Author(s): Mohit Sewak, Ph.D. Originally published on Towards AI. Our most powerful AIs can read a library of information, but they often forget what’s in the middle chapters. Let’s talk about the weirdest, most hilarious, and frankly, most important problem in AI …

Author(s): Intelligent Hustle Originally published on Towards AI. Source: Image by author The startup landscape has fundamentally shifted. What once required teams of dozens can now be accomplished by lean crews of five, armed with the right AI automation tools. This isn’t …

Author(s): Sai Kumar Yava Originally published on Towards AI. Human in the Loop : Building Reliable AI Picture this: Your company deploys an AI agent to handle customer support tickets. For weeks, it works beautifully — until one day it confidently tells …

Author(s): MahendraMedapati Originally published on Towards AI. The Research That Built Your AI Career (Whether You Know It or Not) If you’ve been riding the AI wave, you’ve probably heard terms like “transformers,” “RAG,” and “fine-tuning” thrown around like confetti at a …

Author(s): Utkarsh Mittal Originally published on Towards AI. In transformer models, knowing the order of tokens is essential — even though the model processes tokens in parallel. Traditional positional embeddings rely on a fixed “lookup table” (learned for positions up to a …

Author(s): Kapil Deshmukh Originally published on Towards AI. From embeddings to retrieval: mastering vector similarity search for next-gen enterprise AI applications. Photo by Ecliptic Graphic on Unsplash 🚀 Introduction If you’ve ever asked ChatGPT a question like “What animal likes milk?” and …