Navigating AI Risks with NIST’s AI Risk Management Framework (AI RMF)
Practical Guide for AI Engineers with Supporting Tools Artificial Intelligence (AI) is no longer a research curiosity—it powers critical systems in healthcare, ...
Practical Guide for AI Engineers with Supporting Tools Artificial Intelligence (AI) is no longer a research curiosity—it powers critical systems in healthcare, ...
In Part 2, we built a ProvenanceTracker that generates signed, schema-versioned lineage logs for datasets, models, and inferences. That ensures trust at the dat...
In modern AI pipelines, provenance — the lineage of datasets, models, and inferences — is becoming as important as accuracy metrics. Regulators, auditors, and e...
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...
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...
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: ...
Retrieval-Augmented Generation (RAG) is one of the most effective techniques for making large language models (LLMs) answer accurately using external knowledge....
1. Introduction I have created this teaching chatbot that can answer questions from class IX, subject SST, on the topic “Democratic politics“. I hav...
An ability is emergent if it is not present in smaller models but is present in larger models. [1] Scaling up language models has been shown to improve predicta...