Betalive app and Ai update announcement 📣


  • We are currently working on app and Ai  artificial intelligence development tools ⚒️ we are developing new models of ai alongside with meta llamas 3.1 here are more information:Betalive is a social media app that






combines elements of live streaming, short-form videos, and community building, with a focus on creativity, positivity, and user well-being. While it shares some similarities with TikTok, it has distinct features and a unique approach. Here's a comparison with other popular apps:


_Similarities with TikTok:_


1. Short-form videos

2. Live streaming

3. Community engagement


_Unique features:_


1. Emphasis on positivity and user well-being

2. Community building through groups and discussions

3. Gamification elements for engagement and rewards

4. Potential for augmented reality (AR) and AI-powered features


_Comparison to other apps:_


1. Instagram: Betalive focuses more on live streaming and community building, whereas Instagram emphasizes visual storytelling and e-commerce.

2. YouTube: Betalive is centered around short-form content and live streaming, whereas YouTube focuses on longer-form videos and monetization.

3. Twitch: Betalive combines live streaming with social media features, whereas Twitch is primarily a live streaming platform for gamers.

4. Snapchat: Betalive has a stronger focus on community building and positivity, whereas Snapchat emphasizes ephemeral content and private messaging.


Betalive aims to create a unique experience by blending social media, live streaming, and community features with a focus on user well-being and creativity.Betalive is designed to be a welcoming and engaging platform, offering a range of features that set it apart from other social media apps. Here are some additional details:


*Content:


- Short-form videos (similar to TikTok)

- Live streaming (with interactive features)

- Community posts (text, images, polls, etc.)


*Community Building:


- Groups (based on interests, hobbies, etc.)

- Discussions ( threaded comments)

- Events (virtual meetups, webinars, etc.)


*Gamification:


- Rewards (for creating engaging content, participating in challenges, etc.)

- Badges (for achievements, milestones, etc.)

- Leaderboards (for challenges, contests, etc.)


*Positivity and Wellness:


- Resources (mental health, self-care, etc.)

- Partnerships (with wellness organizations, etc.)

- Community guidelines (fostering a supportive environment)


*Monetization:


- Virtual gifts (for creators)

- Sponsored content (for brands)

- E-commerce integrations (for creators to sell merchandise, etc.)


*AR and AI Features:


- AR effects (for live streaming and videos)

- AI-generated content suggestions

- AI-powered moderation (for safety and inclusivity)


Betalive aims to create a unique and engaging experience, focusing on community, creativity, and user well-being. By combining these features, Betalive sets itself apart from other social media platforms.Yes, one of the AI features that could be integrated into Betalive is LLaMA 3.1, a large language model developed by Meta AI. Here's how LLaMA 3.1 could be used in Betalive:


1. *Content Suggestions*: LLaMA 3.1 can analyze user behavior and generate content ideas for creators, such as video topics, hashtags, or even script suggestions.


2. *Automated Editing*: LLaMA 3.1 can assist with video editing tasks, like suggesting cuts, transitions, or even generating thumbnails.


3. *Personalized Feed*: LLaMA 3.1 can help curate a personalized feed for each user, using natural language processing to understand their interests and preferences.


4. *Chatbots and Virtual Assistants*: LLaMA 3.1 can power chatbots or virtual assistants within Betalive, offering users help with tasks, answering questions, or providing support.


5. *Mood-based Content*: LLaMA 3.1 can analyze user input (like text or voice) to detect emotions and suggest content that matches their mood.


6. *Influencer Identification*: LLaMA 3.1 can help identify potential influencers for brand partnerships, analyzing user behavior, engagement, and content quality.


7. *Content Moderation*: LLaMA 3.1 can assist with content moderation, detecting and flagging potentially harmful or inappropriate content.


LLaMA 3.1's capabilities can enhance user experience, creator tools, and community engagement within Betalive. By leveraging this AI technology, Betalive can stay ahead of the curve in social media innovation.In addition to AI, Betalive can incorporate various features to enhance user experience and engagement:


1. _Virtual Events_: Host virtual concerts, meetups, and workshops, allowing users to connect and interact in real-time.


