vjepa2

That has always been the policy. To answer your question, Meta has released ~100 models since the Superintelligence Lab reorg. https://huggingface.co/facebook/models The most interesting ones to me are: - CWM (Code world model), an LLM for coding https://github.com/facebookresearch/cwm - DINOv3, A vision encoder https://ai.meta.com/dinov3/ - MAPAnything, a 3d reconstruction model https://huggingface.co/facebook/map-anything - VJEPA v2, Self-supervised video pre-training model https://github.com/facebookresearch/vjepa2

It is readily understandable if you are fluent in the jargon surrounding state of the art LLMs and deep learning. It’s completely inscrutable if you aren’t. The article is also very high level and disconnected from specifics. You can skip to FAIR’s paper and code (linked at the article’s end) for specifics: https://github.com/facebookresearch/vjepa2 If I had to guess, it seems likely that there will be a serious cultural disconnect as 20-something deep learning researchers increasingly move into robotics, not unlike the cultural disconnect that happened in natural language processing in the 2010s and early 20s. Probably lots of interesting developments, and also lots of youngsters excitedly reinventing things that were solved decades ago.