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Supports academics and independent researchers in developing innovative solutions to critical AI risks through targeted grantmaking.
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We updated our website and would love your feedback! Funding groundbreaking research in AI safety FAR. AI supports academics and independent researchers in developing innovative solutions to critical AI risks through our targeted grantmaking program.
Currently, due to limited evaluation capacity, we are only able to consider researchers nominated by experts with a strong track record. We plan to launch public requests for proposals (RFPs) soon, focused on high-impact research areas. Our grantmaking is funded by a $12 million grant generously provided by Coefficient Giving.
Failure Modes in Superhuman Systems Florian Tramer, ETH Zurich Broad project examining robustness across four vectors: data poisoning, consistency checks, model stealing, and prompt injection.
Comprehensive Red-Teaming Framework Wenbo Guo, UC Santa Barbara Building automated testing systems for LLM alignment against both training-phase threats and testing-phase threats, with a focus on developing agent-based systems that can generate adversarial prompts.
Explaining Superhuman AI Decisions Nicholas Tomlin, UC Berkeley Using weak-to-strong generalization to explain superhuman AI systems’ decisions, focusing on domains like chess/Go where superhuman AI already exists. Ashwinee Panda, University of Maryland College Park Developing methods to make alignment more secure against jailbreaks, prefilling attacks, and finetuning attacks, with approaches spanning the entire model lifecycle.
Explaining Superhuman AI Decisions Nicholas Tomlin, UC Berkeley Using weak-to-strong generalization to explain superhuman AI systems’ decisions, focusing on domains like chess/Go where superhuman AI already exists.
Comprehensive Red-Teaming Framework Wenbo Guo, UC Santa Barbara Building automated testing systems for LLM alignment against both training-phase threats and testing-phase threats, with a focus on developing agent-based systems that can generate adversarial prompts.
Ashwinee Panda, University of Maryland College Park Developing methods to make alignment more secure against jailbreaks, prefilling attacks, and finetuning attacks, with approaches spanning the entire model lifecycle. Failure Modes in Superhuman Systems Florian Tramer, ETH Zurich Broad project examining robustness across four vectors: data poisoning, consistency checks, model stealing, and prompt injection.
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According to the current listing, eligibility includes: Academics and independent researchers nominated by experts with a strong track record (currently). Public RFPs for high-impact research areas are planned. Confirm the full requirements in the official notice before applying.
FAR.AI Grant Program is funded by FAR.AI. Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
A compliance roadmap published August 19 lays out what colleges and universities have to certify before the 2026-2027 academic year — and two of the items get almost no attention. FAR 52.222-90 must be flowed into existing contracts by December 31, 2026. And under EO 14282, certification of Section 117 foreign gift compliance is now expressly material to False Claims Act liability and to receiving federal grant funds at all. Here is the full stack, the dates, and what a defensible file looks like.
Read articleBuried in the §200.340 termination provisions of the May 29 Uniform Grants Regulation rewrite is a fundamental restructuring of federal grant termination law. The new rule explicitly models grant termination on the Federal Acquisition Regulation's termination-for-convenience framework — agencies may terminate when termination is in the agency's interest, when an award no longer advances agency priorities, or when the national interest as it exists at the time of termination has shifted. Unlike federal contracts, the rule eliminates the objection, hearing, and appeal rights that have historically attached to termination decisions, and unlike federal contracts, it does not import the FAR's termination settlement framework. Multiyear grant recipients now bear contract-level cancellation risk without contract-level settlement protection.
Read articleThe FAR overhaul raises compliance thresholds, renumbers clauses, and restructures cybersecurity rules. Small businesses stand to save thousands in compliance costs if they prepare now.
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