Hey everyone — I’m Dr Nazri, your host and fellow builder in this AI journey. I just dropped a brand new video on my YouTube channel all about AI agents and automation — how they're changing how we work, create, and scale. 🎥 Watch it here:👉 https://www.youtube.com/watch?v=YE57pKK5Ti4&t=20s In this group, we’ll go deeper into: ⚙️ Building real AI agents (with no or low code tools) 📦 Use cases in business, productivity, and beyond 🤖 Cool experiments, behind-the-scenes, and workshops 💬 Weekly check-ins and exclusive insights ✨ To get started: Introduce yourself below! Share what excites you most about AI or automation — and feel free to drop your LinkedIn or project links! Let’s co-build the future of work 🚀 — Dr Nazri, Your beloved AI Coach!

Proven experiences on how AI can really provide value at scales. Interesting part is when you can even earn some $$ without having client. Enjoy the video! Btw, I will be hiring freelancers for some AI Automation works (with n8n.com, make.com, Supabase & LLM experiences. Watch this space!

We’re excited to dive deeper into a powerful discovery: integrating Retrieval-Augmented Generation (RAG) with Graph technology significantly improves how we simulate Artificial Intelligence (AI), closely aligning it with Natural Intelligence (NI). Here's why it matters: - Natural Intelligence Alignment: RAG and Graph techniques combined reflect how our brains naturally process and retrieve information, resulting in more intuitive and accurate AI interactions (Lewis et al., 2020). - Spatial-Temporal Relevance: Leveraging Graph structures allows AI to understand connections not just in data, but in space and time—echoing principles initially proposed by Albert Einstein’s theory of relativity (Einstein, 1916) and further explored through Stephen Hawking’s work on cosmology and the nature of space-time (Hawking, 1988). - Enhanced Simulations: By merging these methodologies, we create smarter AI agents capable of more sophisticated reasoning, prediction, and decision-making, opening doors for applications in urban intelligence, autonomous systems, and beyond (Veličković et al., 2020). Ready to explore more about AI's future? Let's discuss and grow together here in our community! 📌 Citations: - Lewis, P., Perez, E., & Joshi, M. (2020). Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. arXiv preprint arXiv:2005.11401. - Einstein, A. (1916). Relativity: The Special and the General Theory. - Hawking, S. W. (1988). A Brief History of Time. Welcome aboard!