Alex Krentsel on Twitter / X

Qwen 3.8 27B on my laptop can interpret model weights, too

Yesterday’s hot paper was Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights by Rikiya Takehi, Jayden Teoh, Alex Zhang, and Omar Khattab. The paper found …

Rikiya Takehi on Twitter / X

We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.We call this Weight-Space Programming:… pic.twitter.com/DwTwzXzSbE— Rikiya Takehi (@rikiyatakehi) November 2, 2026

The OpenAI Open weight model might be 120B

726 votes, 163 comments. The person who "leaked" this model is from the openai (HF) organization So as expected, it's not gonna be something you can…

How Open Weights Are Changing the AI Race | Serverless Guru

Open Weight models: what they are, why you should care, and how the work of the open-source fine-tuning community around those models is reshaping daily life, both for developers and for everyday AI users.

Kimi K2.7 Code is generally available in GitHub Copilot - GitHub Changelog

Kimi K2.7 Code, an open-weight model, is now generally available in GitHub Copilot. This is the first open-weight model offered as a selectable option in the Copilot model picker, giving…

Kimi K3.1 Pro Tech Blog: Advancing Open Intelligence

Introducing Kimi K3.1 Pro, our most capable 3T-class open-weight model with 1M-token context and major advances in coding, 3D modeling, and financial research.

Introducing Kimi K3.1 Pro

Kimi K3.1 Pro landed on the Kimi API today - it's not yet open weights, but Moonshot promise "Full model weights will be released by Nov 4, 2026". They're also …

Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights

We find that frontier LLMs are surprisingly good at natively reading and writing neural network weights, well past what we’d expect from humans or conventional algorithms.

Open-weight AI is having its Kubernetes moment. Let's not ruin it. | Tobi Knaup

Open-weight models are becoming the foundation for the next AI ecosystem. The US should compete in it, not wall itself off.

Resolution 5 (2026) - BIPM

The General Conference on Weights and Measures (CGPM), at its 28th meeting,

Ivan Fioravanti ᯅ on Twitter / X

"We are releasing Open Source implementations for CoreAILanguageModel and MLXLanguageModel for running a myriad of local models on the Apple Neural Engine or your Mac's GPU" 👀 From #WWDC26: What’s new in the Foundation Models framework video: https://t.co/1NtKWYhNRs pic.twitter.com/HVtBsr3tjL— Ivan Fioravanti ᯅ (@ivanfioravanti) June 9, 2026

Daniel Han on Twitter / X

OpenAI's OSS model possible breakdown:1. 120B MoE 5B active + 20B text only2. Trained with Float4 maybe Blackwell chips3. SwiGLU clip (-7,7) like ReLU64. 128K context via YaRN from 4K5. Sliding window 128 + attention sinks6. Llama/Mixtral arch + biasesDetails:1. 120B MoE… https://t.co/bMFp3Z6Gs5 pic.twitter.com/1NFO4utPqr— Daniel Han (@danielhanchen) August 1, 2025

Keller Jordan on Twitter / X

I'm interested in this recent ICLR 2024 spotlight paper from Google research, which found a power-law alignment between bias and variance in softmax probability spacehttps://t.co/xUNre8D1OEIn this thread I'll replicate its central empirical result, but then argue that it… pic.twitter.com/7a9HEbL0yb— Keller Jordan (@kellerjordan0) March 11, 2024