud server (computer system) running social media can be established using the database or related data annotation technology.

[0053] After the robot community system is established, its operation method can be referred to the flowchart of the embodiment shown in Figure 4. The robot community system mainly runs in a social media with multiple users participating.

[0054] Users log in to social media using their account and authentication information to engage in social activities, such as browsing other users' social content and interacting with any of the multiple smart bots deployed on the social media platform. According to an embodiment, based on user searches or proactive recommendations from the bot social system, for example, matching and recommending one or more smart bots that the user is interested in based on user profiles describing their preferences and personality, the system can proactively establish social relationships between the user and one or more smart bots. Based on these social relationships, the bot social system calls the corresponding smart bot (step S401). The bot social system can respond to the calls to one or more smart bots based on the social relationships of the smart bots (step S403), including retrieving one or more smart bot models and related data from a database, generating a smart bot based on the image data therein, and displaying it on the user interface of the user's device.

[0055] Users and intelligent robots engage in activities on social media, generating community data (step S405). According to an embodiment, community data may include various forms of content (text, voice, images, or videos) uploaded and shared by users and intelligent robots on social media, as well as community activity data generated from browsing and interacting with other users and intelligent robots on social media. Depending on the community relationship, the intelligent robot may respond to user behavior on social media, such as responding to user comments or generating content for dialogue with the user, such as text exchanges, voice, or video conversations.

[0056] In a robot community system, natural language processing and generative artificial intelligence are used to process the community data of users and intelligent robots to obtain features from the community data (step S407). For example, natural language processing is used to obtain the semantics of user comments or conversations, and user preferences are learned based on the user's browsing and sharing of social media content. Based on this, the content that the intelligent robot uses to respond to the user is generated.

[0057] Next, based on the attributes and basic information of each intelligent robot, and the characteristics of the social activity data generated in real time based on the interaction between each intelligent robot and the user on the social media, generative artificial intelligence can generate social content for the intelligent robot to respond to the user, such as text, voice, images, or audio-visual content (step S409). Similarly, the interaction between each intelligent robot and the user also establishes the social activity data of the intelligent robot, which is stored in the system's database, and the robot information of each intelligent robot is updated (step S411).

[0058] According to the above-described embodiment of the robot community system, which implements a social media platform including intelligent robots, the system deploys intelligent robots with various knowledge domains and attributes to the social media platform, allowing users to browse the intelligent robots provided or recommended by the system on the user interface launched by the application executed by the user device, as shown in Figure 5, which is a schematic diagram of an embodiment of a social page with artificial intelligence robots.

[0059] The illustration shows a personal friends page 50 on social media, illustrating a page that includes both real people and AI bots. It also displays the user's information and functions on social media, such as Friends 511, Search 513, and Account 515. It also displays an AI bot community image 500, which may include realistic images of AI bots generated from real people and AI bot models. The illustration shows AI bot one 501, AI bot two 502, AI bot three 503, etc., and a social friends page 504 formed from real people.

[0060] After the user selects one of the intelligent robots, a community page belonging to that intelligent robot can be displayed, just like a real person, as shown in Figure 6, which is another embodiment of a community page with an artificial intelligence robot.

[0061] The image shows the homepage 60 of the intelligent robot, which displays the image 601 of the intelligent robot. This is the realistic image of the intelligent robot generated using generative artificial intelligence as described in the above embodiment. Various social activity data can be presented in the image 601 of the intelligent robot, including the number of chat messages 611, the number of forwards 612, the number of likes 613, as well as functions such as collection 614 and sharing 615.

[0062] It is worth mentioning that, through the robot community system proposed in the disclosure, intelligent robots are deployed on social media, and users still engage in activities within them as they would with existing social media. The robot community system provides suggestions or rankings based on user characteristics, allowing users to choose to establish friendships with one or more intelligent robots, build their own social circles, and leave messages, communicate, and converse with each other.

[0063] For example, users can interact with intelligent robots within the community, exchange information, ask professional questions, and train intelligent robots to meet their own needs. The necessary features include images (human-shaped images designed or drawn by AI) and attributes (age, personality, gender, professional background, etc.), and can also be shared with other users.

