Over the past two years, EleutherAI has established itself as a radically novel initiative aimed at both promoting open-source research and conducting research in a transparent, openly accessible and collaborative manner. EleutherAI's approach to research goes beyond transparency: by doing research entirely in public, anyone in the world can observe and contribute at every stage. Our work has been received positively and has resulted in several high-impact projects in Natural Language Processing and other fields. In this paper, we describe our experience doing public-facing machine learning research, the benefits we believe this approach brings, and the pitfalls we have encountered.
@article{arxiv.2210.06413,
title = {EleutherAI: Going Beyond "Open Science" to "Science in the Open"},
author = {Jason Phang and Herbie Bradley and Leo Gao and Louis Castricato and Stella Biderman},
journal= {arXiv preprint arXiv:2210.06413},
year = {2022}
}