You can now train your own Decision model like Jev locally!
We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM.
Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo.
We fine-tuned with a Clef head using Unsloth and LoRA (r=64) for one epoch, increasing downstream accuracy from 30–37% to 78%.
GitHub: https://t.co/2kXqhhvLsb
Guide and Notebooks: https://t.co/qACsYehl1n
Today marks a new chapter for Windows, as we bring unmetered intelligence to every desk and every home, and make every PC a place where agents can work securely on your behalf.
Some highlights of what we announced:
• MAI-Code-1.1 Flash: 137B parameter coding model w/ 256K context window, which is now optimized to run on your PC!
• GitHub Copilot now hands off work to local models like MAI-Code-1.1 Flash, helping projects cost a lot less without sacrificing quality.
• With Hybrid Intelligence, Copilot can now take action directly on the PC and keep sensitive work on your device.
• And with Code in Copilot, you can essentially build any software you need on your desktop, without any cloud token spend, and it’s just super at it. You’re no longer limited to what’s in an app store! Your PC becomes an infinite software factory.
• Security is foundational to all this, which is why we are also bringing together Windows and Agent 365 so agents can work within secure boundaries on-device, including MXC a local sandbox for agent execution. Windows becomes your secure agent box!
• All this comes to life on a new generation of devices, like Surface Laptop Ultra, powered by NVIDIA RTX Spark.
Can’t wait to see what you build with all this.
Google releases EmbeddingGemma 2, a new open model that runs locally on 0.5GB RAM.
The 740M parameter Apache 2.0 model combines a 270M text model with vision (170M) + audio (300M).
Run & train the model via Unsloth.
GGUF: https://t.co/yVUJs3MNG9
Guide: https://t.co/jw67IZPTek
BREAKING 🔥: Mistral announced Mistral Large 4 "Le Chonk", a new 1T-parameter open-weight model!
> 49B active parameters, native multimodality.
> Rolling out via APIs today; open-weight release is planned for the end of October.
> SOTA on "critical workloads", including cyber defense.
Le Chaton Fat "Le Chonk" is here 👀
Obsidian 1.14 is now available with five major improvements:
1. Edit Markdown files outside your vault
2. Preview files using macOS Quick Look when the app is closed
3. Instantly add notes with Quick Capture on iOS
4. Kanban and new grouping options in Bases
5. Highlight colors
please bro, don't listen to the fake news. We won the war in Iran 37 times. It's 69D chess, bro. I will give you $5k if you vote republican in the midterms and gas will be $2. Please bro
"Learning Mathematics: Why Memory, Practice, and Technique Matter More than Talent"
To learn mathematics it is essential to memorise a great quantity of information, rules, simplifications and problem-solving tricks. There is no other way. Theory has its use, but in the right dose.
It is like learning a language.
If you concentrate too much on the grammar, you will never speak it fluently.
https://t.co/IJjp3SlePq
We stole reasoning. Again.
An update to our paper on reasoning extraction: Patching your own API doesn’t secure your cloud-hosting ecosystem.
Story in the 🧵
We can finally talk about it:
We found a way to extract hidden reasoning of frontier models using a vulnerability in the APIs of every frontier AI company.
We verified that our reasoning token count matches billed API thinking tokens 1:1 for most of the prompts we queried.