Video AI in the Enterprise
Author(s): Onil Gunawardana Originally published on Towards AI. Video AI can generate photorealistic clips in minutes, but that’s not the problem enterprises need solved. Sora, Runway, and Veo create stunning demos from text prompts. But you’re asking the harder question: what problems …
Data Quality and Filtering at Scale for Training Large Language Models
Author(s): M Originally published on Towards AI. From heuristic filters to AI classifiers: practical techniques for curating trillion-token datasets Training a language model on the raw internet is like trying to learn from every conversation happening in the world simultaneously. Most of …
🧠 How Large Language Models Learn to Reason: The Ultimate 2025 Guide with Real-World Examples and Code
Author(s): MahendraMedapati Originally published on Towards AI. Master the Art of AI Reasoning — From Theory to Implementation Have you ever wondered how ChatGPT solves complex math problems or how Claude breaks down intricate coding challenges? 🤔 Image illustrating the reasoning capabilities …
Sourcing and Collecting Data for Training Large Language Models
Author(s): M Originally published on Towards AI. Real-world insights from FineWeb, DCLM, The Stack v2, and modern LLM training When people talk about training language models, the conversation often jumps straight to architecture choices or training techniques. But here’s the reality: you …
“Everyone’s Betting on AI Tools — But They’re Solving the Wrong Problem”
Author(s): Mohamed Ashraf Originally published on Towards AI. The creator economy is now one giant bet on AI tools. Open Twitter. Check Product Hunt. Scan your LinkedIn feed. Every day, there’s a new “game-changing” AI writing assistant promising to 10x your output, …
🚀 Mastering Agentic Design Patterns with LangGraph: A Complete Guide to Building Intelligent AI Systems
Author(s): MahendraMedapati Originally published on Towards AI. Building production-ready AI agents that actually work — not just impressive demos Here’s something I’ve learned after building AI systems for the past few years: the way you structure your workflows determines everything. You can …
Kalman Filters Demystified — The Algorithm Behind Moon Landings
Author(s): Maxwell’s Demon Originally published on Towards AI. Kalman Filters Demystified — The Algorithm Behind Moon Landings Named after Rudolph Kalman, the Kalman filter is one of the most powerful algorithms in signal processing, control engineering, and machine learning. It remains widely …
Stop Using Claude Wrong: Why Skills Are the Solution to Your AI Reliability Problem
Author(s): Mayank Bohra Originally published on Towards AI. Everyone’s frustrated with AI giving different answers every time. Here’s the deterministic framework that actually solves consistency, from someone who’s spent weeks testing production AI systems. You know that feeling when Claude gives you …
The End of Prompt Engineering? Stanford’s Self-Improving AI Learned Clinical Reasoning on Its Own
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Stanford’s Agentic Context Engineering lets models reflect, learn, and build their own playbook. I tested it on clinical lab data — and watched it teach itself temporal reasoning. As we saw in my …
AI-Powered Glasses For Delivery Drivers
Author(s): Anil Kumar Bakkashetti Originally published on Towards AI. Technology makes every step smarter and safer When I first joined Amazon’s warehouse three years ago, I imagined fast-paced conveyor belts, endless rows of packages, and the hum of automated scanners — but …
AI Bots Recreated Social Media’s Toxicity
Author(s): Michael Ludwig Originally published on Towards AI. I was driving home last Tuesday, half-listening to a tech podcast, when something made me pull over. The host was describing an experiment where researchers created a social network populated entirely by AI bots. …
Diffuse and Disperse: Image Generation with Representation Regularization (Paper Review)
Author(s): Hira Ahmad Originally published on Towards AI. Diffuse and Disperse: Image Generation with Representation Regularization (Paper Review) Diffusion models have redefined the frontiers of generative AI, capable of transforming noise into highly structured, realistic images. But as these models grow, a …
The Next Frontier in NLP: Smarter Agents, Not Just Bigger Models
Author(s): CapeStart Originally published on Towards AI. Imagine a world where AI not only mimics human summaries but also exceeds them in quality. For years, Natural Language Processing (NLP) has relied on Supervised Fine-Tuning (SFT) to train language models to replicate human-written …
The Newsletter Template Prompt That Changed My Email Marketing Game
Author(s): Hui Zhu Originally published on Towards AI. I Used to Dread Sunday Nights Sunday evening used to be my least favorite time of the week. Not because the weekend was ending — I love my work — but because I knew …
Crushing ML Latency: The (Un)Official Best Practices for Systems Optimisation
Author(s): Natalia Sikora Originally published on Towards AI. TLDR: This guide offers a concise, accessible, intermediate-level overview addressing training latency issues for ML researchers / programmers. It covers best practices for systems optimisation, while emphasising (especially for newcomers) the crucial details that …
Popular posts
Updates
Recent Posts
