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A case study of something I actually shipped: a tool that lets an officer ask a question in plain words and get the right section of the new BNS, BNSS, and BSA, explained simply. Here is how it works and why I kept it boring.
After the Bhashini posts, a reader asked for the same treatment of PM GatiShakti. It is a very different kind of platform: not AI models, but one shared map for planning India's infrastructure. A simple, fact-checked explainer.
You do not need an expensive GPU server to do real, useful AI. A practical, honest look at what a single modest machine with no GPU can run, what it cannot, and how I host a whole platform on one small box.
Bhashini lets you speak in one Indian language and be understood in another. People assume it is one giant AI. It is not. A simple, fact-checked look at the real models behind it, the base model for translation, and how they were trained.
Large language models will confidently invent a law section that does not exist. Retrieval-Augmented Generation (RAG) is the fix. A plain-English explainer, grounded in a real legal-lookup tool I built for police.
Forget the hype. A grounded, plain-English guide to how the boring, explainable machine learning models can help a real investigating officer sort a pile of cases, spot the odd one out, and defend the reasoning, without ever pretending to be a detective.
Everyone talks about neural networks and LLMs. But the models quietly running your bank, your fraud alerts, and half of Kaggle are older, simpler, and far more boring. A plain-English tour of the real workhorses.
A plain-English guide to how AI, machine learning, neural networks, and large language models actually relate. They're not competing ideas — they're nested inside each other. Written by an ex-Army officer who now builds them.