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Ranjan Kumar
Designing and Building Real-World AI Systems That Actually Work
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Category: Explainable AI

AI & ML/Explainable AI/GenAI/LLMs

When Models Stand Between Us and the Web: The Future of the Internet in the Age of Generative AI

Posted on September 26, 2025 by Ranjan Kumar / 0 Comment

Explore how generative AI models are transforming the internet — from mediating access to content to reshaping user behavior, search, and the open web economy. ...

AI & ML/Deep Learning/Explainable AI/GenAI

Provenance in AI: Auto-Capturing Provenance with MLflow and W3C PROV-O in PyTorch Pipelines – Part 4

Posted on August 29, 2025 by Ranjan Kumar / 0 Comment

AI engineers spend a lot of time building, training, and iterating on models. But as pipelines grow more complex, it becomes difficult to answer simple but cruc...

AI & ML/Deep Learning/Explainable AI/GenAI

Navigating AI Risks with NIST’s AI Risk Management Framework (AI RMF)

Posted on August 28, 2025 by Ranjan Kumar / 0 Comment

Practical Guide for AI Engineers with Supporting Tools Artificial Intelligence (AI) is no longer a research curiosity—it powers critical systems in healthcare, ...

AI & ML/Computer Vision/Deep Learning/Explainable AI/GenAI/Medical Imaging/Software Development

Provenance in AI: Building a Provenance Graph with Neo4j – Part 3

Posted on August 28, 2025 by Ranjan Kumar / 0 Comment

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...

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

Posted on August 28, 2025 by Ranjan Kumar / 1 Comment

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

Posted on August 27, 2025 by Ranjan Kumar / 1 Comment

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...

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MY BLOG POSTS

  • Stop Pasting Screenshots: How AI Engineers Document Systems with Mermaid
  • Building Production-Ready AI Agents with LangGraph: A Developer’s Guide to Deterministic Workflows
  • Choosing the Right LLM Inference Framework: A Practical Guide
  • Agent Building Blocks: Build Production-Ready AI Agents with LangChain | Complete Developer Guide
  • When Your Chatbot Needs to Actually Do Something: Understanding AI Agents
  • How Google’s SynthID Actually Works: A Visual Breakdown
  • Open Source AI’s Original Sin: The Illusion of Democratization
  • The Tyranny of the Mean: Population-Based Optimization in Healthcare and AI
  • The Splintered Web: India 2025
  • The AI Ouroboros: How Gen AI is Eating Its Own Tail
  • Building Agents That Remember: State Management in Multi-Agent AI Systems
  • Building Production-Ready Agentic AI: The Infrastructure Nobody Talks About
  • Asynchronous Processing and Message Queues in Agentic AI Systems
  • Playwright + AI: The Ultimate Testing Power Combo Every Developer Should Use in 2025
  • 🚀 Introducing My New Book: The ChatML (Chat Markup Language) Handbook
  • 🚀Hands-on Tutorial: Fine-tune a Cross-Encoder for Semantic Similarity
  • A Deep Dive into Cross Encoders and How they work
  • 🔎Building a Full-Stack Hybrid Search System (BM25 + Vectors + Cross-Encoders) with Docker
  • 🔎BM25-Based Searching: A Developer’s Comprehensive Guide
  • When Models Stand Between Us and the Web: The Future of the Internet in the Age of Generative AI

Categories

  • Agentic AI
  • AI & ML
  • AI Engineering
  • Computer Vision
  • Deep Learning
  • Deep Reinforcement Learning
  • Explainable AI
  • GenAI
  • Information Retrieval
  • IoT / Edge Computing
  • LLMs
  • Medical Imaging
  • Natural Language Processing – NLP
  • Python
  • Security
  • Software Development
  • Software Testing
  • Unstructured Data
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