RAG — Retrieval Full Matrix Evaluation
Author(s): Lorenzo Pozzi Originally published on Towards AI. 1 ] Introduction Choosing the right retrieval model is often the “make or break” moment for any Retrieval-Augmented Generation (RAG) system. While many developers focus on the LLM, the quality of the response is …
Crafting the Eyes for Thinking Machines: Rewiring the Retina- The Anatomy of ViTStruct
Author(s): Anagha Sharma M Originally published on Towards AI. Blending everything and trying to fetch the tastes 🙁 “There is no joy in a dinner where the soup, the main course, and the dessert are blended into a single, beige slurry. The …
Crafting the Eyes for Thinking Machines: The “White Box” VLM
Author(s): Anagha Sharma M Originally published on Towards AI. “In a voyage to build an open foundation for enthusiasts — to brainstorm and invent, rather than becoming sheep in the herd who call VLMs ‘expensive black boxes’ and settle for whatever crumbs …
From Power BI Dashboard to AI Agent in 30 Minutes: I Built the Tool That Unlocks 20 Million Hidden Ontologies
Author(s): Pankaj Kumar Originally published on Towards AI. A hands-on tutorial showing how to extract formal ontologies from Power BI models — and why I built it in 48 hours with Cursor AI Follow-up to: “The Power BI Ontology Paradox” [Image Caption]This …
Beyond AI Tools: How I Architect Systems That Actually Run the Business
Author(s): Abdul tayyeb Datarwala Originally published on Towards AI. My journey building operational intelligence — and why most AI initiatives quietly die I’ve built AI-enabled systems that scaled revenue, cut operational cost by multiples, and replaced chaos with clarity. I’ve also watched …
Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)
Author(s): Sivasai Yadav Mudugandla Originally published on Towards AI. Image generated with Microsoft Copilot · 1. Introduction: Why Computers Struggle with Language· 2. What Are Word Embeddings and Why Do We Need Them? ∘ The Map Analogy ∘ Why We Need Them …
Beyond Vision Language Action (VLA) Models: Moving Toward Agentic Skills for Zero-Error Physical AI
Author(s): Telekinesis AI Originally published on Towards AI. Vision Language Action (VLA) models are the hottest topic in Physical AI right now. If you are in the space of robotics or computer vision, your feed will be packed with it: massive funding …
Build LLM-Powered Documentation that Always Stays True to latest codebeases
Author(s): Cocoindex Originally published on Towards AI. A practical guide to using Pydantic, Instructor, and incremental processing with CocoIndex to generate always-fresh Markdown docs from source code. Code is Open-sourced, and available in Github. (Apache 2.0) ⭐ Star if you like it! …
From Questions to Insights: Data Analysis with LangChain’s Built-In Tools
Author(s): Vahe Sahakyan Originally published on Towards AI. In the first two articles of this series, we established why tools are essential for agentic systems and how those tools are constructed and orchestrated inside agents. What we deliberately avoided until now is …
How Tools Turn into Agents: What Actually Happens at Runtime
Author(s): Vahe Sahakyan Originally published on Towards AI. Many AI agent demos look convincing — until they fail in practice. Tools are defined correctly. Prompts seem reasonable. Yet the agent either calls the wrong tool, fails to call any tool at all, …
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