🔎 A Deep Dive into Cross-Encoders and How They Work
1️⃣ Introduction In AI systems that retrieve or generate information, ranking quality and relevance are critical. Whether you are building a RAG-based assistant...
Category: LLMs
✨When Models Stand Between Us and the Web: The Future of the Internet in the Age of Generative AI✨
1. Introduction The Internet once felt like a boundless public square: anyone could publish, anyone could read. But the rise of large language models (LLMs) lik...
🚀 Cursor AI Code Editor: Boost Developer Productivity with MCP Servers
1. Introduction The way we write code is changing faster than ever. For decades, developers have relied on traditional IDEs like IntelliJ IDEA, Eclipse, and Vis...
AI & ML/Computer Vision/Deep Learning/Deep Reinforcement Learning/Explainable AI/GenAI/LLMs/Medical Imaging/Natural Language Processing - NLP/Software Development
Provenance in AI: Tracking AI Lineage with Signed Provenance Logs in Python – Part 2
In modern AI pipelines, provenance — the lineage of datasets, models, and inferences — is becoming as important as accuracy metrics. Regulators, auditors, and e...
AI & ML/Computer Vision/Deep Learning/Deep Reinforcement Learning/Explainable AI/GenAI/LLMs/Medical Imaging/Natural Language Processing - NLP/Software Development
Provenance in AI: Why It Matters for AI Engineers – Part 1
1. Introduction: Why AI Needs a Paper Trail Imagine debugging a complex AI pipeline without knowing which version of the dataset was used, how the features were...
LLMs for SMEs – 001: How Small Businesses Can Leverage AI Without Cloud Costs
1. Introduction Ravi runs a small auto parts shop in Navi Mumbai. His day starts at 8 AM, but even before he lifts the shutter, his phone is already buzzing. Cu...
LLM-Powered Chatbots: A Practical Guide to User Input Classification and Intent Handling
1. Introduction If you’ve ever built a chatbot that confidently answered the wrong question, you know the pain of poor intent detection. Imagine a user typing: ...
Reranking for RAG: Boosting Answer Quality in Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) is one of the most effective techniques for making large language models (LLMs) answer accurately using external knowledge....
ChatML: The Structured Language Behind Conversational AI
If you’ve interacted with ChatGPT or built your own conversational AI, you might have wondered — how exactly does the AI know which parts of a message are from ...
Question Answer Chatbot using RAG, Llama and Qdrant
1. Introduction I have created this teaching chatbot that can answer questions from class IX, subject SST, on the topic “Democratic politics“. I hav...