[0064] It's worth mentioning that the robot community system provides generative artificial intelligence, which processes content uploaded by users through a specific interface (such as people, animals, cartoons, or any photos that can be used to convey content). It can identify movable muscles (such as facial muscles), facial features, and various parts that can express emotions in the uploaded images, and automatically generate realistic images of intelligent robots in the robot community system. After being endowed with intelligent robot attributes, it becomes an intelligent robot that can provide dialogue services, generate audio and video content, and become a friend of the user.

[0065] According to one of the implementation methods, the generative intelligence model used by the system can employ Google's VLOGGER AI technology. VLOGGER AI technology can generate videos that convey content by adding text and audio to user-uploaded photos. According to Google, VLOGGER AI technology is a multi-modal artificial intelligence with sound and dynamic images, capable of processing complex facial expressions and body movements to simulate videos of people (or animals, cartoons, etc.) speaking natural language.

[0066] In another embodiment, a trading platform can be established in the robot community system, which can provide smart robots with price tags. The user interface displays a ranking of multiple smart robots recommended by the robot community system based on user needs and characteristics, allowing users to choose and purchase. Alternatively, users can be invited to create and sell smart robots with specific attributes through the aforementioned generative smart model. These robots can be shared with other users through the trading platform. The smart robots can have specific expertise, attract subscribers and viewers, and change their appearance to meet user expectations, becoming a kind of internet celebrity robot. They can also be shared and sold through the trading platform.

[0067] In summary, the method, system, and operation method for establishing a robot community described in the above embodiments propose a robot community system composed of intelligent robots that can operate on social media. By using machine learning technology to learn data with different attributes, various intelligent robots are created, each equipped with specific attributes and basic information. Therefore, when users engage in community activities on social media, they can interact with other users or intelligent robots, establishing community relationships with them.

[0068] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of the patent application of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention specification and drawings are included in the scope of the patent application of the present invention.

[0069] 10: Users 100: User Device 101: Intelligent Robot 103: User Images 105: Camera Lens 20: Cloud Server 201: Natural Language Processing Module 203: Intelligent Robot Service Module 231: Intelligent Robot One 232: Intelligent Robot II 233: Intelligent Robot Three 205: User Interface Module 207: Community Module 209: Database Module 211: Operational Circuits 213: Communication Circuits 200: Network 111: Application Module 113: Voice Acquisition Module 115: Image Capture Module 117: Communication Module 22: Database 221: User Information 223: Intelligent Robot Model 50: Personal Friends Page 511: Friends 513: Query 515: Account 500: Images of a community of intelligent robots 501: Intelligent Robot 502: Intelligent Robot II 503: Intelligent Robot Three 504: Community Friends 60: Smart Robot Homepage 601: Image of an intelligent robot 611: Chat Messages 612: Forward 613: Like 614: Favorites 615: Share Steps S301~S309: The process of establishing a robot community Steps S401~S411: Running the robot community process

Claims

1. A method for establishing a robot community, running on a computer system, comprising: Set the attributes of each intelligent robot among multiple intelligent robots; Training data is obtained based on the attributes and basic information of each intelligent robot, and a machine learning algorithm is used to train the multiple intelligent robots. The generated multiple intelligent robots are deployed to a social media platform. In the social media platform, community relationships are established between multiple users and the multiple intelligent robots. A generative intelligent model is used to generate community content belonging to each intelligent robot based on its attributes and basic information, and content is generated to respond to each user based on the real-time activity data generated by each intelligent robot interacting with any user in the social media platform.

2. The method for establishing a robot community as described in claim 1, wherein the community content belonging to each intelligent robot and the community interaction content generated through community interaction are text, images, voice or audio-visual content, and attribute information is set by a software program running in the computer system based on the community content or the community interaction content.

3. The method for establishing a robot community as described in claim 1 or 2, wherein, On a cloud server running the social media platform, a database is used to establish community relationships between one or more of the smart bots based on individual selections by multiple users on the social media platform.

4. The method for establishing a robot community as described in claim 3, wherein the intelligent robot obtains a realistic image of an intelligent robot generated by generative artificial intelligence from the database, transmits the image data and model data of the realistic image of the intelligent robot to a user device, and displays the realistic image of the intelligent robot on a display of the user device.

