CAIS Project

Compute Cluster

The Center for AI Safety is providing compute resources for ML safety research.

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Center for AI Safety resources :

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What is the CAIS Compute Cluster?

The Center for AI Safety is launching an initiative to provide free compute support for research projects in ML safety.

  • CAIS has set up a compute cluster specifically for ML safety research
  • 256 A100 GPUs with 80GB memory
  • 1,600 Gbit/s inter-node network speeds.

We hope that this initiative enables researchers to pursue novel lines of research which would be otherwise infeasible to pursue. Others should feel free to apply as well, but with our current limited capacity, the application is primarily for professors.

Any questions can be directed to compute@safe.ai

Our Collaborators

We support leading experts in a diverse range of ML safety research directions.

Matthias Hein

Professor of Machine Learning, University of Tübingen

Jinwoo Shin

Professor of AI, Korean Advanced Institute of Science & Technology

Dawn Song

Professor of Computer Science, University of California Berkeley

David Wagner

Professor of Computer Science, University of California Berkeley

Percy Liang

Associate Professor of Computer Science, Stanford University

Scott Niekum

Associate Professor of Computer Science, University of Massachusetts Amherst

David Bau

Assistant Professor of Computer Science, Northeastern Khoury College

Robin Jia

Assistant Professor of Computer Science, University of Southern California

Bo Li

Assistant Professor of Computer Science, University of Illinois at Urbana-Champaign

Who is Eligible for Access?

  • The CAIS Compute Cluster is specifically designed for researchers who are working on the safety of machine learning systems. Work which improves general capabilities or work that improves safety as a consequence of improving general capabilities are not in scope. 
  • For a non-exhaustive list of topics we are excited about, see Unsolved Problems in ML Safety or the ML Safety Course.
  • The current application is primarily for professors.