Designing Agent Conversations: From FIPA to Today’s Protocols
Author(s): Souradip Pal Originally published on Towards AI. How decades-old dreams of digital dialogue shaped the way modern AI agents talk today. Did you know that back in the late ’90s, researchers were already dreaming about digital agents talking to each other …
Stop Learning Like a Human. Start Learning Like AI Does.
Author(s): Rohan Mistry Originally published on Towards AI. I Mastered ML in 3 Weeks After Failing for 6 Months. I’m learning AI and Machine Learning. Human Vs AI LearningThis article recounts the author’s transformative journey from struggling with human-style learning in AI …
Is OpenAI’s AgentKit the New Automation KING— or Just AI Hype?
Author(s): AIversity Originally published on Towards AI. Does it truly surpass n8n and Zapier, or is it just riding the AI hype? OpenAI’s latest AgentKit is making waves across the AI community — for all the right reasons. Sam altman OpenAI DevDay …
5 Reasons Mom Entrepreneurs Stall on Rebrands (How AI Made Mine Possible)
Author(s): Iryne Vanessa Somera Originally published on Towards AI. Why hesitation holds me back and how AI clears the path I am a mom and a business owner. My days are full, starting with client work, school prep, and meals. When I …
The Unseen Biases Lurking in Generative AI and How They Could Affect You
Author(s): Piyoosh Rai Originally published on Towards AI. Picture this: you ask an AI to create an image of a CEO. It gives you a clean-cut white man in a suit. Ask for a “businesswoman,” and you get a smiling, conventionally attractive …
AgentCrewOps — Part 1 — Agents for builders: goals, gotchas, and a practical starting stack
Author(s): Subramanian Mayakkaruppan Originally published on Towards AI. Series: Part 1 — Goals, gotchas, starting stack · Part 2 — Deploy the Lite stack TL;DR: Agents aren’t just APIs with bigger prompts. They’re stateful, stochastic programs that call tools, spend real money, …
Why and How We t-Test
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Girl with red hat on Unsplash Introduction When running experiments — be it with models, prompts, or human evaluations — we often need to answer one deceptively simple question: Did the change …
RLAD: How AI Learns to Think Strategically Before Solving Hard Problems
Author(s): MKWriteshere Originally published on Towards AI. A new training method teaches language models to generate reasoning strategies first, improving accuracy by 44% on complex math problems Large language models struggle with a specific problem: they optimize for generating longer solutions instead …
Building and Deploying a RAG Application: From PDF Processing to Production
Author(s): Ashutosh Malgaonkar Originally published on Towards AI. Overview I built a Retrieval-Augmented Generation (RAG) system that answers physics questions by retrieving relevant passages from an AP Physics textbook and generating responses using an LLM. The application processes 500 pages of Electricity …
Data Normalization in ML
Author(s): Amna Sabahat Originally published on Towards AI. In the realm of machine learning, data preprocessing is not just a preliminary step; it’s the foundation upon which successful models are built. Among all preprocessing techniques, normalization stands out as one of the …
How to Surgically Edit LLMs Without Retraining in Data Science
Author(s): The Bot Group Originally published on Towards AI. How to Surgically Edit LLMs Without Retraining in Data Science Your large language model is a marvel of engineering, trained on vast datasets at an enormous cost. It’s powerful, fluent, and… wrong. It …
The Model That Broke All the Rules in Data Science
Author(s): The Bot Group Originally published on Towards AI. The Model That Broke All the Rules in Data Science For years, the world of sequence modeling was dominated by a single, stubborn idea: to understand language, a model had to process it …
Your Model Has 95% Accuracy. It’s Completely Useless.
Author(s): Rohan Mistry Originally published on Towards AI. You Built a Model That Predicts Everything as “No.” It Has 95% Accuracy. You Just Shipped Garbage. Your boss: “How’s the fraud detection model?”You: “95% accuracy! Ready to deploy!”Your boss: “Great! Ship it.” Source: …
Data Leakage: Your 99% Accuracy Model is a Lie
Author(s): Rohan Mistry Originally published on Towards AI. Training Accuracy: 99%. Production Accuracy: 53%. Welcome to Data Leakage Hell. You spent 3 months building the perfect model. Source: Image by author.The article discusses the challenges of data leakage in machine learning, where …
Humans vs Machines: Who Wins Tomorrow?
Author(s): Arav Jain Originally published on Towards AI. Will AI really steal your job? “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human” — Alan Turing, father of theoretical computer science …
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