Meta AI technology page Top Builders

Explore the top contributors showcasing the highest number of Meta AI technology page app submissions within our community.

Meta

Meta, founded in 2004, is a global technology leader that revolutionizes how people connect and interact in the digital world. Originally known as Facebook, Meta is renowned for its pioneering advancements in social media, with platforms like Facebook, Instagram, and WhatsApp, which collectively reach billions of users worldwide. In addition to its social media prowess, Meta is a global technology company at the forefront of AI innovation, focusing on enhancing human connectivity and creating immersive digital experiences. Among its leading products related to AI technology are the LLaMA (Large Language Model Meta AI) series and Meta AI.

General
Company	Meta Platforms, Inc.
Founded	January 4, 2004
Headquarters	Menlo Park, California, U.S.
Repository	https://github.com/facebook

Key Products and Research

Meta has developed a range of AI products designed to enhance various aspects of technology and user experience. Here’s a brief overview of these AI products:

LLaMA (Large Language Model Meta AI)

LLaMA is a series of large language models designed for natural language processing tasks. These models, including the latest LLaMA 3.1, are known for their advanced capabilities in text generation, understanding, and multilingual processing. They are available as open-source models, promoting innovation and research in AI Meta | Social Metaverse Company,Facebook.

Meta AI

Meta AI is an intelligent assistant integrated across Meta’s platforms, such as Facebook, Instagram, WhatsApp, and Messenger. Powered by LLaMA models, it helps users with tasks like content creation, information retrieval, and personalized interactions Meta | Social Metaverse Company.

PyTorch

PyTorch is an open-source machine learning library developed by Meta and widely used in both research and industry. It provides tools for building and training deep learning models and has become a standard framework in the AI community Facebook.

Meta AI Research (FAIR)

Meta’s AI research division, formerly known as FAIR (Facebook AI Research), focuses on advancing the field of AI through open research and collaboration. This division works on various AI challenges, including computer vision, natural language processing, and generative AI Facebook.

Meta AI in the Metaverse

Meta is also incorporating AI into its metaverse initiatives, using AI to create immersive experiences in virtual and augmented reality. This includes developing AI-driven avatars, enhancing virtual environments, and improving interaction within the metaverse Meta | Social Metaverse Company.

AI for Ads

Meta leverages AI to optimize ad targeting, delivery, and measurement across its platforms. AI algorithms analyze vast amounts of data to improve the effectiveness of advertising campaigns, making them more relevant to users and efficient for advertisers Meta | Social Metaverse Company.

LLaMA Impact Grants

The LLaMA Impact Grants program, launched by Meta, aims to support and encourage the innovative use of its LLaMA (Large Language Model Meta AI) models to address critical challenges in various sectors, including education, environmental sustainability, and public good. This initiative offers financial grants and resources to researchers, nonprofits, and other organizations that seek to leverage LLaMA models for impactful projects. The program highlights Meta’s commitment to responsible AI development and its belief in the potential of AI to drive positive social change.

For more details, visit the LLaMA Impact Grants page.

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Meta AI technology page Hackathon projects

Discover innovative solutions crafted with Meta AI technology page, developed by our community members during our engaging hackathons.

SocialSwarm

Introducing Social Swarm: Amplify Your Voice to the World Everyone has something meaningful to share, but in today's digital landscape, only a few manage to get their messages heard. The hurdles? Time-consuming content creation, specialized skills, and deciphering ever-changing social media algorithms. Enter Social Swarm—a revolutionary agent system that empowers everyone to share their thoughts effortlessly. Effortless Content Creation: Simply provide the subject or message you want to share, and our intelligent agents handle the rest. Engaging Posts: Utilizing advanced prompting techniques and an agentic workflow, Social Swarm crafts posts that are not only compelling but also optimized for engagement. Factual Accuracy & High Engagement: We validate all content for accuracy and assess its potential to engage your audience effectively. Continuous Learning: Through social media monitoring and user feedback, Social Swarm learns and adapts to become even more efficient at spreading your message. Unlock your potential and let your voice be heard with Social Swarm. Share effortlessly, engage authentically, and make an impact.

CrewNews

Biases in news reporting can distort public perception, leading to a skewed understanding of important issues and events. When media outlets present information from a single perspective, they risk creating echo chambers where only certain viewpoints are amplified while others are silenced. This not only undermines the integrity of journalism but also affects how individuals form opinions and make decisions based on incomplete information. CrewNews addresses this critical issue by actively sourcing and presenting content from a diverse range of media providers from the United States, ensuring that multiple perspectives are represented in each report. By utilizing advanced AI technologies, CrewNews fosters a more balanced discourse, empowering users to hear all sides of the story for a given question or topic and come closer to the truth.

