AI for Science & Safety Nodes
Physical hubs in San Francisco and Berlin, with a new xNode in Cape Town.
Application deadline
31st October 2026Request for Proposals
We offer grant funding, office space, community, and compute for open AI for science and safety projects. Our current RFP spans three calls: I. Local Compute, II. Coordination and accountability, III. AI-first science: Bio, Neuro, Nano. Details below.
Ecosystem for decentralized, AI-driven progress
Artificial intelligence is accelerating the pace of discovery across science and technology. But todayโs AI ecosystem also risks the development of civilization-destroying capabilities on the one hand and the centralization of compute, talent, and decision-making power on the other โ concentrating capabilities in ways that could undermine both innovation and safety.
To counter these developments, we are building a decentralized network of Nodes dedicated to AI-powered science and safety. Aside from our own AI nodes in San Francisco in Berlin, we now also have our first community xNode in Cape Town, in collaboration with Cape Institute for Safe AI (CISAI). The goal is to empower researchers and builders with a mission-aligned ecosystem, where AI-driven progress remains open, secure, and aligned with human flourishing.
Our Nodes offer
- Grant funding: see RFPs below
- Hubs: office space in SF and in Berlin
- Compute: access to private compute clusters
Apply for all three types of support, or select one or two based on your needs. We prioritize projects that want to be active, in-person members of one of our hubs in San Francisco or Berlin. You can read more about the mission of the Nodes in our article on Open Science Needs Open Compute.
What is this RFP about?
We are looking for ambitious projects that use AI as the primary engine of progress on two connected problems: making the transition to capable AI go well, and using that transition to unlock science that matters. We believe that there are other areas that are also important for AI to go well, but our focus for this RFP is on areas we think are largely neglected and that Foresight is uniquely suited to funding. Typical grants range between $30,000 โ $100,000 for this RFP but larger amounts are possible for the right project.
The call spans three connected layers:
- I. Local compute is focused on building and providing compute that individuals or communities physically own and control, giving them a chance at agency in the next decade.
- II. Coordination and accountability is exploring the ways humans and/ or AI systems could interact better, and how independent institutions can assess AI risk and create better incentives around it. RFP areas include supercollaboration and decentralized alignment, human empowerment, and AI insurance and open governance.
- III. AI-first science: Bio, Neuro, Nano is focused on the work a good AI transition makes possible. RFP areas include automated nanotechnology, whole-brain-emulation and frontier bio areas like replacement, enhancement or biostasis.
AI-first projects
To keep up with and leverage increasing AI capabilities, we give priority to projects that use AI to achieve their goals. Instead of large team budgets, we are looking for smart allocation of resources and compute to automate workflows. The goal is to enable science and safety to accelerate in tandem with AI for the safe and beneficial evolution of intelligence.
Node-first projects
As stated above, selected projects can receive grant funding, private local compute, and workspace in our San Francisco or Berlin AI Nodes, along with travel-paid field-building events and access to Foresightโs advisors and scientific network. The value of the physical hubs comes from peer collaboration and the work that happens between scheduled programming.
Follow our Foresight calendar for our local AI Node events.
Launch your own AI Node
Our long-term vision is a global, decentralized network of AI Nodes dedicated to the use of AI to further science and human safety. We’re starting with our own hubs in San Francisco and Berlin, but are also interested in collaborating to set up independent Nodes led by others elsewhere.
Weโre envisioning each Node serving as its region’s independent hub: equipped with local compute infrastructure to support a community of researchers and builders advancing secure, safe, private cooperative AI and AI for science. Nodes in the network could share compute, talent, and progress, where aligned, while retaining their own character and governance: forming a meaningful alternative to centralized AI development.
For the right teams, we can offer limited incubation support such as compute know-how, smaller seed funding, plus integration into our wider network.
Are you already building an AI Node, or interested in establishing one in your area? Fill out the form below as an expression of interest to start a conversation.
FAQ
Proposals are first reviewed in-house for fit and quality. Strong submissions are sent to technical advisors for further evaluation. If your proposal advances, we may follow up with written questions or a short call. If you choose to opt into Lightcone Commons sharing, Foresight may also share selected applications with Lightcone Commons for evaluation, and possible additional funding consideration.
Unfortunately, due to the number of applications we receive, we are unable to provide individual feedback to unsuccessful applicants.
- Alignment with the specific RFP focus area: the degree to which the project addresses the selected focus area as outlined in the RFP
- Impact on reducing existential risks from AI: the extent to which the project can reduce existential risks associated with AI, focusing on achieving significant advancements within short timelines.
- Feasibility within short AGI timelines: the projectโs ability to achieve meaningful progress within the anticipated short timeframes for AGI development. We prioritize projects that can demonstrate concrete milestones and deliverables in the next 1-3 years.
- AI-first work: Instead of large team budgets, this means smart allocation of resources and compute to automate workflows.
- Capability to execute: the qualifications, experience, and resources of the applicant(s) to successfully carry out the proposed work. Strong teams with proven expertise in the field will be prioritized.
- High-risk, high-reward potential: the level of risk involved in the project, balanced with the potential for substantial, transformative impact on the future of AI safety. We encourage speculative, high-risk projects with the potential to drive significant change if successful.
- Requirement for open source: We require the work product (code, data, and outputs) of the funding to be open-sourced.
- We fund both short-term and longer projects. Grants are typically paid in one lump sum. However, for larger projects spanning multiple years, payments may be made in tranches, with each subsequent tranche contingent upon the successful completion and reporting of previous milestones.
- We can fund overhead costs up to 10% of direct research costs, where these directly support the funded work.
- Successful applicants must pass our due diligence process, which includes confirming your connections to Foresight Institute, sharing any ongoing criminal proceedings, bankruptcy, tax documents etc., and sharing an itemized budget, project plan and organizational documents.
- By accepting funding, grantees agree that we may list their project on our website and share the project title and project lead on for example social media. If you prefer for your project to remain private, please inform us.
- Grants are subject to basic reporting requirements. Grantees are expected to submit brief progress updates at regular intervals, describing use of funds and progress against agreed milestones.
- Tax obligations vary by country and organization type. Applicants are responsible for understanding and complying with any applicable tax requirements.
Grantees
Previously funded
Dawn Song
University of California
Dan Hendrycks
Center for AI Safety
Blake Richards
Mila
OpenMined
Herbie Bradley
University of Cambridge
Adam Binksmith
AI Digest (Sage)
Yevgeniy Vorobeychik
Washington University in St. Louis