Can You Predict a Subway Delay Before Transit Officials Announce It?
Author(s): Charlie Taggart Originally published on Towards AI. How I used MBTA train telemetry and machine learning to call out service breakdowns 30+ minutes early I‘m consider myself a patient person. But nothing tests that patience like standing on a T platform …
The Complete Guide to Guardrails: Building AI Agents That Won’t Go Rogue
Author(s): Divy Yadav Originally published on Towards AI. Photo by Gemini Note: If you’re implementing guardrails soon, this is essential reading; pair it with LangChain’s official docs for edge cases. Let’s begin Picture this: You’ve built an AI agent to handle customer …
From Basic RAG to Advanced Retrieval: A Practical Roadmap Using the Modern RAG Stack
Author(s): Anubhav Originally published on Towards AI. Build intelligent, adaptive AI that understands and utilizes all your data sources General-purpose LLMs are incredible, but they have a fundamental blind spot: your data. Their knowledge was frozen at a specific point in time, …
Setting Up TensorFlow with GPU (CUDA): A Step-by-Step Installation Guide
Author(s): Muaaz Originally published on Towards AI. If you are writing Deep Learning code on a machine with a GPU, TensorFlow will default to running on the CPU. This happens because TensorFlow does not automatically select the best hardware. To use the …
Why 90% of Agentic RAG Projects Fail (And How to Build One That Actually Works in Production)
Author(s): Divy Yadav Originally published on Towards AI. Photo by Gemini Most enterprise AI pilots fail. McKinsey’s research found only 10–20% of AI proofs-of-concept scale beyond pilots. Why? Teams treat production systems like demos. I’ve seen companies spend six months building agentic …
This is How Google Finally Fixed AI Images: The Secret Sauce Behind “Nano Banana”
Author(s): Sayan Chowdhury Originally published on Towards AI. This is How Google Finally Fixed AI Images: The Secret Sauce Behind “Nano Banana” If you’ve been on the internet in the last six months, you’ve seen them: those hyper-realistic 3D figurines of your …
The “Sora” Trap: Why Meta’s V-JEPA 2 Proves That Hallucinating Pixels is Not “Planning”
Author(s): Siddharth M Originally published on Towards AI. While the world obsesses over AI video generation, a team at Meta just dropped a 1-Billion parameter “World Model” that plans robot actions by ignoring reality’s noise. Here is the definitive engineering deep dive …
Claude Just Broke Bioinformatics
Author(s): Gowtham Boyina Originally published on Towards AI. Anthropic’s secret plugin marketplace lets AI auto-search PubMed, analyze single-cell data, and generate publication-ready figures — no more switching tabs. (And it’s already live.) If you’ve used Claude Code for bioinformatics or research, you’ve …
We’ve Been Building AGI Wrong This Whole Time
Author(s): Gaurav Shrivastav Originally published on Towards AI. AGI isn’t about smarter models — it’s about giving them the right tools. I realized something uncomfortable last week. Image Credit: Nano Banana ProThe article discusses the misconception that advancing Artificial General Intelligence (AGI) …
What Mistakes Did I Make in Vibe Coding Genie-Hi
Author(s): Gabrielle Y Originally published on Towards AI. The First Leap: When Vibe Coding Feels Like Magic When I first started vibe coding Genie-Hi, I genuinely thought it would simply help me move faster. I typed a few sentences describing what I …
How Video Streaming Actually Works: Why YouTube Starts Playing in 3 Seconds (System Design Explained)
Author(s): Divy Yadav Originally published on Towards AI. Photo by Gemini You click play on a YouTube video. Within 2 seconds, it starts playing. But here’s what blows my mind: that video is 4 GB, sitting on a server thousands of miles …
The Complete RAG Playbook (Part 3): Advanced Architectures
Author(s): Ravi Kumar Verma Originally published on Towards AI. The Complete RAG Playbook (Part 3): Advanced Architectures In Part 2, we upgraded the basic RAG pipeline with 12 techniques that improved chunking, context, queries, and retrieval. Those techniques work great — until …
The Complete RAG Playbook (Part 4): Evaluation & Choosing What Works
Author(s): Ravi Kumar Verma Originally published on Towards AI. The Complete RAG Playbook (Part 4): Evaluation & Choosing What Works We’ve covered 19 RAG techniques across three parts. You’ve seen chunking strategies, context enrichment, query transforms, rerankers, and advanced architectures. But there’s …
No Libraries No Shortcuts: Reasoning Models from Scratch with PyTorch — Part 1
Author(s): Ashish Abraham Originally published on Towards AI. The no BS Guide to implementing LLMs with Mixture of Experts, RoPE, and Grouped Query Attention from scratch There is this term called “moment” that has been spooking and exciting AI investors of this …
The ML Evaluation Math You Can Actually Trust
Author(s): Akshat shah Originally published on Towards AI. Train/Val/Test, Cross-Validation, and Data Leakage Photo by Thomas T on Unsplash Machine learning isn’t just “a model that predicts things.” In the real world it’s a measurement process. You build a pipeline, and you …
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