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.

Law4all

Law4All is an AI-driven legal aid ecosystem aimed at democratizing access to justice, particularly for marginalized and underserved communities. Legal systems are often expensive, complex, and difficult to navigate—especially for those unfamiliar with legal terminology or unable to afford professional help. Law4All simplifies this journey through an intelligent, multilingual chatbot that explains legal rights, documents, and procedures in plain language. It offers real-time case tracking via eCourts, retrieves relevant case laws and statutes using Retrieval-Augmented Generation (RAG), and generates personalized legal roadmaps based on case complexity and jurisdiction. To ensure ethical AI usage, Law4All includes a bias and hallucination detection module that flags inaccuracies and ensures fairness in responses. The platform also helps users locate nearby legal clinics and connect with pro bono lawyers, effectively bridging the gap between AI support and real human counsel. Data privacy is a top priority, secured with AES-256 encryption and anonymization protocols. By integrating accessibility, transparency, and ethical safeguards, Law4All aims to empower individuals with the tools they need to understand and assert their legal rights—confidently and safely.

Procurement for Public Sector Connectivity

UniSphere: Transforming Public Sector Procurement with AI UniSphere is an AI solution revolutionizing government procurement for connectivity projects through automated RFP analysis and bid evaluation. The Problem Government procurement suffers from inefficient, error-prone processes that lead to delays, wasted funds, and poor vendor selection. Creating comprehensive RFPs and objectively evaluating bids remains challenging for procurement teams. Our Solution UniSphere's procurement-specific Language Intelligence Model (LIM) processes complex documents with precision, built on open-source technologies for transparency and flexibility. Key Features RFP Analysis: Automatic requirements and criteria extraction. Technical specification identification. Gap detection in vendor proposals. Bid Evaluation: Objective bid scoring against requirements. Detailed strengths/weaknesses analysis. Best practices integration. Technology Built using Llama 3.1, IBM Granite, Hugging Face, Docker, PyTorch, and FastAPI—ensuring security, scalability, and seamless integration. Benefits for Users. Procurement Officers: Faster, more efficient processes. Technical Evaluators: Consistent, objective evaluations. Security Officers: Secure, compliant implementations. Challenges and Roadmap Current Focus: Security through secure self-hosting. Developing robust procurement datasets. Creating continuous improvement mechanisms. Future Plans: Enhanced security features. Risk prediction and sentiment analysis. Human-in-the-loop accountability. Ongoing model refinement. Conclusion UniSphere transforms public procurement by automating critical processes, helping governments save time, reduce costs, and improve decision-making. Our open-source approach ensures transparency and adaptability, building a foundation for more efficient, accountable procurement practices in connectivity projects.

AI Powered Mesh Network

AIM Network is an AI-powered application designed for network engineers, integrating seamlessly with existing monitoring tools and network logs. It automates troubleshooting, provides real-time solutions, and enhances operational efficiency while reducing downtime. By leveraging advanced AI technologies like machine learning and predictive analytics, AIM Network optimizes network performance and empowers engineers with actionable insights for proactive management. Core Components Zabbix Dashboard AIM Network integrates with Zabbix, an enterprise-class open-source monitoring solution, offering: Advanced distributed monitoring for servers, networks, and applications. Real-time notifications and alerting. Extensive data collection options (e.g., SNMP, IPMI, JMX). Customizable dashboards and visualization tools. Auto-discovery of network devices and configurations. AI Assistant The AI-powered assistant enhances troubleshooting efficiency with: Intelligent Log Analysis: Automatically identifies patterns and anomalies in network logs. Root Cause Analysis: Pinpoints underlying causes of issues, not just symptoms. Step-by-Step Resolution: Provides actionable guidance to resolve problems. Network Best Practices: Recommends solutions based on industry standards. Knowledge Base: Continuously learns from new issues to improve recommendations. Reduced Downtime: Speeds up issue resolution to minimize disruptions. Key Features Seamless integration with monitoring tools and logs. Real-time troubleshooting and resolution of network issues. AI-powered insights for proactive network management. Optimization of network performance, including speed, bandwidth, and reliability. Ability to answer general network questions using network documentation. Whether addressing latency, connection problems, or bandwidth constraints, AIM Network empowers engineers with expert-level recommendations, ensuring efficient and reliable network operations.

