The 4 RAG Architectures: How to Give AI Perfect Memory Without Retraining
Author(s): TANVEER MUSTAFA Originally published on Towards AI. Understanding Naive RAG, Advanced RAG, Modular RAG, and Agentic RAG Your LLM is brilliant but frustratingly limited. Image generated by Author using AIThis article delves into the concept of Retrieval Augmented Generation (RAG), discussing …
We Replaced 47 Excel Files With One Power BI Model. Here’s What Actually Happened.
Author(s): Gulab Chand Tejwani Originally published on Towards AI. 15 hours every Monday copying data. Daily errors. Zero trust in the numbers. Here’s what actually happened when we migrated from Excel chaos to Power BI. Monday, 6:23 AM. My phone buzzed. We …
9 Agentic AI Projects I’d Build in 2026 to Learn What Agents Really Are
Author(s): Khushbu Shah Originally published on Towards AI. Most “ AI agent demos” online are just chatbots with a loop. I’ve seen enough agent demos that look impressive and teach nothing. These AI agent projects are different. Each one forces you to …
The 5 Normalization Techniques: Why Standardizing Activations Transforms Deep Learning
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 5 Normalization Techniques: Why Standardizing Activations Transforms Deep Learning Training deep neural networks is difficult. Add more layers, and training becomes unstable — gradients explode or vanish, learning slows, or the model fails …
How We Built a 99% Accurate Invoice Processing System Using OCR and LLMs
Author(s): Vaibhav Rathi Originally published on Towards AI. We had a working RAG solution at 91% accuracy. Here’s why we rebuilt it with fine-tuning and what we learned along the way. Our client was spending eight minutes per invoice on manual data …
When Optimization Works: The Role of Convexity in Business Decisions
Author(s): Saif Ali Kheraj Originally published on Towards AI. Every business decision operates under constraints, budgets, capacity, regulations, and trade-offs. The structure of those constraints determines whether a decision has a single clear optimal choice or several competing alternatives. Convex problems lead …
Mastering Unstructured data: The Blueprint For Efficient Solution
Author(s): Pankaj Agrawal Originally published on Towards AI. In the rapidly evolving landscape of Artificial Intelligence, the spotlight has shifted from neatly organized tables to the vast, messy, and context-rich world of unstructured data., Comprising the vast majority of enterprise information, formats …
Bonferroni vs. Benjamini-Hochberg: Choosing Your P-Value Correction | Towards Data Science
Author(s): Marco Hening Tallarico Originally published on Towards AI. Bonferroni vs. Benjamini-Hochberg: Choosing Your P-Value Correction | Towards Data Science P-values can be a sensitive topic. Perhaps best avoided on first encounter with a Statistician. The disposition toward the topic has led …
The 4 Flash Attention Variants: How to Train Transformers 10× Longer Without Running Out of Memory
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 4 Flash Attention Variants: How to Train Transformers 10× Longer Without Running Out of Memory You’re training a Transformer. Image generated by Author using AIThis article discusses four Flash Attention variants that enhance …
The 4 Positional Encoding Methods: Why Word Order Is Everything in AI
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 4 Positional Encoding Methods: Why Word Order Is Everything in AI Understanding how Transformers learn sequences without sequential processing Image generated by Author using AIThis article delves into four distinctive methods of positional …
The 4 Gradient Clipping Methods: How to Prevent Training from Exploding
Author(s): TANVEER MUSTAFA Originally published on Towards AI. The 4 Gradient Clipping Methods: How to Prevent Training from Exploding You’re training a deep neural network. Image generated by Author using AIThis article explores the critical issue of exploding gradients in deep learning, …
OpenAI’s GPT-5.3-Codex: The AI That Learned to Code Itself
Author(s): Mandar Karhade, MD. PhD. Originally published on Towards AI. OpenAI finally stops pushing porn and starts building coworkers OpenAI just dropped something that should make every software engineer pause their current Sprint planning. GPT-5.3-Codex isn’t just another incremental update to AI-assisted …
Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)
Author(s): Sivasai Yadav Mudugandla Originally published on Towards AI. Image generated with Microsoft Copilot · 1. Introduction: Why Computers Struggle with Language· 2. What Are Word Embeddings and Why Do We Need Them? ∘ The Map Analogy ∘ Why We Need Them …
Agents 2.0: AI Agents that Can Learn (6 Learning Types that Make Memory Persistent)
Author(s): Divy Yadav Originally published on Towards AI. What if your AI actually remembered you? We call them AI agents. Personal assistants. Digital helpers. Photo by geminiThis article discusses the limitations of current AI agents, which typically do not learn from past …
I tuned a 7B Model That Outperforms GPT-4 (Here’s How You Can Too)
Author(s): Gaurav Shrivastav Originally published on Towards AI. A practical guide to understanding and implementing model specialization for real-world applications Last month, I helped a startup replace their GPT-4-powered customer service system with a fine-tuned 7B parameter model. The results were surprising: …
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