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Schmidt Sciences 2026 Interpretability RFP funds technical research on detecting and mitigating deceptive behaviors in large language models.
The program targets three primary directions: (1) Detection — developing tools to identify deceptive behaviors where model outputs contradict internal representations of truth; (2) Steering — creating targeted interventions to improve model truthfulness using mechanistic insights, outperforming traditional finetuning baselines; and (3) Applications — translating detection and steering techniques into practical improvements for human-AI collaboration, multi-agent systems, and decision support.
Deceptive behaviors include factually incorrect outputs, misleading confidence claims, fabrications, selective omissions, and other knowingly misleading conduct. Awards range from $300K to $1M with projects lasting 1-3 years.
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Search similar grants →Based on current listing details, eligibility includes: Open globally to individual researchers, research teams, research institutions, and multi-institution collaborations across universities, national laboratories, institutes, and nonprofit research organizations. Cross-border partnerships encouraged. Indirect costs cannot exceed 10%. Funded projects must comply with applicable law without lobbying or political activity. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $300,000 to $1,000,000 per award inclusive of overhead up to 10%. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is May 26, 2026. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
The Wellcome Mental Health Data Prize UK 2026-2028 supports the development of data tools and AI solutions contributing to improving early intervention for anxiety, depression, and psychosis. This prize program, managed in partnership with Social Finance, funds teams to develop innovative data science and AI tools that can identify individuals at risk of mental health conditions earlier and connect them with appropriate interventions. The prize builds on Wellcome's broader mental health science priorities and complements their separate generative AI mental health research program. Previous rounds funded teams at approximately £200,000 each. The UK 2026 round accepts applications until May 8, 2026 at 12pm. The prize program has previously operated in Africa (2024-2026 with £200,000 per team) and globally (2022-2023 with £1.4 million total). Contact: dataprize@wellcome.org.
The Bill & Melinda Gates Foundation AI Fellows Program is the Foundation's first-ever AI Fellows cohort, a fully funded 12-month opportunity that places selected candidates on high-impact projects applying artificial intelligence to real-world challenges in health, agriculture, and development. Fellows work closely with Foundation program teams and receive structured mentorship while building innovative AI-driven solutions for low- and middle-income countries. Focus areas include global health systems, agricultural innovation for smallholder farmers across sub-Saharan Africa and South Asia, education technology, and development challenges. The program reflects the Foundation's strategic commitment to AI for public good, including real-time weather forecasts for regions without local weather stations, multilingual digital advisory services for farmers, and AI-driven crop improvement initiatives. The India office is currently accepting applications for the inaugural cohort. The Foundation has committed $1.4 billion over four years to expand agricultural innovation through AI and digital tools.