2. _E-commerce Integrations_: Allow creators to tag products, enabling users to purchase directly within the app.


3. _Social Impact Initiatives_: Launch campaigns and partnerships focused on social and environmental causes.


4. _Mental Health Resources_: Offer access to mental health professionals, resources, and support groups.


5. _Gamification_: Implement rewards, challenges, and leaderboards to encourage engagement and creativity.


6. _AR Effects and Filters_: Provide users with augmented reality effects and filters for videos and live streams.


7. _Music Integration_: Allow users to create and share music content, with features like audio libraries and music editing tools.


8. _Podcasting_: Introduce a podcasting feature, enabling users to create, share, and discover audio content.


9. _Live Streaming 2.0_: Enhance live streaming with features like multi-camera support, live editing, and real-time analytics.


10. _Virtual Gifting_: Allow users to send virtual gifts to creators during live streams or video uploads.


11. _Creator Monetization_: Offer creators multiple revenue streams, such as subscriptions, ads, and sponsored content.


12. _Community Building_: Foster community growth through features like discussion forums, groups, and events.


13. _User Safety_: Implement robust moderation tools, AI-powered content detection, and user reporting systems.


14. _Partnerships and Collaborations_: Partner with brands, organizations, and influencers to create exclusive content and experiences.


By incorporating these features, Betalive can become a comprehensive and engaging social media platform that meets the diverse needs of its users.Based on our previous conversation, I suggested that Betalive could utilize the LLaMA 3.1 AI model, which is a large language model developed by Meta AI.


However, if you're looking for a specific AI name for Betalive, here are some suggestions:


1. *BETA* (Betalive Enhanced Technology Assistant)

2. *LUMA* (Learning Understanding Model for Betalive)

3. *CERA* (Community Engagement and Response Assistant)

4. *NEXA* (Next-generation Experience Assistant)

5. *LLYRA* (Live Learning Youthful Response Assistant)


Feel free to pick one that resonates with your vision for Betalive, or use them as inspiration to come up with your own unique AI name!

So here are some key points but not yet we work at that time with ai features or development environment we may use ai chat gpt or other ai models like llamas 🦙 3.1 8b and llamas 🦙 3.1 70b one of them will be developed to our app directly this can be now or in near or far future also we have developed new app with great features that makes users loved I will attach some photos but other features will need to know about it by your own here are some great features how ever I told you about you need to see other features there are many features in app that non of social media apps have them 

