I Built a Clinical AI Agent — and It Skipped the Tools I Gave It
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. An evaluation of tool coverage in local healthcare agents, with a simple fix. I thought my healthcare AI agent would call my lab-checking tool every time it encountered lab values. Instead? Only 1 …
RAG Techniques You Must Know in 2025
Author(s): Ahmed Boulahia Originally published on Towards AI. RAG is no longer just about answering questions; here are the top techniques in 2025 that every AI builder should know. By now, you’ve probably seen tons of videos and projects about RAG (Retrieval-Augmented …
CSV Plot Agent with LangChain & Streamlit: Your Introduction to Data Agents
Author(s): Sarah Lea Originally published on Towards AI. How you can learn the basics of tool-based agents with LangChain, GPT-4o-mini and Streamlit. If you work with data a lot, you’re probably familiar with this. You open a new CSV file and always …
ATOKEN: A Unified Tokenizer for Vision Finally Solves AI’s Biggest Problem
Author(s): MKWriteshere Originally published on Towards AI. How Apple eliminated the need for separate visual AI systems with one tokenizer that handles all content types While competitors grabbed headlines with flashy AI demos, Apple’s researchers were quietly solving visual AI’s most fundamental …
From Experiment to Essential: Why AIBlog — an AI That Researches AI — Has Become My Daily Compass
Author(s): Abozar Alizadeh Originally published on Towards AI. I built AIBlog as part of the SandBox research playground to test how far autonomous agents can go when asked to do the entire workflow of a researcher: discover a topic, read the literature …
Mastering RAG: Precision from Table-Heavy PDFs
Author(s): Vicky’s Notes Originally published on Towards AI. I just wrapped a customer pilot where “documents” really meant PDFs stuffed with tables, footnotes, and odd layouts. The goal sounded simple: answer two kinds of questions reliably. For semantic questions like “What changed …
Integrating CI/CD Pipelines to Machine Learning Applications
Author(s): Kuriko Iwai Originally published on Towards AI. A step-by-step guide on automating the infrastructure pipeline on AWS Lambda architecture A CI/CD pipeline is a set of automated processes that helps machine learning teams deliver models more reliably and efficiently. Photo by …
How to Model APIs with Ontologies and Graphs for AI Agents
Author(s): Souradip Pal Originally published on Towards AI. Ever tried assembling IKEA furniture without the manual? You’ve got planks, screws, and hinges scattered across the floor. You know they fit together somehow… but without the guide, you’re lost. Image captionThis article discusses …
Building an AI Debate Panel: Agents that Argue and Give a Final Conclusion
Author(s): Michalzarnecki Originally published on Towards AI. Building an AI Debate Panel: Agents that Argue and Give a Final Conclusion A single LLM prompt or a plain ReAct (reasoning & take actions) agent often gives you a plausible answer – sometimes great, …
From A/B Testing to DoubleML: A Data Scientist’s Guide to Causal Inference:
Author(s): Rohit Yadav Originally published on Towards AI. Image by Author This article is a comprehensive guide to the most common causal inference techniques, complete with practical examples and code. While the scenarios are inspired by real-world use cases I have worked …
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