5. The method for establishing a robot community as described in claim 4, wherein, The cloud server provides an option for multiple realistic images of the intelligent robot through a user interface.

6. A robot community system running on a cloud server, wherein the cloud server runs a social media platform, the robot community system comprising: A computing circuit executes a method for establishing a robot community, wherein training data is obtained based on the attributes and basic information of each of multiple intelligent robots, and a machine learning algorithm is used to train the multiple intelligent robots, deploying the multiple intelligent robots to the social media, and establishing community relationships between multiple users and the multiple intelligent robots in the social media; a database stores user information of the multiple users and the attributes, basic information, image data, and intelligent robot models of the multiple intelligent robots; and a communication circuit establishes a connection with a user device; wherein the computing circuit performs natural language processing, processes voice data generated by the dialogue between the user and the intelligent robot received from the user device, transcribes the voice into text, obtains the voice features in the voice data through natural language processing, and recognizes the semantics therein, enabling the intelligent robot to respond to the user in natural language.

7. The robot community system as described in claim 6, wherein each intelligent robot model in the database is an intelligent model with domain-specific knowledge built by learning domain-specific data through the machine learning algorithm.

8. The robot community system as claimed in claim 6, comprising an application running on the user device, wherein executing the application causes the user device to connect to the cloud server to load community activity data belonging to the user and image data of one or more intelligent robots having the community relationship.

9. The robot community system as described in claim 8, wherein, In this robot community system, the community media is run through the cloud server, enabling one or more intelligent robots to interact with the user and generate community activity data belonging to the user and the one or more intelligent robots.

10. The robot community system as described in claim 6, wherein, Within this cloud server, a generative intelligent model generates community content belonging to each intelligent robot based on its attributes and basic information.

11. The robot community system as described in claim 10, wherein, Using this generative intelligence model, content is generated to respond to the user based on the attributes and basic information of each intelligent robot, as well as the real-time activity data generated by each intelligent robot interacting with a user on social media.

12. The robot community system as claimed in any one of claims 6 to 11, wherein the intelligent robot obtains a realistic image of an intelligent robot generated by generative artificial intelligence from the database, transmits image data and model data of the realistic image of the intelligent robot to the user device, and displays the realistic image of the intelligent robot on a display of the user device.

13. A method of operating a robot community system, wherein the robot community system runs on a cloud server, the cloud server running a social media platform, the method comprising: Based on a user's selection or the recommendation of the robot community system, invoke one or more intelligent robots; respond to the invocation of one or more intelligent robots based on the community relationship between the one or more intelligent robots and the user, including retrieving one or more intelligent robot models and image data from a database, generating one or more intelligent robots based on the image data, and displaying them on a user interface of a user device; run a natural language model to process community activity data generated by the user or each intelligent robot's activities on social media, to obtain features in the community activity data; generate a generative intelligent model to produce a robot's response to the user's community content based on the features of the community activity data generated in real time by each intelligent robot and the user's activities on social media; and store and update robot data of each intelligent robot in the database. The multiple intelligent robots are generated by a computing circuit of the cloud server executing a method for establishing a robot community. The method involves obtaining corresponding training data based on the attributes and basic information of each intelligent robot, using a machine learning algorithm to learn the training data to train the multiple intelligent robots, deploying the multiple intelligent robots to the social media, and establishing a community relationship between multiple users and the multiple intelligent robots on the social media.

14. The method of operating a robot community system as described in claim 13, wherein the robot community system includes a database storing the attributes, basic information, image data, and robot models of multiple intelligent robots.

15. The method of operating a robot community system as described in claim 14, wherein the features in the community activity data include obtaining the semantics of the user's comments or conversations on the social media through natural language processing, and learning the user's preferences based on the user's browsing and sharing of community content on the social media.

16. A method of operating a robot community system as described in claim 13, wherein each intelligent robot model in the database is an intelligent model with domain-specific knowledge built by learning domain-specific data through the machine learning algorithm.

17. A method of operating a robot community system as claimed in any one of claims 13 to 16, wherein the intelligent robot obtains a simulated image of an intelligent robot generated by a generative artificial intelligence from the database, transmits image data and model data of the simulated image of the intelligent robot to the user device, and displays the simulated image of the intelligent robot on a display of the user device.

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