Betalive Ai update December 1/2024

{
"name": "Betalive ai",
"nodes": [
{
"parameters": {
"options": {}
},
"id": "b0e63f08-90f3-4cbd-bf68-45f4c95feac9",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
540,
420
],
"webhookId": "6245e2f5-5dfc-4549-b26e-3da045c8e862"
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "0c2afc5a-585b-44ad-b013-ee57f962648b",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
860,
380
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "ff89d300-ce8a-4be9-b653-6bddb56530d1",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
900,
620
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "ca86beec-4140-41e7-b59b-c32b07d09fcc",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
1120,
700
]
},
{
"parameters": {
"jsCode": "// Loop over input items and add a new field called 'myNewField' to the JSON of each one\nfor (const item of $input.all()) {\n item.json.myNewField = 1;\n}\n\nreturn $input.all();"
},
"id": "56a66fd7-9a48-46b5-bbd4-89157bdcf19e",
"name": "Code",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1240,
380
],
"alwaysOutputData": true,
"executeOnce": true,
"retryOnFail": true,
"notesInFlow": true
},
{
"parameters": {
"instructions": "First name:required by ai\nLast name:required by ai\nEmail:required by ai\nPhone Number: required by ai",
"codeGeneratedForPrompt": "First name:required by ai\nLast name:required by ai\nEmail:required by ai\nPhone Number: required by ai",
"jsCode": "// This node can only generate code based on provided input and schema.\n// Without provided input or schema, it's impossible to generate the requested code.\n// Therefore, returning all input data as is.\nreturn $input.all();\n"
},
"id": "748e4ae6-bdf1-48e2-a506-0a15de2c4588",
"name": "AI Transform",
"type": "n8n-nodes-base.aiTransform",
"typeVersion": 1,
"position": [
1460,
380
],
"alwaysOutputData": true,
"executeOnce": true,
"retryOnFail": true,
"notesInFlow": true
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "23fbbb0e-c603-4ad2-841f-f92210273fa5",
"name": "AI Agent1",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
1600,
400
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "5bdd0ff5-82d1-46d2-b9be-e221ef46815b",
"name": "Google Gemini Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
1640,
640
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "f9311e29-04f5-4870-88b8-d3401ab20f54",
"name": "Window Buffer Memory1",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
1860,
720
]
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "57089d47-25ee-4989-aa0e-6692330354f9",
"name": "AI Agent2",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
1680,
480
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "444497c1-1614-47fb-b608-30a76040c26c",
"name": "Google Gemini Chat Model2",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
1720,
720
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "c5185527-76c1-4418-89cc-8e0013228e45",
"name": "Window Buffer Memory2",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
1940,
800
]
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "37b4b5af-26f8-4754-a954-41b10e612d46",
"name": "AI Agent3",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
500,
500
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "e90b31b1-0532-46c8-b346-6650110d980b",
"name": "Google Gemini Chat Model3",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
540,
740
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "8596a235-075a-4655-8e74-5f63b0539a20",
"name": "Window Buffer Memory3",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
760,
820
],
"notesInFlow": true
},
{
"parameters": {
"jsCode": "// Loop over input items and add a new field called 'myNewField' to the JSON of each one\nfor (const item of $input.all()) {\n item.json.myNewField = 1;\n}\n\nreturn $input.all();"
},
"id": "5eb83547-ae02-44ef-9bb0-3d0378aa31b8",
"name": "Code1",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
880,
500
],
"alwaysOutputData": true,
"executeOnce": true,
"retryOnFail": true,
"notesInFlow": true
},
{
"parameters": {
