Why Popular AI Frameworks Are Actually Making Your Life Harder 😤
Author(s): MahendraMedapati Originally published on Towards AI. A Developer’s Journey from Framework Hell to Building Real AI Solutions Picture this: You’re excited to build your first AI application. You Google “best AI frameworks 2024” and everyone’s screaming about LangChain, CrewAI, and the …
Why GPT-5 Hits a Wall: The Real Story Behind AI’s Biggest Challenge 🤖💭
Author(s): MahendraMedapati Originally published on Towards AI. And how two groundbreaking research advances are trying to fix it You know that feeling when you’re trying to solve a 1000-piece jigsaw puzzle, and you can find all the corner pieces and edges, but …
🧠 Turn Any Text into Beautiful Interactive Maps: The Magic of AI-Powered Knowledge Graphs ✨
Author(s): MahendraMedapati Originally published on Towards AI. 🧠 Turn Any Text into Beautiful Interactive Maps: The Magic of AI-Powered Knowledge Graphs ✨ Ever wished you could turn a boring research paper into a visual story? Here’s how I discovered the coolest AI …
Fine-Tuning LLMs: From Zero to Hero with Python & Ollama 🚀
Author(s): MahendraMedapati Originally published on Towards AI. Ever wondered how to make AI models actually useful for YOUR specific needs? Let me show you how I went from confused beginner to fine-tuning wizard in just one weekend! Picture this: You’re trying to …
Understanding Model Context Protocol (MCP): The Future of AI Tool Integration
Author(s): MahendraMedapati Originally published on Towards AI. A beginner-friendly guide to how MCP is revolutionizing AI connections — with visual examples and step-by-step explanations By the end of this article, you’ll understand: Image of the Model Context Protocol (MCP) diagram illustrating AI …
Evaluating RAG Systems: The Metrics That Actually Matter
Author(s): MahendraMedapati Originally published on Towards AI. How to measure success and systematically improve your RAG system’s performance You’ve built your first RAG system, it’s retrieving documents and generating answers… but how do you know if it’s actually working well? How do …
Prompt Engineering for RAG: Crafting Templates That Turn Good Retrievals Into Excellent Answers
Author(s): MahendraMedapati Originally published on Towards AI. Prompt Engineering for RAG: Crafting Templates That Turn Good Retrievals Into Excellent Answers Master the art and science of prompt engineering specifically designed for Retrieval-Augmented Generation systems Master the art and science of prompt engineering …
Beyond Simple Similarity Search: Advanced Retrieval Techniques for Production RAG Systems
Author(s): MahendraMedapati Originally published on Towards AI. A comprehensive guide to building sophisticated retrieval systems that deliver precise, diverse, and relevant results Advanced retrieval systems combine multiple techniques for optimal results This article explores advanced retrieval techniques for Production RAG (Retrieval-Augmented Generation) …
The Make-or-Break Decision in RAG Systems: Choosing the Right Document Chunking Strategy
Author(s): MahendraMedapati Originally published on Towards AI. The way you split your documents could determine your RAG system’s success or failure Picture this: You’ve built a RAG system for your company’s employee handbook. Everything seems perfect until your HR manager asks: “What’s …
Building Your First RAG System: A Complete Step-by-Step Guide
Author(s): MahendraMedapati Originally published on Towards AI. Stop talking theory and start building — Create a working RAG system that can answer questions about your own documents Retrieval-Augmented Generation (RAG) has become one of the most practical applications of AI for working …
Vector Databases Performance Comparison: ChromaDB vs Pinecone vs FAISS — Real Benchmarks That Will Surprise You
Author(s): MahendraMedapati Originally published on Towards AI. Vector Databases Performance Comparison: ChromaDB vs Pinecone vs FAISS — Real Benchmarks That Will Surprise You This article accompanies my comprehensive YouTube video on vector database performance testing. You can watch the full tutorial here: …
Vector Databases Explained: The Engine Behind AI That Can Search Like Google
Author(s): MahendraMedapati Originally published on Towards AI. How specialized databases make large-scale AI applications possible — and why your next AI project probably needs one Imagine you’re Netflix, and you want to build an AI system to help users find movies. You …
Understanding Vector Embeddings: The Mathematical Heart of RAG Systems
Author(s): MahendraMedapati Originally published on Towards AI. Converting words into mathematical vectors to unlock the power of semantic search What if I told you that the key to making AI truly understand the meaning of text lies in converting words into mathematical …
🧠 “Attention Is All You Need” Explained (with PyTorch from Scratch)
Author(s): MahendraMedapati Originally published on Towards AI. Understand the Transformer Paper Deeply & Build It Yourself Step-by-Step In 2017, a single paper titled “Attention is All You Need” flipped the deep learning world on its head. From Research Paper Attention is All …
The Age of Autonomous Agents: How AI is Moving Beyond Chatbots to Do Your Bidding
Author(s): MahendraMedapati Originally published on Towards AI. The Age of Autonomous Agents: How AI is Moving Beyond Chatbots to Do Your Bidding Imagine an AI that doesn’t just answer your questions but proactively acts on your behalf. An AI that can book …
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