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"Digital Promise K-12 AI Infrastructure Program Open Source AI Model for Tutoring (EDU AI) Request for Proposals" is currently closed and not accepting applications.
The Open Source AI Model for Tutoring (EDU AI) RFP, part of Digital Promise's Gates Foundation-funded K-12 AI Infrastructure Program, provides up to $8 million to a single team to build an open-source AI model for K-12 math tutoring in the United States.
The effort targets known limitations of frontier models — 'helpful assistant' bias, weak misconception recognition, and limited pedagogical effectiveness — and requires rigorous evaluation, safety safeguards, and open release of all deliverables (content under CC BY 4. 0 and code/models under Apache 2. 0 or similar).
The goal is durable public infrastructure usable by researchers, districts, curriculum teams, and model developers rather than a closed commercial product. The project period is 30–36 months with work beginning around November 2026.
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Or search similar grants →According to the current listing, eligibility includes: Organizations or institutions with a prior peer-reviewed publication on U.S. education AI models (before May 8, 2026), a track record of contributing significant digital public goods, and deployment or evaluation on real student data at meaningful scale; teams must cover ML/AI engineering, K-12 practice, learning science/education research, and ed-tech product partnership roles. Confirm the full requirements in the official notice before applying.
The current listing shows up to $8,000,000 for a single award over a 30–36 month project period. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was July 31, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Digital Promise K-12 AI Infrastructure Program Open Source AI Model for Tutoring (EDU AI) Request for Proposals is funded by Digital Promise (K-12 AI Infrastructure Program), funded and managed by the Gates Foundation. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The AI Safety Policy Entrepreneurship Fellowship is FAS's route for turning technical and domain expertise into frontier AI safety policy that actually moves. It is a part-time hybrid programme running 30 September 2026 to 28 February 2027, with applications due 7 September 2026, and it pays a USD 5,000 stipend plus up to USD 1,000 as a merit award. Fellows commit roughly five hours a week to developing a policy memo on a specific AI safety challenge, attend training sessions, join an in-person retreat in California from 4 to 7 November 2026, and present at a capstone event in Washington DC during the week of 22 February 2027. The design target is explicit and unusual: it recruits early- to mid-career professionals who have limited direct public policy experience but deep expertise elsewhere - technical AI research, academia, think tanks, civil society, industry, law, cybersecurity and national security - and teaches them the mechanics of getting an idea adopted. Selection weighs clear understanding of AI governance challenges, concrete implementation-oriented solutions rather than broad principles, awareness of which stakeholders must be moved, and a credible commitment to translating expertise into policy outcomes. Because the stipend is modest and the time commitment part-time, this is designed to sit alongside an existing job rather than replace one.
The Climate Change AI Innovation Grants program supports projects that address research and deployment challenges in climate change mitigation, adaptation, and climate science by leveraging AI and machine learning, while also creating publicly available datasets and tools to catalyze further work. The program enables key partnerships that accelerate the research-to-deployment cycle, creating synergies between academic researchers, nonprofits, startups and other companies, and governmental or intergovernmental organizations. Funded by the Quadrature Climate Foundation, Schmidt Futures, and Google DeepMind, with Future Earth serving as fiscal sponsor, this is one of the few dedicated grant programs specifically targeting the intersection of AI/ML and climate change. Projects typically involve climate modeling, weather prediction, emissions monitoring, energy optimization, biodiversity monitoring, and other environmental applications of machine learning. The 2026 competition opens with a full proposal deadline of September 15, 2026. The program has grown steadily since its inception, funding 23 projects to date across diverse climate domains and geographies.
The Climate Change AI Innovation Grants program supports catalytic projects using AI and machine learning for climate action, funding research and deployment challenges in climate change mitigation, adaptation, and climate science. Projects must create publicly available datasets and tools as digital public goods, and release open-source code. The program builds partnerships between academic researchers, non-profits, startups, companies, and governmental organizations to accelerate the research-to-deployment cycle. Past funded projects span climate modeling, emissions monitoring, renewable energy optimization, and disaster prediction across all continents.
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