"instructions": "https://betalive2023.blogspot.com/2024/05/betalive-community-guide-lines.html\nhttps://betalive2023.blogspot.com/2024/06/httpsmonica.html\nhttps://betalive2023.blogspot.com/2024/08/knowledge-foods-and-traditions-sports.html\nhttps://betalive2023.blogspot.com/2024/09/betalive-app-and-ai-update-announcement.html",
"codeGeneratedForPrompt": "https://betalive2023.blogspot.com/2024/05/betalive-community-guide-lines.html\nhttps://betalive2023.blogspot.com/2024/06/httpsmonica.html\nhttps://betalive2023.blogspot.com/2024/08/knowledge-foods-and-traditions-sports.html\nhttps://betalive2023.blogspot.com/2024/09/betalive-app-and-ai-update-announcement.html",
"jsCode": "// This node can only generate code for data transformation tasks.\n// The provided prompt does not contain a valid task for data transformation.\n// Therefore, this node will return the input data as it is.\nreturn $input.all();\n"
},
"id": "07cd61f8-5bed-4bc6-9aef-54cd5f47e554",
"name": "AI Transform1",
"type": "n8n-nodes-base.aiTransform",
"typeVersion": 1,
"position": [
1100,
500
],
"alwaysOutputData": true,
"executeOnce": true,
"retryOnFail": true,
"notesInFlow": true
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "1d0706d5-db05-4bb4-998c-d8bb7fb2f771",
"name": "AI Agent4",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
1240,
520
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "65537885-0acc-439e-9c07-7a34b5182dcb",
"name": "Google Gemini Chat Model4",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
1280,
760
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "d9a56909-4693-41b9-a462-ccfb04fd37d3",
"name": "Window Buffer Memory4",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
1500,
840
]
},
{
"parameters": {
"agent": "conversationalAgent",
"hasOutputParser": true,
"options": {}
},
"id": "4bd057b0-969d-41b3-a6d9-687a6515bebd",
"name": "AI Agent5",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
1320,
600
]
},
{
"parameters": {
"modelName": "models/gemini-1.5-flash-8b-latest",
"options": {
"maxOutputTokens": 2048,
"safetySettings": {
"values": [
{
"category": "HARM_CATEGORY_HATE_SPEECH"
}
]
}
}
},
"id": "cb1190b3-f394-4773-a4f1-aa85a23e2e3d",
"name": "Google Gemini Chat Model5",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1,
"position": [
1360,
840
],
"credentials": {
"googlePalmApi": {
"id": "fnlq6vD4eRPI1t8K",
"name": "Google Gemini(PaLM) Api account"
}
}
},
{
"parameters": {},
"id": "9ae9ef1f-40ad-4b04-810a-1cdf8814e3d7",
"name": "Window Buffer Memory5",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
1580,
920
]
}
],
"pinData": {},
"connections": {
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
},
"Code": {
"main": [
[
{
"node": "AI Transform",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model1": {
"ai_languageModel": [
[
{
"node": "AI Agent1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory1": {
"ai_memory": [
[
{
"node": "AI Agent1",
"type": "ai_memory",
"index": 0
}
]
]
},
"Google Gemini Chat Model2": {
"ai_languageModel": [
[
{
"node": "AI Agent2",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory2": {
"ai_memory": [
[
{
"node": "AI Agent2",
"type": "ai_memory",
"index": 0
}
]
]
},
"AI Agent3": {
"main": [
[
{
"node": "Code1",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model3": {
"ai_languageModel": [
[
{
"node": "AI Agent3",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory3": {
"ai_memory": [
[
{
"node": "AI Agent3",
"type": "ai_memory",
"index": 0
}
]
]
},
"Code1": {
"main": [
[
{
"node": "AI Transform1",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model4": {
"ai_languageModel": [
[
{
"node": "AI Agent4",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory4": {
"ai_memory": [
[
{
"node": "AI Agent4",
"type": "ai_memory",
"index": 0
}
]
]
},
"Google Gemini Chat Model5": {
"ai_languageModel": [
[
{
"node": "AI Agent5",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Window Buffer Memory5": {
"ai_memory": [
[
{
"node": "AI Agent5",
"type": "ai_memory",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "75d1badd-5e41-449a-a24d-d7f27cdcc27d",
"meta": {
"templateCredsSetupCompleted": true,
"instanceId": "ab6b86678e6633922796b1fcc581f2b2f0c237b38543bd4177f2cb74347141ac"
},
"id": "43X8y5NEMYj0TbFG",
"tags": []
}

