The Great LLM Convergence: When Everyone’s Best Becomes Nobody’s Advantage
Author(s): Ali Khalilvandi Originally published on Towards AI. The AI landscape in late 2025: where differentiation goes to die. Image credit: Gemini Nano Banana Last year I had an answer when people asked me what LLM to use. GPT-4. Done. This year? …
More than Chat: Fixing Multilingual Search Queries with LoRA finetuning on Apple Silicon
Author(s): Sreejith Sreejayan Originally published on Towards AI. I recently read a fantastic engineering article from Zepto (one of India’s fastest-growing quick-commerce apps) about a difficult search problem. In India, people don’t just search in English. They search in a mix of …
Why Most RAG Systems Fail in Production and the Simple Fix That Improves Accuracy Fast
Author(s): Divy Yadav Originally published on Towards AI. Source: By the author You spent two weeks building a RAG application. It retrieves documents. It generates answers. You tested it with a few questions. It looked good. Then you put it in production …
DOCKER’S MCP TOOL KIT: The App Store for Real-World AI Agents
Author(s): Baivab Mukhopadhyay Originally published on Towards AI. DOCKER’S MCP TOOL KIT: The App Store for Real-World AI Agents AI agents are finally good enough to be useful, but most teams hit the same wall: connecting those agents to real tools is …
Running Unsloth On a Jetson AGX Orin Device With Jetson-Containers
Author(s): Stephen Cow Chau Originally published on Towards AI. Background I have been for a long time container first, mainly because of the ease of environment isolation (including but not limited to system package, programming library package…). For Jetson it’s a little …
Data Exploration with Python: A Hands-On Demo in EDA (and Why It’s Essential for Model Building)
Author(s): Faizulkhan Originally published on Towards AI. Exploratory Data Analysis (EDA) is the bridge between raw data and reliable machine-learning models. In this post, we will learn the “why” and the “how” through a complete, runnable example in Python using NumPy, Pandas, …
The Builder’s Notes: I Tested 5 De-Identification Tools on 10,000 Clinical Notes. Most Failed on the Same 3 Edge Cases
Author(s): Piyoosh Rai Originally published on Towards AI. Presidio caught 94% of patient names. The 6% it missed included the only patient who could actually be re-identified. Here’s how to benchmark de-identification tools before they break in production. 99% accuracy on benchmarks. …
Data Imputation in Machine Learning: A Practical, No-Nonsense Guide (ML Chapter -2, Module-2)
Author(s): Sayan Chowdhury Originally published on Towards AI. Missing data shows up everywhere: surveys, logs, sensors, medical records, finance datasets, you name it. And if you feed missing values directly into most ML models, they’ll crash or behave unpredictably. That’s why data …
Agentic AI Fundamentals: Part 3— How Do You Trust an AI Agent in the Real World?
Author(s): Anjanadry Rane Originally published on Towards AI. In the town of Greenfield, Max has grown from a kid with a good sense of direction into something more: a reliable guide who helps others navigate the forest. We’ve been using Max as …
AI Cost Reduction Outlook: How to Cut Operational Expenses Smartly
Author(s): Ruben Melkonian Originally published on Towards AI. How much is your organization losing every quarter by ignoring AI cost reduction potential? According to a recent McKinsey study [1], companies that have already applied gen AI across most critical operations see cost …
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