EneRIC - Connecting People

EneRIC is an innovative project designed to address connectivity challenges in developing regions, particularly in rural areas where deploying 5G networks remains economically unfeasible. High infrastructure costs (CapEx) and recurring operational expenses (OpEx) prevent telecommunications providers from expanding coverage, leaving millions without reliable internet access. To overcome these barriers, EneRIC leverages cutting-edge 5G technology and artificial intelligence to create a low-cost, sustainable, and efficient network solution. Unlike traditional deployment models, which rely on expensive physical infrastructure, EneRIC optimizes connectivity through: Virtualized Networks that reduce the need for costly hardware installations. AI-driven Optimization Algorithms to enhance network performance and resource allocation. Cost-Reduction Strategies that minimize operational and maintenance expenses. EneRIC utilizes open-source software for radio management, eliminating the need for proprietary hardware by virtualizing the Central Unit (vCU) and Distributed Unit (vDU). This approach enhances flexibility and reduces deployment costs. Furthermore, by implementing a *Near-Real Time RIC* (Radio Intelligent Controller) for gNB that follows the ORAN Alliance specifications, EneRIC ensures maximum interoperability and integrates cutting-edge technologies in next-generation telecommunications. This innovation enables the deployment of an *AI-driven network, where the Radio Access Network (RAN) can self-manage and dynamically optimize energy consumption. By leveraging artificial intelligence, EneRIC minimizes operational expenditures (OpEx) by up to **75%* in optimal scenarios, making 5G deployment more sustainable and cost-efficient.

EdenShack

**Inspiration** EdenHouse addresses food security by tackling rising grocery prices, vulnerable supply chains, accessibility issues, and the disruption from traditional systems. **Connection to AI and Power** EdenHouse leverages principles from distributed AI and power generation: - **Scalability**: Like Kubernetes scales applications, EdenHouse scales food production. - **Fault Tolerance**: Ensures continuous food supply despite setbacks. **What It Does** EdenHouse is a hydroponics orchestrator akin to Kubernetes: - **Hydroponics Setup**: Modular and efficient plant growth. - **AI-Assisted Monitoring**: Automates feeding, climate control, and lighting. - **Community System**: Facilitates trading and selling homegrown produce. - **Scalability**: Grows more units as demand increases. **Challenges** Ensuring user-friendly design, minimizing maintenance, integrating AI, and creating a community trading platform. **Accomplishments** Low-maintenance hydroponics system and a framework for community engagement. **What's Next** Expanding outreach, enhancing AI, partnering with local restaurants, and exploring subsidized solar panel options. Check Out Our Website: duo-keyboard-koalition.github.io GitHub Repo: [GitHub Repo](https://github.com/duo-keyboard-koalition)

Ai powered Network monitoring and Troubleshooting

This project introduces an innovative approach to network management by integrating Al-powered network monitoring with a voice-enabled chatbot. The primary goals are to proactively predict network failures and simplify the often complex process of network troubleshooting. Traditional network monitoring systems tend to be reactive, alerting administrators to issues only after they occur, and often require specialized expertise to interpret the data. This project offers a solution by leveraging artificial intelligence to predict potential failures before they impact network performance, coupled with a user-friendly, voice-enabled chatbot to assist with resolving network issues. Imagine being able to anticipate a network outage before it happens, and then resolving the issue with a simple voice command. This project showcases the powerful integration of Al, voice technology, and network monitoring. Key components include Al for failure prediction, weather-based monitoring, a voice chatbot, and email alerts, creating a comprehensive and intuitive network management system.

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