This Tiny 1-Bit Model Could Change AI Forever

Video Description

BitNet is Microsoft’s groundbreaking 1-bit large language model — and it’s surprisingly powerful. In this video, we explore how it works, why quantizing weights to just 1.58 bits is such a big deal, and what it means for running AI on everyday hardware. We also put BitNet to the test on an M2 MacBook Pro to see how well it performs in real-world use. 🔗 Relevant Links BitNet: https://github.com/microsoft/BitNet BitNet Demo Page: https://bitnet-demo.azurewebsites.net/ LLM Logic Tests: https://docs.google.com/spreadsheets/d/1NgHDxbVWJFolq8bLvLkuPWKC7i_R6I6W/edit?gid=2011456595#gid=2011456595 BitNet Hugging Face Page: microsoft/bitnet-b1.58-2B-4T ❤️ More about us Radically better observability stack: https://betterstack.com/ Written tutorials: https://betterstack.com/community/ Example projects: https://github.com/BetterStackHQ 📱 Socials Twitter: https://twitter.com/betterstackhq Instagram: https://www.instagram.com/betterstackhq/ TikTok: https://www.tiktok.com/@betterstack LinkedIn: https://www.linkedin.com/company/betterstack 📌 Chapters: 00:00 Intro: Can You Really Run AI on a Laptop? 00:39 What is BitNet? 00:49 How 1-Bit / Ternary Quantization Works 01:26 Why 1-Bit Models Matter (Size, Speed, Efficiency) 02:20 Training Natively in 1-Bit Space 02:40 How to Run BitNet (Easiest Setup via Hugging Face) 03:45 Logic Tests 04:56 Coding Test 05:42 Limitations and Where BitNet Struggles 06:15 What BitNet Means for Edge AI and the Future