Yoh!
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
They won ka code and they're going to win on everything else.
When DeepMind was founded, their mission was very simple - solve AGI and use it to solve everything else.
This was super prophetic. There's no human who can beat a robot ka Chess or Go, etc.
Wang is cooking. 🔥
Today we’re releasing Muse Spark Open, the most capable US open-weight model to date.
Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.
Key Model Specs:
→ 816B total / 42B active parameters
→ 1M token context window
→ Natively multimodal across text, image, video, audio
DeepMind really released a good model here. 🤌🏾
🎯 Gemini 4 Argon has a 15% hallucination rate on AA-Omniscience, compared with 51% for GPT-6 Astra.
📊 It ranks first on the Vals Index, reflecting its high performance in legal and other knowledge work.
🔐 For now, only cybersecurity defenders in Google's Fairwind program can use it.
Full story in our weekly AI newsletter, The Batch 📬 hubs.la/Q04zX8YW0
#DeepLearningAI #AIEngineering #Cybersecurity
Git is not evolving fast enough. This is very bad for them.
New on our Engineering blog: Creating in-house source control.
In May, we merged around 2,500 code changes per day. In September, we merged more than 30,000 per day. As a result, we became bottlenecked by developer infrastructure built for human (rather than agent) scale.
Here, we share how we built a new version control system—and fully migrated our monorepo from git—in five months: anthropic.com/engineering/re…
Train your decision model. Deploy as an API. Give it to your LLM as a tool. Big deal! 🔥
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: github.com/unslothai/unsloth
Guide and Notebooks: unsloth.ai/docs/basics/train…
Haibo?! 🙆🏾♂️
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
This is spooky! 🤯 Why do we need this?
Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
It’s the first Human Interaction Model (HIM).
Readers added context they thought people might want to know
The 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-gri…
research.nvidia.com/labs/amri/proj…
tech-ish.com/2026/10/02/tav…
At a WITS conference this year, I asked a full symposium who knows what huggingface is, only 10% raised their hands. Kaggle, Zindi. These students just want to pass. No curiosity outside the classroom whatsoever. What do you mean you never used git? Docker? Aowa! 🚮
It's a skill issue. Most graduates are not employable. I spoke about The “Classroom Student” vs “Out of Classroom Student” Theory of Learning at the Africa Data Science conference earlier this year. Good grades are not enough. I interview many of these grads and it's really bad.


























