What an AI “Co-founder” Does When You’re Not Online
Author(s): R. Thompson (PhD) Originally published on Towards AI. Real workflows, guardrails, and the surprising errors you should plan for — a practical operating guide. You have a tiny team (maybe one person). The calendar is full. The to‑do list keeps spawning …
Detailed Guide to Quantisation Methods for LLMs
Author(s): Parth Chokhra Originally published on Towards AI. A Visual Step-by-Step Guide to Popular Quantisation Techniques Quantisation is the process of reducing the precision of numbers used in a model; for example, storing weights in 8-bit integers instead of 16- or 32-bit …
Your GenAI is 81.7% More Persuasive Than Your Best (Human) Friend
Author(s): Mohit Sewak, Ph.D. Originally published on Towards AI. A visual metaphor for an AI’s ability to subtly reshape human thought, reflecting the core finding that personalized AI is significantly more persuasive than human counterparts. I. That 81.7% Figure Should Stop You …
Reducing Hallucinations in VLMs using REVERSE
Author(s): Youssef Farag Originally published on Towards AI. Paper link: https://arxiv.org/abs/2504.13169 Code: https://github.com/tsunghan-wu/reverse_vlm Released: 17th of April 2025 Figure 1. REVERSE: a novel online verification and hallucination detection framework capable of automatically detecting hallucinations and proactively correcting itself. Image taken from [1] …
Master AI Agents 10x Faster by Fixing This One Neglected Skill: Memory
Author(s): Khushbu Shah Originally published on Towards AI. The Harsh Truth: Without Memory, Your AI Projects Will Never Scale Everyone loves talking about agentic AI frameworks, orchestration layers, and the latest LLM benchmarks. They make great demos, they look impressive on a …
Why Your AI Is a Fluent Liar
Author(s): Kaushik Rajan Originally published on Towards AI. A deep dive into the research that explains why AI hallucinations are an inherent feature of Large Language Models, not just a bug. You’ve probably seen it before. You ask an AI chatbot a …
The Dark Side of AI: When Innovation Meets Exploitation
Author(s): MD. SHARIF ALAM Originally published on Towards AI. Figure: Even as I write this piece about the ethical use of data and AI, the header image I used comes from the very kind of dataset practices I’m critiquing. This contradiction highlights …
5 ML Mistakes That Scream “Student” (And How to Fix Them) 🚀
Author(s): MahendraMedapati Originally published on Towards AI. From campus to career-ready: Transform your machine learning projects with these industry insights As a student diving deep into machine learning, you’ve probably built some cool projects, aced those assignments, and maybe even topped a …
Stop adding chatbots, use Agentic AI to Modernize Legacy CX Systems
Author(s): Manbir T Originally published on Towards AI. Stop adding chatbots, use Agentic AI to Modernize Legacy CX Systems If your support strategy over the last five years has boiled down to “spin up another chatbot,” you’re not alone — and you’re …
LAI #91: Reinforcement Learning, Knowledge Graphs, and Modular AI Agents
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week’s issue highlights how reinforcement learning and modular architectures are reshaping AI systems. We feature new research applying RL to sequential market basket decisions, showing how Q-learning …
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