Meet NVIDIA Nemotron 3.5 Super VL
Our new open model combines reasoning and tool use with text, image, document, and video understanding for long-running AI agents.
120B total parameters with 12B active 🧵
In our previous work, we also used OPSD in a similar way. Instead of using it for token-level supervision, we used hindsight-induced log-prob changes to identify critical points in a trajectory, then further sampled new continuations from those points for training while reusing the prefix. https://t.co/SYSab7iYZR
Frontier labs are rumored to be adopting looped Transformers for their potential to unlock implicit reasoning. But can looped Transformers really master it?
We find a bottleneck that keeps looped Transformers from perfect implicit reasoning. Using mechanistic interpretability, we show how looping helps implicit reasoning, why it still struggles to generalize, and how to fix it.
We introduce DiscoLoop: a residual design for looped Transformers that improves implicit reasoning.
🧵 Long thread ahead 👇
I’ll be at @COLM_conf this week (Oct 5–10), presenting work from my internship at ByteDance Seed:
“Towards Full Pipeline FP8 Reinforcement Learning for LLMs”
https://t.co/G0QdInCuqO
Happy to chat about RL infra, agentic RL, and continual learning. Come say hi if you’re around :)
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
The world needs both frontier closed models and frontier open models.
https://t.co/AUKzoQ5Ikb
i loved my time at openai. it was transformative for me personally, and hopefully the world a little bit. most of all i loved working with such talented people.
will have more to say about what’s next later.
🫡
@joe_hellerstein@AzzaAbouzied Greatest intro level DB course in the world👍 BTW, does Berkeley plan to offer some new advanced DB courses like CMU's 15-721 ?