“Talent is universal, but opportunity is not. Millions of underserved students especially in rural or low-income regions struggle with No access to expert career mentorship No awareness of digital/freelance opportunities Poor understanding of AI tools like ChatGPT/Midjourney Difficulty reading academic content or research papers Pressure from family or mental health issues Language or bandwidth barriers A web + SMS + voice-based AI mentor that provides: Personalized career guidance Real mentor connections Research paper summarization and prompt generation Prompt writing skill development Local scholarship and job discovery Culturally aware, low-bandwidth design for underserved communities

Child-Safe AI Mentor is an educational and interactive platform that allows users—categorized as children, teens, or mature audiences—to safely engage with AI. The system is built using FastAPI (backend), Streamlit (frontend), and a logging mechanism that stores potentially unsafe content. It features a dual flagging system: automatic detection of inappropriate content and manual user-flagging. Parents have access to a secure review panel where they can approve, delete, or clear flagged responses. The platform also includes a badge reward system for positive engagement and personalization options like avatars and themes. This project prioritizes safe, age-appropriate AI interaction in educational settings.

DefendX is an AI-powered cybersecurity solution focused on safeguarding edge devices by detecting and mitigating security threats like unusual login activities, background-running malware, and abnormal traffic at routers. Leveraging cutting-edge technologies such as Llama, Phi3, and Streamlit, DefendX offers real-time anomaly detection and threat analysis tailored for edge environments. Llama's robust natural language processing and Phi3's advanced machine learning algorithms enable the model to efficiently recognize and respond to potential security breaches. Integrated with a user-friendly Streamlit interface, DefendX provides seamless interaction, allowing users to easily monitor and address threats while ensuring optimal device performance and data privacy.

Build a flawless RAG based app w/o any hallucinations by using the newest Vectara’s HHEM model and win up to $1500! 🕒 24 hours to complete the challenge 💡 Implement RAG based app by utilizing HHEM model 🤝 Take part alone or form a team with other participants 🚀 3 finalists will share the Vectara’s credits worth of $4000

🔧 Spend 10 days launching your startup! 🚀 Improve your prototype previously developed at hackathons. 🤜 Collaborate with peers or work independently throughout the Hackathon. 🤖 Gain complimentary access to learning resources about Generative AI models, AI Agents, and beyond. 🚀 Explore opportunities with GAIA Startup Accelerator for Hackathon victors. 🌍 Connect and innovate alongside a worldwide AI community!

⌚ Dive into a 48-hour journey of creativity. 🚀 Compete to craft an app supercharged by Llama 3. 🎓 Expert mentors will guide you every step of the way. 🏆 Win an opportunity to participate in the Lablab NEXT acceleration program, exciting cash prizes, credits, and gear from LlamaIndex, Together AI & Zilliz 🧑🏻‍💻 Sign up before the Kick-Off Stream to secure your spot!