RAG Evaluation Frameworks Compared: RAGAS vs TruLens vs DeepEval
LLMs are getting stronger every day, and building a RAG pipeline has never been easier. Knowing whether it actually works is not. Most teams ship a RAG system, see decent-looking answers, and call it done, until users hit hallucination, missing context, or irrelevant chunks. That’s where evaluation ...
That Is Embarrassing: Why Frontier AI Still Makes Things Up, and What to Do About It
The best AI models still hallucinate. These hallucinations are sometimes funny, and sometimes cause actual damage. In this post we will consider recent tales of AI hallucinations, and then look under the hood to understand why they happen.
The post That Is Embarrassing: Why Frontier AI Still Makes T...
RAG Was Always a Temporary Workaround. What is Next?
Vector databases are a temporary bridge. Discover why the next AI infrastructure revolution relies on persistent neural state and strict latency budgets, not on vector databases.
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Behind the Scenes of Distributed Training and Why Your GPU Wiring Matters as Much as Your Strategy
A measured look at distributed training, from DDP and FSDP to the ZeRO stages in between, and why the wiring between your GPUs matters as much as the strategy you choose
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Find the optimal way to interact with your coding agents
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Loop Engineering for Hierarchical Retrieval: Reading a Long Document by Its Table of Contents
Enterprise Document Intelligence [Vol.1 #7quater] - A 492-page document has a 358-entry table of contents. You can’t read it all, and top-k over every page mixes the answer with its neighbours. Route through the TOC instead: a bounded loop inside retrieval that saves tokens and lifts precision
The p...
7 Steps to Automating Descriptive Statistics with Python
Stop writing mean() and std() for every column. Learn how to automate descriptive statistics in Python and generate publication-ready summary tables in just a few steps.
Where Does an AI’s Personality Actually Come From?
They aren’t designed, you can’t help perceiving one anyway, and that makes them an engineering problem almost no one is solving.
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How to Clean Messy CSV Files with Python: A Beginner’s Guide
Learn how to clean CSV files with pandas by handling missing values, duplicate rows, messy text, wrong data types, mixed date formats, invalid emails, and currency values.
Inside the Subspace Where Spurious Correlations Are Born
Why small samples can produce large correlations by chance, and why large does not always mean meaningful
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A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers
Enterprise Document Intelligence [Vol.1 #9A] - Same paper, same question as Article 1. One upgraded contract per brick: document parsing, question parsing, retrieval, generation
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Zero-Shot Local Document Parsing with Gemma 4: Treating PDFs as Images
Treating PDFs as images and feeding those images to Gemma 4 dissolves the scanned-versus-digital distinction that makes every text-extraction pipeline fragile. Fix that.
Increase the effectiveness of your coding agents through end-to-end testing.
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Validating the RAG Answer Before the User Sees It: Spans, Quotes, and the Feedback Loop
Enterprise Document Intelligence [Vol.1 #8C] - Structured output is the start of validation, not the end: check the evidence, accept not-found, loop the feedback
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YOLO26 Tutorial: Object Detection, Pose Estimation & More
Looking to model to implement pose estimation? I know something that can perform detection, instance segmentation, pose estimation and classification, all of that in real-time. Yes, I’m talking about the YOLO26 from ultralytics. It can aid security systems or can be fine-tuned to detect even smalle...
Large Action Models (LAMs) vs Agentic LLMs: What’s the Real Difference?
You tell your AI “Polish my email and send it.” Same sentence, three outcomes. The gap between Large Action Models (LAMs) and agentic LLMs is one of the most practically important distinctions in AI today, and also one of the least clearly explained. In this article, we cut through the confusion thr...
AI Agents Explained: What Is a ReAct Loop and How Does It Work?
How agents reason, act, and observe their way to a final answer, one step at a time
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