By compiling a simple program directly into transformer weights.
The post I Built a Tiny Computer Inside a Transformer appeared first on Towards Data Science.
Why storing and retrieving data isn’t enough to build reliable AI memory systems
The post Stop Treating AI Memory Like a Search Problem appeared first on Towards Data Science.
A deep-dive and practical guide to cross-encoders, advanced techniques, and why your retrieval pipeline deserves a second pass.
The post Advanced RAG Retrieval: Cross-Encoders & Reranking appeared first on Towards Data Science.
Introduction to Reinforcement Learning Agents with the Unity Game Engine
A step-by-step interactive guide to one of the most vexing areas of machine learning.
The post Introduction to Reinforcement Learning Agents with the Unity Game Engine appeared first on Towards Data Science.
Understanding BERTopic: From Raw Text to Interpretable Topics
Topic modeling uncovers hidden themes in large document collections. Traditional methods like Latent Dirichlet Allocation rely on word frequency and treat text as bags of words, often missing deeper context and meaning. BERTopic takes a different route, combining transformer embeddings, clustering, ...
From Karpathy’s LLM Wiki to Graphify: AI Memory Layers are Here
Most AI workflows follow the same loop: you upload files, ask a question, get an answer, and then everything resets. Nothing sticks. For large codebases or research collections, this becomes inefficient fast. Even when you revisit the same material, the model rereads it from scratch instead of build...
When Things Get Weird with Custom Calendars in Tabular Models
Since September 2025, we have had Calendar-based Time Intelligence in Power BI and Fabric Tabular models. While this feature offers great possibilities, we must be aware of its pitfalls. Here are some of them.
The post When Things Get Weird with Custom Calendars in Tabular Models appeared first on T...
AI can feel like a maze sometimes. Everywhere you look, people on social media and in meetings are throwing around terms like LLMs, agents, and hallucinations as if it’s all obvious. But for most people, it just feels confusing. The good news is, AI isn’t nearly as complicated as it sounds once you...
A long-form article featuring over 100 visualizations, covering a range of topics from how to build linear regression model, measure the quality and how to improve the model
The post A Visual Explanation of Linear Regression appeared first on Towards Data Science.
The mathematical foundations of Vision-Language-Action (VLA) models for humanoid robots and more
The post How Visual-Language-Action (VLA) Models Work appeared first on Towards Data Science.
This five day generative AI intensive course covers foundational models, embeddings, AI agents, domain-specific LLMs, and MLOps through a week of whitepapers, hands-on code labs, and live expert sessions.
Project Glasswing is World’s Most Powerful AI in Action
We already had a hint. AI would surpass most human capabilities someday. In the field of cybersecurity, that day arrived way too early, with the recent announcement of the Mythos Preview by Claude. The new AI model promises a level of coding skills that it is deemed to ‘surpass all but the most skil...
The Future of AI for Sales Is Diverse and Distributed
True creativity and innovation will come from human-agent collaboration. One human, millions of agents.
The post The Future of AI for Sales Is Diverse and Distributed appeared first on Towards Data Science.
Open-weight models are driving the latest excitement in the AI landscape. Running powerful models locally improves privacy, cuts costs, and enables offline use. But the open-source models are far and few! But Google‘s Gemma 4 is here to change that! This guide walks through what Gemma 4 is, would ex...
Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI
A practical system design combining open-source Bayesian MMM and GenAI for transparent, vendor independent marketing analytics insights.
The post Democratizing Marketing Mix Models (MMM) with Open Source and Gen AI appeared first on Towards Data Science.
From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs
How a hybrid PyMuPDF + GPT-4 Vision pipeline replaced £8,000 in manual engineering effort, and why the latest models weren’t the answer
The post From 4 Weeks to 45 Minutes: Designing a Document Extraction System for 4,700+ PDFs appeared first on Towards Data Science.
Handling Race Conditions in Multi-Agent Orchestration
If you've ever watched two agents confidently write to the same resource at the same time and produce something that makes zero sense, you already know what a race condition feels like in practice.
7 Steps to Mastering Retrieval-Augmented Generation
As language model applications evolved, they increasingly became one with so-called RAG architectures: learn 7 key steps deemed essential to mastering their successful development.
How to optimize context, a precious finite resource for AI agents
The post Context Engineering for AI Agents: A Deep Dive appeared first on Towards Data Science.
LLM Wiki Revolution: How Andrej Karpathy’s Idea is Changing AI
Think about revisiting items you’ve saved to Pocket, Notion or your bookmarks. Most people don’t have the time to re-read all of these things after they’ve saved them to these various apps, unless they have a need. We are excellent at collecting tons of information. However, we are just not very goo...