Machine-Learning

AI Hype vs. Reality: What’s Actually Behind the Buzzwords TL;DR A new tool called Extra-steps.dev is trying to cut through AI marketing noise by mapping hyped AI concepts directly to their underlying computer science primitives. The idea is simple but potentially powerful: instead of letting vendors dazzle you with buzzwords, you can trace every claim back to foundational CS concepts you already understand. It surfaced on Hacker News with modest but notable attention. If you’ve ever rolled your eyes at an AI pitch deck, this one’s for you. ...

MicroGPT: Finally, a GPT Model You Can Actually See Inside Your Browser TL;DR MicroGPT is an educational GPT implementation that lets you visualize how transformer models work directly in your browser. Posted on Hacker News in mid-February 2026, it’s gained significant attention (145+ upvotes) from developers wanting to understand what’s actually happening under the hood of models like GPT-5, Claude 4.6, and Gemini 2.5. Unlike production-scale models with billions of parameters, MicroGPT is deliberately tiny—making every layer, attention head, and token prediction visible and interactive. It’s not meant to compete with frontier models, but rather to demystify them. ...

The Post-Transformer Era: Are State Space Models Like Mamba Really the Future? TL;DR The machine learning community is buzzing about State Space Models (SSMs) and Mamba as potential successors to the dominant Transformer architecture. While the Reddit discussion generated significant engagement (82 upvotes, 28 comments), this research topic remains largely in academic and experimental phases. Mistral AI’s Codestral Mamba—an SSM-based code generation model—has already been deprecated since June 2025, raising questions about whether SSMs are truly ready to replace attention mechanisms or if they’re just another promising research direction that hasn’t quite delivered on its hype. ...