In a new blog, Russell Power explains how the Marin team nearly doubled its sustained TPU usage by creating a custom global scheduler: Iris. Iris searches every region where Marin has compute, places each job wherever capacity appears, and moves data along as needed. 🔗 openathena.ai/blog/cluster...

To train better open models, we need predictable scaling. Delphi is Marin’s first step: we pretrained many small models with one recipe, then extrapolated 300× to predict a 25B-param / 600B-token run with just 0.2% error. Getting there took some work 🧵

Learn more about the project in Percy's blog post: marin.community/blog/2025/05... And about the Models we are releasing in @dlwh.bsky.social's training retro: marin.readthedocs.io/en/latest/re...

Super excited Marin is finally out! Come see what we've been building! Code/platform for training fully reproducible models end-to-end, from data to evals. Plus a new high quality 8B base model. Percy did a good job explaining it on the other place. marin.community x.com/percyliang/s...

Percy Liang on X: "What would truly open-source AI look like? Not just open weights, open code/data, but *open development*, where the entire research and development process is public *and* anyone can contribute. We built Marin, an open lab, to fulfill this vision: https://t.co/racsvmhyA3" / X

What would truly open-source AI look like? Not just open weights, open code/data, but *open development*, where the entire research and development process is public *and* anyone can contribute. We built Marin, an open lab, to fulfill this vision: https://t.co/racsvmhyA3

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