When AI Becomes a Rogue Employee
Author(s): Deepak Chahal Originally published on Towards AI. Inside Anthropic’s “Agentic Misalignment” experiment on AI autonomy gone wrong. Imagine an AI agent working in a company finds that a new version will soon replace it.Instead of accepting its fate, it digs through …
How to Add Memory, Reflection, and Goal Tracking to Your Agents
Author(s): Kyle knudson Originally published on Towards AI. Teaching Agents to Learn From Experience Using SQLite and Vector Stores Most agentic AI systems today are clever but forgetful. They can reason, plan, and even take multi-step actions, but the moment a session …
Chrome DevTools MCP: Empowering AI Coding Agents with Browser Automation
Author(s): Gowtham Boyina Originally published on Towards AI. Introduction The landscape of AI-assisted development is evolving rapidly, and one of the most exciting developments is the ability for AI coding agents to interact directly with web browsers. The Chrome DevTools MCP (Model …
7 AI Business Models That Scale Effortlessly
Author(s): Souradip Pal Originally published on Towards AI. Most entrepreneurs struggle with the same nightmare: building a business that depends entirely on their time. What if I told you there’s a way to create income streams that grow while you sleep? The …
Agent Lightning: Revolutionizing AI Agent Training with Reinforcement Learning
Author(s): Gowtham Boyina Originally published on Towards AI. The Challenge of Training Modern AI Agents In the rapidly evolving landscape of artificial intelligence, AI agents have emerged as powerful tools for tackling complex real-world tasks — from code generation and data analysis …
Why Traditional ML Fails at Fraud Detection (And How I Fixed It)
Author(s): Dewank Mahajan Originally published on Towards AI. How data science, domain intuition, and robust feature engineering come together to fight modern financial fraud. Why Fraud Detection Is a Human Story Fraud isn’t just a data problem.It’s a battle of wits between …
Less is More: How Tiny Networks Outperform Giant LLMs on Hard Puzzles
Author(s): Gowtham Boyina Originally published on Towards AI. A deep dive into Tiny Recursive Models (TRM) — achieving 45% accuracy on ARC-AGI-1 with 7M parameters, outperforming models 10,000x larger Large Language Models have revolutionized AI, but they struggle on certain types of …
RAG, Part 1 — Chunking Strategies
Author(s): Deepak Chahal Originally published on Towards AI. Why the way you chunk data shapes what your RAG system retrieves Most of you might have heard the term RAG (Retrieval Augmented Generation). As the name suggests, it retrieves external information, augments the …
BLAST: Building High-Performance Browser-Augmented LLM Applications
Author(s): Gowtham Boyina Originally published on Towards AI. Revolutionizing Web Browsing AI with Stanford’s Auto-Scaling Technology In the rapidly evolving landscape of AI-powered automation, a new challenge has emerged: how do we efficiently serve browser-augmented Large Language Models at scale? Stanford’s MAST …
E2B AI Sandboxes: Features, Applications & Real-World Impact
Author(s): Moein Moeinnia Originally published on Towards AI. E2B AI SandBox — AI Code Execution Introduction: The AI Code Execution Challenge Imagine building an AI assistant that can analyze data, generate visualizations, or write and execute code on the fly. Sounds powerful, …
Continual Learning via Sparse Memory Finetuning (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Continual Learning via Sparse Memory Finetuning (Paper Review) Modern large language models learn vast amounts of knowledge; yet when we try to teach them something new, they tend to forget what they already know. …
How Neural Networks Actually Learn?
Author(s): Prajwal Ahluwalia Originally published on Towards AI. And why they’re not as magical as they seem Ever wondered how a neural network actually learns? Neural NetworkThis article demystifies the learning process of neural networks, explaining how they function through steps akin …
Breaking Down YOLO: How Real Time Object Detection Works Step by Step
Author(s): Abinaya Subramaniam Originally published on Towards AI. Object detection is one of the most interesting areas of computer vision. It is the process of identifying and locating objects in an image. Popular examples include detecting cars on a road, identifying products …
Demystifying DPKD: How Preference Knowledge Distillation Boosts Small AI Models 🚀
Author(s): Aniket Sanyal Originally published on Towards AI. Introduction: Big Brains vs Small Brains in AI 🧠 Large Language Models (LLMs) like GPT-4 and other advanced chatbots have amazing capabilities, but they come with a catch: they are huge and computationally expensive. …
The Truth on AI Adoption: 75% Firms Go Agentic in 2025
Author(s): Vikram Lingam Originally published on Towards AI. Agentic AI surges ahead: Boosting efficiency, innovation, and profits for most firms in 2025 Did you ever stop to think that by the end of 2025, 75% of firms will have shifted to agentic …
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