How to Perform Effective Project Management with AI
Become a more productive software engineer with LLMs The post How to Perform Effective Project Management with AI appeared first…
Category: General
Loop Engineering for RAG: The Small Loops Inside Each Step, the Big Loops Across the Pipeline
Enterprise Document Intelligence [Vol.1 #13bis] – The four bricks return useful results most of the time. Loop engineering is what…
Designing a Persistent Knowledge Layer That Refuses to Guess
RAG Retrieves, It Never Remembers. A vendor-neutral blueprint for applications that accumulate understanding. Includes a complete Azure-native implementation (Microsoft Foundry,…
Running SQL Concurrently Across Three Remote DuckDB Servers with Quack
A small experiment in remote SQL execution The post Running SQL Concurrently Across Three Remote DuckDB Servers with Quack appeared first…
Mathematical Experiments Are Becoming Abundant Through Human-Machine Teaming
Two open problems, exact-arithmetic checking and a proof assistant, over a single weekend. The post Mathematical Experiments Are Becoming Abundant Through Human-Machine…
How to Shine as a Data Scientist in the Vibe Coding Era
Here’s how to be the Data Scientist who thrives in a world where coding is a commodity. The post How…
A Day in the Life of a Data Scientist in 2026
How AI has massively changed my day-to-day workflow The post A Day in the Life of a Data Scientist in…
RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop
Enterprise Document Intelligence [Vol.1 #13] – Putting the patterns together, and why this is what “agentic RAG” should look like…
Found Friday S5I6: Privacy and Practical AI
FOUND FRIDAY · SEASON 5 · ISSUE 6 Privacy is the control layer for practical AI. This issue starts with…
My Model Was Cheating on Its Own Test
A preprocessing pipeline let my car price model peek at the test set before the exam, and the twelve points…
I Made an LLM Lay Siege to My Minecraft House
Can a language model do live adversarial level design? Yes, emphasis on the adversarial part The post I Made an…
How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs
Google’s Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses…
Before Full Agentic RAG: Know How You Decide, and the Parsing Methods You Pick From
Enterprise Document Intelligence [Vol.1 #5nonies] – Nature, plan, execute, synthesize: closing brick 1 with a dispatcher that reads each PDF’s…
Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works
From one gradient to every gradient The post Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works appeared first…
Putting sign language AI into users’ hands
Introducing sign-language-to-text (SL2T), our breakthrough model powering new sign language features for Deaf and hard of hearing users.
Building Multimodal Workflows with a Local LLM
Image inputs and structured outputs with Gemma 4 and Ollama The post Building Multimodal Workflows with a Local LLM appeared…
How to Place Vertiport Locations in Any City Using Geospatial Machine Learning
A reproducible Lagos case study with population data, transport access, and airspace constraints The post How to Place Vertiport Locations…
Stop Calling the First Significant Day a Win
Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost…
Should AI Developers Make the Switch from Polars to Pandas?
Not all Python data libraries are created equal! The post Should AI Developers Make the Switch from Polars to Pandas?…
The Budget Split That Explains Itself
How to diversify a budget without losing the shadow prices that explain the result The post The Budget Split That…
Can a Local LLM Run My AI Assistant?
I replayed the same 27 real production tasks through two local models, one hardware upgrade apart, to find out what…
With a feel for physics, AI models simulate a wider range of real-world scenarios
Artificial intelligence models are jacks of many trades, including writing, generating images, and creating 3D models. But they aren’t as…
How to Effectively Deploy Code With Claude Code
Learn how to optimize your CI/CD pipeline for coding agents The post How to Effectively Deploy Code With Claude Code…
Building an Agent-Ready Data Warehouse: What Traditional Architectures Do Wrong
Giving an AI agent access to a data warehouse doesn’t automatically make it agent-ready. The real challenge lies in teaching…
Variational Autoencoders (VAEs) Explained: From Theory to ELBO and the Reparameterization Trick
A clear, math-first walkthrough of how VAEs learn to generate new data The post Variational Autoencoders (VAEs) Explained: From Theory…
SPP-Net Paper Walkthrough: Breaking the Fixed-Size Constraint
Learn how Spatial Pyramid Pooling enables CNNs to handle any image size, with a from-scratch PyTorch implementation The post SPP-Net…
I Thought Loading Data Was the Finish Line. It Was the Starting Point.
Building my first dbt models and learning what “analysis-ready” data actually means The post I Thought Loading Data Was the…
How to Implement Structured Output with Local LLMs
Why use it? How to implement it? What can we do when it fails? The post How to Implement Structured…
Before Q, K, and V: Reconstructing the Transformer
Many Transformer explainers start with the finished architecture. We ask why it looks the way it does. The post Before…
Building a Streamlit UI for My LangGraph AI Agent
Building a production-ready web interface for a stateful LangGraph agent The post Building a Streamlit UI for My LangGraph AI…
Matplotlib vs Plotly: Which Python Chart Tool Should You Choose?
From Static Plots to Interactive Data Exploration The post Matplotlib vs Plotly: Which Python Chart Tool Should You Choose? appeared first…
Loop Engineering for Listing Questions: When the Answer Is Every Passage, Not the Top One
Enterprise Document Intelligence [Vol.1 #12] – The category of question most RAG pipelines silently fail on, and the pipeline shape…
My Fall-Detection Model Scored 94%, and It Was Lying to Me
How a single evaluation choice inflated my results by 25 points, and what rebuilding honestly taught me about ML systems…
I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.
A step-by-step guide to building a data agent and conversational interface that let business users to explore data in natural…
Last Month’s Machine Learning Lessons Learned
The downside of conference travel The post Last Month’s Machine Learning Lessons Learned appeared first on Towards Data Science.
I Built a Tool-Calling Agent in Python. Here’s How I Debugged It
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post…
Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer
Enterprise Document Intelligence [Vol.1 #11] – When the first answer points elsewhere in the document, the pipeline loops back to…
How a Frontier Model Gets Built, Read from the Kimi K3 Report
An open, 2.8-trillion-parameter model shipped with 47 pages of its own recipe. Reading it tells you what building a frontier…
Introduction to Semi-Supervised Learning
A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data. The post…
Is This Slop? Detecting AI-Generated Content Without a Model
Research-backed cues to detect LLM-generated text along with the mathematical intuition as to ‘why’ The post Is This Slop? Detecting…
Building Document Structure with Loop Engineering: Recovering a PDF’s Outline from Body Typography for RAG
Enterprise Document Intelligence [Vol.1 #5octies] – Rules propose, LLM validates: six deterministic signals on span-level typography surface heading candidates, one…
Solving the solvent problem
Lithium-ion batteries are the leading choice in today’s electric vehicle and battery energy storage system industries, but they contain a…
The Medallion Data Architecture: An Introduction
A practical guide to Bronze, Silver and Gold, with a working Python and DuckDB example The post The Medallion Data…
How to Get More Statistical Power from Fewer Research Participants
An online simulation and a novel method for increasing power The post How to Get More Statistical Power from Fewer…
Are Home Teams Favoured by Referees in Football/Soccer?
Data Storytelling Series, Chapter 1 The post Are Home Teams Favoured by Referees in Football/Soccer? appeared first on Towards Data…
Using Agents as Tools
Building manager–specialist workflows with the OpenAI Agents SDK The post Using Agents as Tools appeared first on Towards Data Science.
The benefits of medical AI assistance vary based on user expertise
A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis. A…
Alexander Rakhlin named director of the MIT Statistics and Data Science Center
Alexander “Sasha” Rakhlin PhD ’06, the Distinguished Professor in Data, Systems, and Society at the MIT Institute for Data, Systems,…