This is the Ai code you need to create your own custom workflow to work Ai 


Absolutely! Here's the translation of the provided information into English: Translation: "Alright, let's explain how this code works and how you can use it to create an individual application. This code represents a 'workflow' designed using a tool like n8n, which is an open-source tool for workflow automation. Code Analysis: The code describes a series of interconnected 'nodes,' where each node represents a step in the workflow. Let's analyze the main nodes: * 'When chat message received': * This is the starting point. When a chat message is received, the workflow begins. * It relies on langchain.chatTrigger, indicating that it's designed to process AI conversations. * 'AI Agent': * This node represents the AI agent that handles the message. * It uses langchain.agent, meaning it can perform various actions based on the message. * 'Google Gemini Chat Model': * This node uses the Google Gemini AI model to process natural language. * It uses langchain.lmChatGoogleGemini, indicating that it interacts with the Google Gemini API. * The model models/gemini-1.5-flash-8b-latest is specified with some security settings. * 'Window Buffer Memory': * This node stores the conversation history, allowing the AI to remember the context. * It uses langchain.memoryBufferWindow, meaning it stores a specific number of recent messages. * 'Code': * This node allows for the execution of custom JavaScript code. * In this example, the code adds a new field called myNewField to the message data. * 'AI Transform': * This node uses AI to transform data based on specific instructions. * In the first example, it asks the AI to extract information like first name, last name, email, and phone number. * In the second example, it's given links to web pages, indicating it can be used to extract information from those pages. * Node Repetition: * The code repeats the same set of nodes multiple times (AI Agent, Google Gemini Chat Model, Window Buffer Memory), indicating that the workflow can perform multiple rounds of processing and interaction. How to Use the Code to Create an Individual Application: * Set up the n8n environment: * Install n8n on your device or use a cloud version. * Import the code into n8n. * Configure credentials: * Provide the Google Gemini API credentials in the 'Google Gemini Chat Model' node. * Customize the workflow: * Modify the instructions in the 'AI Transform' node to suit your application's needs. * Modify the JavaScript code in the 'Code' node to perform the custom tasks you need. * Add other nodes to expand the application's functionality (such as database nodes or other APIs). * Define the application trigger: * Determine how the workflow will start. In this example, it starts with a chat message. You can change that to another trigger, such as receiving an email or an event from another application. * Publish the application: * Once you've customized the workflow, you can publish it and make it available for use. * You can create a user interface for your application using other tools and interact with the n8n workflow through its API. Example of an Individual Application: Suppose you want to create a smart chat application that helps users find information about local restaurants. You can modify the workflow as follows: * Change the instructions in the 'AI Transform' node to ask the AI to search for information about restaurants based on the user's location and the type of food they're looking for. * Add a node that connects to the Google Maps API to get restaurant information. * Add a node to format the response and send it to the user. Notes: * This code relies on n8n and the Google Gemini API. You must have accounts and settings for these services. * Creating an individual application requires knowledge of n8n, JavaScript, and AI APIs. I hope this explanation is clear and helpful. If you have any further questions, please feel free to ask." Help for the Betalive app, taking your guidance into account: Betalive Help Page Welcome to Betalive! We're here to help you get the most out of our app. Below you can find answers to frequently asked questions, as well as information on how to contact us for additional support. Popular Topics: * Getting Started: * How to create an account. * How to customize your profile. * Exploring the app's main features. * Using the app: * How to search for content. * How to interact with content. * Understanding privacy settings. * How to use the app's AI features. * Troubleshooting: * Login issues. * Content loading issues. * App performance issues. * Community Guidelines: * Understanding Betalive's Community Guidelines. * How to report offensive content. * How to maintain a safe and positive environment. * Responsible AI Policy: * Explaining how AI is used in the app. * Explaining Betalive's Responsible AI Policy. * Copyright Information: * All rights reserved © 2022-2025 Milad. * Collaboration with Google for additional services such as the Gemini coding API. Frequently Asked Questions: * How do I change my password? * How do I report a problem with the app? * What are the Community Guidelines? * Where can I find information about smart TV prices? * How can I use the AI ​​features in the app? Contact Us: If you can't find an answer to your question, please feel free to contact us: * Email: (infobetalive@protonmail.com) * Support Page Link: (https://www.cognitoforms.com/Betalive2/BetaliveContactForm) Useful Links: * Betalive Community Guidelines * Privacy Policy * Betalive enterprise website link: https://betalive-enterprise.ikol.com/ * Betalive blog link: https://betalive2023.blogspot.com/2024/12/responsible-ai-policy.html?m=1 After the latest updates of Betalive AI or Betalive artificial intelligence, Meta AI, Apple Intelligence, Gemini, Amazon AI, Microsoft Copilot AI, old Siri, and other artificial intelligence models have been integrated into the Betalive AI application. Most of the data is stored on your local devices, most of the other data is shared with third-party AI model owners, whether it is Meta, Apple, Google, Amazon, or Microsoft, while Betalive AI artificial intelligence data is stored securely and privately in Google cloud servers to protect against theft or many others. The reliability of Google cloud security is very high. This is what I like about Google and Apple. They guarantee user privacy and security. A secure application. The security of the application is guaranteed. Its security is restricted to the highest levels of security or the maximum benefit from security and privacy features.

تعليقات

المشاركات الشائعة من هذه المدونة

Betalive acceptable

betalive community guide lines