Do AI Agents Really Use the Tools You Build for Them? I Tested It.
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Testing tool coverage in local agents and how to improve compliance. I thought my healthcare AI agent would call my lab-checking tool every time it encountered lab values. Instead? Only 1 out of …
Understanding Neural Networks — and Building One!
Author(s): Aditya Gupta Originally published on Towards AI. Why Do We Need Neural Networks? Imagine trying to teach a computer to do something humans find easy like recognizing a face in a photo, understanding someone’s accent, or predicting which movie you’ll enjoy …
LLMs Don’t Just Need to Be Smart — They Need to Be Specific. Here’s How.
Author(s): Kaushik Rajan Originally published on Towards AI. How a new technique called “Test-Time Deliberation” teaches AI to think before it speaks I spend a lot of my time wrestling with Large Language Models (LLMs). The goal is always the same: how …
Beyond pre-trained LLMs: Augmenting LLMs through vector databases to create a chatbot on organizational data
Author(s): Leapfrog Technology Originally published on Towards AI. In the ever-evolving realm of AI-driven applications, the power of Large Language Models (LLMs) like OpenAI’s GPT and Meta’s Llama2 cannot be overstated. In our previous article, we introduced you to the fascinating world …
Harnessing the power of LLMs and LangChain for structured data extraction from unstructured data
Author(s): Leapfrog Technology Originally published on Towards AI. In today’s ever-evolving tech landscape, the rise of Large Language Models (LLMs) has brought about a transformative shift in how we engage with digital applications and content. These advanced language models, exemplified by renowned …
How I Built a GPT App in Under 4 Hours and Saved $7,500 in MVP Costs
Author(s): Supreeth Kashyap Originally published on Towards AI. From $7,500 and 3 Months to Just 4 Hours: My AI-Powered App Journey When I built my first app a few years ago, it cost me around $7,500 and three months of development time …
TAI #171: How is AI Actually Being Used? Frontier Ambitions Meet Real-World Adoption Data
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, AI models continued to push the frontiers of capability, with both OpenAI and DeepMind achieving gold-medal-level results at the 2025 ICPC World …
In-Context Learning Explained: Why LLMs Need 100 Examples, Not 5
Author(s): MKWriteshere Originally published on Towards AI. New research reveals the truth about few-shot learning and what it means for your AI applications What happens when you feed ChatGPT examples in your prompts isn’t what you think Image Generated by Author Using …
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 …
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 …
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 …
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 …
RAG-Fusion Multimodal: The Theory Behind Local Document Intelligence
Author(s): Elangoraj Thiruppandiaraj Originally published on Towards AI. Retrieval-Augmented Generation (RAG) has an enormous potential for building AI applications that go beyond static prompts or pre-trained datasets. Instead of depending only on what a model has memorised, RAG lets you add context …
Understanding Gradient Descent: How Machines Learn Step by Step
Author(s): Aditya Gupta Originally published on Towards AI. Gradient Descent Explained the Easiest Way, A Beginner’s Guide You’ll Actually Remember Have you ever played Angry Birds? What is the first thing you do when you start the game? If you are a …
Researchers put AI in a Room with Regulators and a Game of Trust. It Didn’t Go Well.
Author(s): Kaushik Rajan Originally published on Towards AI. A new study uses game theory to simulate how AI agents, developers, and users interact. I’ve spent countless hours thinking about AI safety. It’s the kind of topic that keeps you up at night. …
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