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😌 Completed the 📚 Diploma in English Language and Literature ✍🏻 by 🏅 Scoring 91% 🏆

In a recent educational lecture, Andrej Karpathy, one of the creators of ChatGPT, provides an introduction to Large Language Models (LLMs). LLMs are advanced technologies that can process and generate human-like text. Karpathy highlights the fut

🚀 Narayana Murthy Sparks Debate on India's AI Ambitions! 🇮🇳🤖 Infosys founder NR Narayana Murthy has questioned India's push to develop homegrown large language models (LLMs). He highlights key challenges like: 🔹 Lack of robust databases 📊 🔹

Choosing the best programming language to learn first depends on your goals, but Python is often the best starting point. It's beginner-friendly, widely used, and great for web development, automation, data science, and more. Other good options inclu

🚀 Exploring Conversational AI + Automation: My journey with Voiceflow, Retell AI & n8n Over the past few weeks, I’ve been diving into chatbots, voice agents & workflow automation — and it’s been a rewarding learning curve! 🔹 Built a chatbot on Vo

The AI Arms Race: OpenAI vs. DeepMind vs. Deepseek vs. Meta AI 🤖 Who will dominate the future of AI? The battle between OpenAI, Google DeepMind, Deepseek, and Meta AI is shaping the next wave of LLMs, agentic AI, and multimodal intelligence. 🔥 Ke

My Favorite AI & ML Books That Shaped My Learning Over the years, I’ve read tons of books in AI, ML, and LLMs — but these are the ones that stuck with me the most. Each book on this list taught me something new about building, scaling, and underst

Are there any data scientists here? What new ways are you using large language models (LLMs) in your everyday tasks? Do you think we should include LLM topics in data science courses? If so, what should we focus on teaching? For example: - The bas

Step into the Shadows: Exploring Dark Tourism Curious about the world’s hidden corners? Dark tourism is your gateway to places where history and mystery intertwine. Picture yourself wandering through a haunted mansion, exploring an abandoned asylum,

Retrieval-Augmented Generation (RAG) is a GenAI framework that enhances large language models (LLMs) by incorporating information from external knowledge bases, improving accuracy, relevance, and reliability of generated responses. Here's a more det