I made a 4B Qwen3 distill of this model (and a synthetic dataset created with it) a while back. Both can be found here: https://huggingface.co/flashresearch
I think the fine tuned policies are still very brittle, but I agree that this is super promising. It's also one of the most open (the model is still closed) research blogposts we've seen from any private embodied AI lab
seems like an improvement on the aloha approach? You still need to finetune it on roughly the same amount of OOD examples. Contrast this with google's approach over 2023, which was training large vision-language models with the goal of generalizing on OOD.
ML Engineer & Research Scientist. Ex AI grant startup, hedge fund. I've previously worked on inference for LLMs and vision models & have experience with data curation and multinode training. Looking for summer internships or part time positions
SEEKING VOLUNTEERS: open source self-play training for language models
we are a small team associated with EleutherAI. looking to push the frontier of open source language models through self-play. so far we have implemented SPIN. compute included.