Reflect Discover Jarvis - RDJ

RDJ (Reflect Discover Jarvis) is a web application that merges AI technology with psychological principles to create a unique platform for personal growth and self-discovery. The project utilizes advanced language models to generate personalized assessments, analyze user responses, and provide tailored insights. Users can explore their personality traits, emotional states, and potential areas for growth through interactive questionnaires and guided reflections. The application features a dynamic visual experience with AI-generated shader animations that respond to user input and mood, creating an immersive and engaging environment for self-exploration. AI chat support offers users guidance and clarification throughout their journey. RDJ aims to make professional-level psychological insights and personal development tools accessible to a wide audience, addressing the growing need for mental health and self-improvement resources in the digital age. The scalable architecture and continuous improvement cycle ensure that RDJ can evolve and adapt to user needs, potentially expanding into various sectors such as education, corporate wellness, and healthcare.

Luna AI - The Ultimate Personal Assistant

The Desktop Task Manager and Communication Assistant is an innovative application that revolutionizes how users interact with their digital workspace. By harnessing the power of LLaMA 3.1, a cutting-edge language model, and integrating it with crew.ai's sophisticated AI agents, this tool creates a seamless bridge between voice commands and complex task execution. At its core, the application offers an intuitive voice interface, allowing users to manage their daily tasks, schedule meetings, compose emails, and manipulate documents across various Google services with simple spoken instructions. The AI interprets these natural language inputs, extracting relevant information to trigger the appropriate task agents. What sets this assistant apart is its multi-agent architecture. Each Google service (Meet, Gmail, Docs, Calendar, Drive, and Sheets) has a dedicated AI agent, enabling specialized handling of service-specific tasks. This modular approach ensures efficient and accurate execution of user requests, whether it's creating a new spreadsheet, scheduling a video call, or organizing files in Google Drive. The LLaMA 3.1 model serves as the central intelligence, processing user prompts and coordinating between agents. It can understand context, infer user intent, and even automate complex multi-step processes. For instance, a single voice command could trigger the creation of a meeting invite, generate an agenda document, and send email notifications to participants. By automating routine tasks and providing a natural, conversational interface to powerful productivity tools, this Desktop Task Manager and Communication Assistant significantly enhances workflow efficiency. It's particularly valuable for professionals who juggle multiple projects, frequent meetings, and extensive digital communication, offering a smarter way to manage their digital workload.

Agentic SDLC

We designed four agents to automate the SDLC. These were: Requirements Agent: Understand requirements from requirements doc Design Agent: Create high level design doc Software Development Agent: Generate codebase to build PoC (small project) Code Test Agent: Generate code tests The workflow steps we followed were as follows: a. Requirements Gathering Task: Extract key requirements from a document. Goal: Create a concise summary of the CRM system's required features. Outcome: Defines the project scope (authentication, CRUD operations, task management, reporting). b. High-Level System Design Task: Design the architecture of the CRM system. Diagrams Generated: Use Case Diagram Class Diagram Entity-Relationship Diagram (ERD) UI Design for Dashboard Outcome: A document detailing the architecture, components, and visual diagrams of the system. c. Code Generation Task: Develop the Code for the system. Goal: Create functional code that implements core features. Outcome: Working code implementing authentication, database operations, and reporting. d. Code Testing Task: Run test cases to verify code functionality. Goal: Ensure the system meets the requirements and works as expected. Outcome: A detailed test report highlighting results and potential issues. Future Work could include: Improvements in Design Diagrams: Explore more AI-driven tools for automated generation of detailed design diagrams. Customization: Enable more advanced configurations for tasks such as adding new agents or expanding CRM functionality. Deployment: Plan for deployment of the final CRM system in a production environment. We also considered building an agentic workflow for MLOps, but ultimately decided on the SDLC.

Super leads

An AI agent designed to assist small and medium-sized businesses (SMBs) in Sub-Saharan Africa with lead generation represents a transformative opportunity for enhancing business growth and sustainability in the region. This innovative solution leverages advanced artificial intelligence technologies to streamline the process of identifying and nurturing potential customers, enabling businesses to thrive in a competitive marketplace. Overview of the AI Agent The AI agent functions as a comprehensive lead generation tool tailored specifically for the unique challenges faced by SMBs in Sub-Saharan Africa. By utilizing machine learning algorithms and data analytics, the agent can analyze market trends, customer behavior, and demographic information to identify high-potential leads. This targeted approach allows businesses to focus their marketing efforts on individuals and organizations most likely to convert into loyal customers. Key Features 1. Data-Driven Insights The AI agent aggregates data from various sources, including social media, online interactions, and industry reports. By processing this information, it provides businesses with actionable insights into customer preferences and market dynamics. This capability empowers SMBs to make informed decisions regarding their marketing strategies. 2. Automated Outreach 3. Lead Scoring and Prioritization