Announcing Ambient Protein Diffusion, a state-of-the-art 17M-params generative model for protein structures.

Diversity improves by 91% and designability by 26% over the previous 200M SOTA model for long proteins.

The trick? Treat low pLDDT AlphaFold predictions as low-quality data.

Ambient Proteins: Training Diffusion Models on Low Quality Structures [new]
Trains diffusion models using low-confidence AlphaFold2 structures by adapting the diffusion objective based on corruption level.

New episode in this line of work from @giannisdaras.bsky.social et al. on training diffusion models with mostly bad/low-quality/corrupted data (+few high-quality samples). This time for proteins!

📄 Ambient diffusion Omni: arxiv.org/pdf/2506.10038
📄 Ambient Proteins: www.biorxiv.org/content/10.1...

We are releasing OpenThinker-32B, the best 32B reasoning model with open data. We match or outperform Deepseek-R1-32B (a closed data model) in reasoning benchmarks. Congrats to Negin and the whole Open Thoughts team.

github.com/open-thought...

o3 can't multiply beyond a few digits...

But I think multiplication, addition, maze solving and easy-to-hard generalization is actually solvable on standard transformers...

with recursive self-improvement

Below is the acc of a tiny model teaching itself how to add and multiply

Well deserved!

Did Gauss invent the Gaussian?

- Laplace wrote down the integral first in 1783
- Gauss then described it in 1809 in the context of least-sq. for astronomical measurements
- Pearson & Fisher framed it as ‘normal’ density only in 1910

* Best part is: Gauss gave Laplace credit!

“There is nothing quite so useless, as doing with great efficiency, something that should not be done at all.”

“To write well is to think clearly.”

Please reply to your ICLR rebuttals 🙏