a lot of data research to be done across all sorts of tasks and modalities!

#CVPR2025 starts in two days, and can’t wait to share our new work! 🎉 We present ZeroGrasp, a unified framework for 3D reconstruction and grasp prediction that generalizes to unseen objects. Paper📄: arxiv.org/abs/2504.10857 Webpage🌐:sh8.io/#/zerograsp (1/4 🧵)

OpenThoughts3 is the #1 trending dataset on Huggingface! Thank you to everyone who is using the dataset and giving us great feedback 🚀!

How can we achieve both common sense understanding that can deal with varying levels of ambiguity in language and dextrous manipulation? Check out CodeDiffuser, a really neat work that bridges Code Gen with a 3D Diffusion Policy! This was a fun project with cool experiments! 🤖

Web data, the “fossil fuel of AI”, is being exhausted. What’s next?🤔 We propose Recycling the Web to break the data wall of pretraining via grounded synthetic data. It is more effective than standard data filtering methods, even with multi-epoch repeats! arxiv.org/abs/2506.04689

This plot is a thing of beauty. Great visualization by Jean Mercat! One of many cool artifacts that arose from conducting 1000+ experiments for OpenThoughts 😀

Just did a version of this! And it’s such an energizing experience. Travel award for 8 builders and engineers from the Philippines to spend a week in a retreat here in Silicon Valley. All are working on tough problems to deploy AI in a frontier market with poor infra but

If you’re working on robotics and AI, the recent Stanford talk from Russ Tedrake on scaling multitask robot manipulation is a mandatory watch, full stop. No marketing, no hype. Just solid hypothesis driven science, evidence backed claims. A gold mine in today’s landscape!

TRI's latest Large Behavior Model (LBM) paper landed on arxiv last night! Check out our project website: toyotaresearchinstitute.github.io/lbm1/ One of our main goals for this paper was to put out a very careful and thorough study on the topic to help people understand the state of the

🚀Thrilled to share what we’ve been building at TRI over the past several months: our first Large Behavior Models (LBMs) are here! I’m proud to have been a core contributor to the multi-task policy learning and post-training efforts. At TRI, we’ve been researching how LBMs can

Tokenization has been the final barrier to truly end-to-end language models. We developed the H-Net: a hierarchical network that replaces tokenization with a dynamic chunking process directly inside the model, automatically discovering and operating over meaningful units of data

Open Thoughts delivers again. Congrats team for a small but powerful reasoning model. Writeup: open-thoughts.ai/blog/ot3_small

🚨 The era of infinite internet data is ending, So we ask: 👉 What’s the right generative modelling objective when data—not compute—is the bottleneck? TL;DR: ▶️Compute-constrained? Train Autoregressive models ▶️Data-constrained? Train Diffusion models Get ready for 🤿 1/n

great to see more LLM research on Philippine languages!

1/Pretraining is hitting a data wall; scaling raw web data alone leads to diminishing returns. Today DatologyAI shares BeyondWeb, our synthetic data approach & all the learnings from scaling it to trillions of tokens🧑🏼‍🍳 - 3B LLMs beat 8B models🚀 - Pareto frontier for performance