Building Self-Correcting RAG Systems
Author(s): Kushal Banda Originally published on Towards AI. Self-correcting RAG systems Standard RAG pipelines have a fatal flaw: they retrieve once and hope for the best. When the retrieved documents don’t match the user’s intent, the system generates confident nonsense. No feedback …
Fine-Tuning Large Language Models (LLMs) Without Catastrophic Forgetting
Author(s): Sachchida Nand Singh Originally published on Towards AI. Introduction Fine-tuning large language models (LLMs) is no longer optional — it is the standard way to adapt foundation models to domains such as healthcare, finance, legal text, customer support, or internal enterprise …
LLM & AI Agent Applications with LangChain and LangGraph — Part 28: Multi-Agent Discussion Panel (Researcher, Expert, Critic, Moderator)
Author(s): Michalzarnecki Originally published on Towards AI. Hi. In this part I’ll present a multi-agent application. It will be a discussion panel with four roles: Researcher — has access to a search tool and brings facts and sources into the conversation. Expert …
LLM & AI Agent Applications with LangChain and LangGraph — Part 27: The Publisher Agent (News → Summary → Article → Critic → Improve)
Author(s): Michalzarnecki Originally published on Towards AI. Hi. In this part I’ll run and demonstrate a publisher agent — a system that autonomously aggregates news from the web, summarizes the most important points, and then generates an article based on that material. …
LLM & AI Agent Applications with LangChain and LangGraph — Part 25: AI Agents architectures(and How to Organize Them)
Author(s): Michalzarnecki Originally published on Towards AI. Hi! In this article I’ll demonstrate different types of AI agents. This topic is useful because it helps you understand how many ways “intelligent agents” can behave and be organized — from simple reactive systems …
mHC: Rethinking the Neural Highway
Author(s): Revanth Madamala Originally published on Towards AI. If you’ve been following the evolution of Deep Learning, you know that for the last decade, we’ve been obsessed with Residual Connections (ResNets). They are the “highways” of a neural network — the bypass …
Setting Up TensorFlow with GPU (CUDA): A Step-by-Step Installation Guide
Author(s): Muaaz Originally published on Towards AI. If you are writing Deep Learning code on a machine with a GPU, TensorFlow will default to running on the CPU. This happens because TensorFlow does not automatically select the best hardware. To use the …
Why Intelligent Systems Fail Quietly
Author(s): Mind the Machine Originally published on Towards AI. Hallucination, confidence, and the hidden cost of punishment-driven optimization This article continues the line of inquiry started in Mind the Machine, which examined how modern discussions about AI often overlook deeper structural properties …
LLM & AI Agent Applications with LangChain and LangGraph — Part 26: RAG AI Agent in LangGraph
Author(s): Michalzarnecki Originally published on Towards AI. Hi. So far in this series we’ve built a basic graph, and then a graph with an LLM and a conditional loop. We also covered different types of AI agents. Now we’ll do a practical …
LoRA and QLoRA: Fine-Tune Billion-Parameter Models on Your Laptop
Author(s): Alok Choudhary Originally published on Towards AI. Stop Wasting GPU Memory: Learn how LoRA reduces 175B parameters to just millions. Master efficient LLM fine-tuning with practical insights on rank and quantization. Fine-tuning large language models has become an essential part of …
No One Is Talking About These 5 Software Development Fields AI Will Replace by 2026
Author(s): Asjad Abrar Originally published on Towards AI. No One Is Talking About These 5 Software Development Fields AI Will Replace by 2026 The artificial intelligence (AI) technology is still keeping on its fast-paced growth in the technological fields, and it is …
DecEx-RAG: A Paradigm Shift from Outcome to Process in Agentic RAG
Author(s): Florian June Originally published on Towards AI. Have you encountered Agentic RAG in your work or research? Today we will look at the progress of Agentic RAG. Figure 1: Illustration of the framework for DecEx-RAG, which demonstrates the process of search …
Why Everyone is Talking about Google Antigravity: The Era of Agentic AI Coding
Author(s): Swapnil Anil Damate Originally published on Towards AI. How I used Google’s new agent-first IDE to launch my MVP in a single weightless weekend. The weekend used to be where my ideas went to die. This time, it was where one …
From Perceptrons to Sigmoid Superstars: Building Smarter Neural Networks
Author(s): Hayanan Originally published on Towards AI. Unveiling the Magic of Gradient Descent, Feedforward Architectures, and Universal Function Approximation in AI Neural networks form the backbone of modern artificial intelligence, powering breakthroughs in computer vision, natural language processing, recommender systems, and scientific …
Building Reliable Machine Learning Systems for Heart Disease Prediction
Author(s): Puspita Chowdhury Originally published on Towards AI. Image Source: https://www.technologynetworks.com/diagnostics/news/wealth-and-education-play-significant-role-in-heart-disease-risk-396976 Heart disease continues to be the leading cause of death worldwide, responsible for millions of deaths every year. Despite advances in clinical diagnostics, early and accurate detection remains a persistent challenge. …
Recent Posts
