Working to automate nuclear plant operations
For nuclear to be considered as a viable clean energy source, it has to be competitively priced and economical to…
Category: General
When Data Science Makes Us Sad: The Story of an Overbooked Flight
$8 million vs $5k + Potentially Going Viral The post When Data Science Makes Us Sad: The Story of an…
Most RAG Hallucinations Are Extraction Errors: Seven Patterns for a Typed Generation Contract
Enterprise Document Intelligence [Vol.1 #8ter] – Naming the RAG error correctly matters: model reads the context, so a wrong answer…
Lessons Learned After 8.5 Years of ML
Patience, Optimism, Discipline, Projects, Teams The post Lessons Learned After 8.5 Years of ML appeared first on Towards Data Science.
Why Adding More AI Agents Made Our System Slower
The hidden cost of asynchronous systems, how tiny CPU tasks quietly became our biggest bottleneck while scaling hundreds of LLM…
MIT projects selected for funding under US Department of Energy’s Genesis Mission
MIT researchers are set to contribute to the U.S. Department of Energy’s (DOE) Genesis Mission, with 15 collaborative projects among those…
Professor Emeritus Dimitri Bertsekas, influential computer scientist and prolific author, dies at 83
Dimitri Bertsekas PhD ’71, the Jerry McAfee (1940) Emeritus Professor in Engineering in the Department of Electrical Engineering and Computer…
Loop Engineering for RAG Generation: iterate top-k one at a time
Enterprise Document Intelligence [Vol.1 #8bis] – Two regimes for sending retrieved candidates to the generation brick, the sufficiency signal that…
Build an LLM Agent That Can Write and Run Code
A hands-on walkthrough of code execution with the OpenAI Agents SDK and Docker The post Build an LLM Agent That…
Accelerating the frontiers of scientific discovery: Google’s $40M commitment to the Genesis Mission
Google commits $40M in AI tokens and credits for the Genesis Mission
Detecting Vulnerabilities in Agent Skills with SkillSpector: From Green Checkmark to Real Security Judgment
Static analysis nailed the malicious skill and over-flagged the useful one. The gap between those results is where human judgement…
Prompt Engineering Isn’t Enough: How Four Bricks of Context Engineering Stop RAG Hallucinations
Enterprise Document Intelligence [Vol.1 #9bis] – Your RAG isn’t hallucinating, it’s answering the wrong context faithfully. On real NIST and…
I Tried Fine-Tuning a Robot AI Model on Colab. Here Is What Worked
A reproducible 100-step LoRA fine-tuning run for OpenVLA, with dataset checks, Colab setup, training metrics, and W&B evidence. The post…
Introducing Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber
We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.
How Much of a Data Science Workflow Can Run on a GPU Today? Part 1: Accelerating Data Preparation
Exploring GPU acceleration with cuDF, cudf.pandas, and the Polars GPU Engine The post How Much of a Data Science Workflow Can…
How to Run Claude Code Agents for 24+ Hours
Apply long-running coding agents to become a more productive engineer The post How to Run Claude Code Agents for 24+…
Water Cooler Small Talk, Ep. 12: Byzantine Fault Tolerance
How do you make decisions when you can’t trust anyone in the room? The post Water Cooler Small Talk, Ep.…
Backpropagation Explained for Beginners (Part 1): Building the Intuition
Let’s discover how neural networks learn, step by step The post Backpropagation Explained for Beginners (Part 1): Building the Intuition…
Loop Engineering for RAG Question Parsing: The Small Loop That Runs Before Retrieval
Enterprise Document Intelligence [Vol.1 #6quinquies] – Prompt engineering, then context engineering, then loop engineering. On the question side, the loop…
Your AI Agent Passed Every Eval. Finance Still Killed It.
An AI agent passed every metric in the eval harness I published, then the CFO killed it — its successful…
Many Companies Use AI. Few Know How to Build an AI-Native Enterprise Data Platform.
A practical enterprise AI architecture with data agents, AI-powered QA, and AI governance. The post Many Companies Use AI. Few…
Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It
Enterprise Document Intelligence [Vol.1 #10A] – The escalation cascade and the free, deterministic checks that flag a failed parse before…
How to Improve Customer Retention in FinTech
A practical guide to combining pre-churn scoring with uplift modelling for smarter retention. The post How to Improve Customer Retention…
Following the questions where they lead
Ever since she was a child playing on her family’s farmland in Wisconsin, Bailey Flanigan was guided by her own…
How to Work Effectively with GPT-5.6
Maximize the latest OpenAI model The post How to Work Effectively with GPT-5.6 appeared first on Towards Data Science.
