The interventions catalog
PL R&D helps frontier ideas move from open research to deployment — one field-level constraint at a time. Browse the public programs below, or read how we choose the work.
How we choose our interventions →Draft-source examples. Not approved commitments.
15 published examples. Draft-source programs, labeled as proposed — not a verified active inventory.
Help national institutions turn open models into useful, locally maintained AI capability.
Give public institutions credible evidence for AI adoption decisions.
Make participatory decision tools easier to adopt, evaluate, and maintain.
Turn public-goods research conversations into sustained collaborations.
Develop shared research and evaluated AI tools for environmental institutions.
Make credible evaluation more useful and affordable.
Turn country requirements into usable compute access and technical capability.
Help a senior cross-institutional cohort advance shared missions.
Make connectome reconstruction a measurable, competitive AI problem.
Create a primate reference dataset that tests long-range tracing.
Test whether neural simulation can predict a new biological result.
Make a large-scale connectome program technically and financially credible.
Give AI researchers well-defined neuroscience problems they can work on.
Build shared simulation infrastructure after a discovery target is proven.
Supply persistent operational ownership and an AI-native talent pipeline.
Public types here follow the FA2 draft vocabulary. See the methodology for how they relate to the Console toolkit.