We are beyond thrilled to share our first flagship models, Rnj-1 base and instruct 8B parameter models. Rnj-1 is the culmination of 10 months of hard work by a phenomenal team, dedicated to advancing American SOTA OSS AI. Lots of wins with Rnj-1. 1. SWE bench performance close

🚀 Launching DeepSeek-V3.2 & DeepSeek-V3.2-Speciale — Reasoning-first models built for agents! 🔹 DeepSeek-V3.2: Official successor to V3.2-Exp. Now live on App, Web & API. 🔹 DeepSeek-V3.2-Speciale: Pushing the boundaries of reasoning capabilities. API-only for now. 📄 Tech

Q1. What is a number that a man may know it? -> Knowing of Nature; where we model nature abstractly and understand it. Q2. What is a man that he may know a number? -> Nature of Knowing; domain of ML, Deep Learning and AI are trying to unravel this with hardly any progress so far.

There's no better feeling than coming up with a simpler solution. And then an even simpler one. And then an EVEN SIMPLER one. I love it. It's also the hardest thing to do in programming, because over-complicating things is so so easy, I see it happen everywhere all the time.

Google may have had a breakthrough with Continual Learning AI models: "We introduce Nested Learning, a new approach to machine learning that views models as a set of smaller, nested optimization problems, each with its own internal workflow, in order to mitigate or even

Excited to release new repo: nanochat! (it's among the most unhinged I've written). Unlike my earlier similar repo nanoGPT which only covered pretraining, nanochat is a minimal, from scratch, full-stack training/inference pipeline of a simple ChatGPT clone in a single,