Using Classical ML to Empower AI Agents
On the value of building on existing foundations The post Using Classical ML to Empower AI Agents appeared first on Towards…
Context Engineering Isn’t Enough — A Loop Engineering Experiment With No LLM Inside the Loop
Everyone is talking about loop engineering, but most discussions assume an LLM sits at the center of the loop. I…
One RAG Pipeline, Four Very Different PDFs: Same Four Bricks, Every Answer Typed and Cited
Enterprise Document Intelligence [Vol.1 #9B] – One call wires the four upgraded bricks together, run on a paper, a NIST…
Prepare These 5 Assets Before Your AI Agents Take On More Work
How to define recurring work, give AI the right context, explain what high-quality work looks like, and decide where human…
How to Get the Most Out of Claude Fable 5
Maximize your Claude Fable 5 usage The post How to Get the Most Out of Claude Fable 5 appeared first…
Our approach to bioresilience
Google DeepMind and Isomorphic Labs are sharing our joint approach to bioresilience and AI models.
A better way to turn 2D designs into 3D models for rapid prototyping
Engineers often use vision-language models to produce new designs, such as for airplane or automobile components. To simulate how those…
3 Questions: Neural transparency and the future of AI design
Millions of people are now designing their own personalized artificial intelligence companions, yet most have little idea how those creations…
Don’t Let Claude Grade Its Own Homework
Cross-provider PR review with Codex in GitHub Actions, and why a second opinion from a different lab beats any self-review…
Building Trustworthy Production RAG Systems Through Continuous Evaluation
A practical guide to building an evaluation workflow that catches retrieval failures, hallucinations, and performance drift before they reach users…
How I Mastered Data Structures and Algorithms for ML (In 6 Weeks)
The strategies, questions, and process I used to ace coding interviews. The post How I Mastered Data Structures and Algorithms…
Most RAG Hallucinations Are Retrieval Failures: How the Retrieval Brick Decides What the Model Can Invent
Enterprise Document Intelligence [Vol.1 #7quinquies] – Hallucination is usually garbage-in. Fix retrieval, and the model has nothing left to make…
Helping AI models to meet the real world
Systems using artificial intelligence to enhance forecasting, planning, and decision-making in businesses have been proliferating in recent years, but in…
How I’m Making Sure My Analytics Career Doesn’t Get Eaten by AI
The analytics career I signed up for five years ago doesn’t exist anymore, and honestly, I am fine with that.…
Can AI build a jet engine? JARVIS Challenge tests role of AI copilots in tough-tech engineering
Artificial intelligence has rapidly transformed software engineering. Generative AI and large language models (LLMs) can create huge volumes of code…
A Gentle Introduction to Autoencoders & Latent Space
Introduction Heavy computation is a well-known problem in various ML algorithms today, especially when generative AI is applied to text,…
Pydantic + OpenAI: The Cleanest Way to Get Structured Outputs from LLMs
How to stop parsing JSON by hand and start trusting your model’s output The post Pydantic + OpenAI: The Cleanest…
Empowering India’s next generation of innovators with ATL Saathi
Google and AIM launched ATL Saathi, a Gemini-powered AI tool empowering Indian educators in robotics labs.
How MIT students are helping to prevent cyberattacks
In May 2019, the government of Baltimore, Maryland, fell into chaos. Cybercriminals had locked the city out of many of…
Agentic RAG: Let the Agent Search
A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search…
Context Rot: Why Claude Code Sessions Decay, and How to Govern Them
Long sessions rot quietly, well before any token limit is reached. Here’s why, and how to govern your context in…
Building Models in Two Worlds: From Latent Constructs to Behavioral Signals
My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything…
The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices
A framework for aligning agentic AI with enterprise intent to ensure consistent scenario‑wide autonomous behavior. The post The Three Dimensions…
New method aims to keep kids safe from illegal AI-generated content
With the exploding popularity of generative artificial intelligence, many open-source models are now available online for anyone to adapt for…
RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each
Two techniques, two different problems, and why the question is not really “which one wins” The post RAG vs Fine-Tuning…