LLMs Are Dying – The New AI Is Killing Them
Author(s): Jose Crespo, PhD Originally published on Towards AI. Though Still Haunted by AI’s Fatal Obsession with Euclidean Flatland Yes, ChatGPT, Claude, Gemini, all of them. Brilliant fossils of a linguistic age that’s already ending. They’re decomposing in public, billions are still …
Getting Started with Generative AI Models: Concepts and Building Blocks
Author(s): Gulshan Yadav Originally published on Towards AI. Getting Started with Generative AI Models: Concepts and Building Blocks Master Generative AI from foundations to implementation. Learn GANs, VAEs, transformers, and diffusion models with hands-on examples. Build your first text generator, image creator, …
You’re Not an AI Engineer. You’re Just Using ChatGPT.
Author(s): Rohan Mistry Originally published on Towards AI. What actually separates AI engineers from AI users I see it everywhere on LinkedIn: Source: Image by author.The article discusses the misconception surrounding those who utilize AI tools like ChatGPT versus those who are …
Jules + Gemini CLI: The AI Combo That Actually 10x’s Your Productivity
Author(s): Rohan Mistry Originally published on Towards AI. Stop context switching — let Jules handle the boring work while you code You’re debugging a neural network. Training loss is spiking. You’re in the zone. Source: Image by author.The article discusses the challenges …
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 …
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 …
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 …
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. …
Beyond Scarcity: How LLM-Driven Synthetic Data Generation is Reshaping AI
Author(s): Burak Degirmencioglu Originally published on Towards AI. In the world of artificial intelligence, data is the new oil. But what happens when that oil is scarce, locked behind privacy walls, or simply too expensive to acquire? This post explores a revolutionary …
Transformers Architecture: How Google’s ‘Attention Is All You Need’ Changed Deep Learning Forever
Author(s): TechWiz Originally published on Towards AI. When Machines Learned to Pay Attention In the last decade, artificial intelligence has undergone a remarkable transformation.But in 2017, something extraordinary happened, a single paper from Google Brain, titled “Attention Is All You Need,” quietly …
This New Embedding Model Cuts Vector DB Costs by ~200x!
Author(s): Avi Chawla Originally published on Towards AI. It also outperforms OpenAI and Cohere models. RAG is 80% retrieval and 20% generation. Contextualized chunk embedding (Image by Author)This article discusses the challenges and solutions related to Retrieval-Augmented Generation (RAG) setups, particularly focusing …
8 AI Research Papers Every Entrepreneur Should Read
Author(s): Souradip Pal Originally published on Towards AI. A founder-friendly breakdown of the most important AI research papers shaping product innovation, business strategy, and startup growth. Most founders talk about AI like it’s a distant storm.Loud. Exciting. Unpredictable. Image CaptionThe article explores …
How to Design Efficient Memory Architectures for Agentic AI Systems
Author(s): Suchitra Malimbada Originally published on Towards AI. A practical guide to building agentic AI systems that manage memory efficiently using hierarchical memory architectures, knowledge graphs, and forgetting machanisms, covering everything needed to know before designing memory architecture. A gif showing how …
Popular posts
Updates
Recent Posts