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AI Grant Program is a grant from AI Grant, founded by Nat Friedman and Daniel Gross, that funds open source projects in artificial intelligence with no strings attached. Grants range from $5,000 to $50,000 and can be provided as cash or compute credits.
The program has supported a wide range of AI and machine learning projects, including neural network libraries, language model tooling, medical imaging AI, quantum system simulations, 3D object generation, and data compression. Past recipients include developers working on llama-cpp-python, the GGUF file format, reinforcement learning agents, and browser-based deep learning.
Individual entrepreneurs and early-stage startup founders building AI-first solutions are eligible to apply.
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AI Grant — grants for open source projects Looking for our accelerator program? Check out aigrant. com !
$5,000 - $50,000 in grants for open source projects, no strings attached. Grants can come in the form of compute or cash. abetlen – for their work on llama-cpp-python.
philpax – for their work on the GGUF file format. TySam – for their work on 10-second models. Russell Kaplan and Christopher Sauer , to build and open source an RL agent that learns faster because you can talk to it based on our prototype that beats most other approaches to Montezuma’s Revenge ( paper ).
Kevin Kwok , a fast cross-platform library for hardware-accelerated deep learning in the browser using WebGL ( video ). Jordi Pons , the freesound datasets project ( video ). Patrick Slade , machine learning for motion recognition and trajectory generation of human movement for rehabilitation ( video ).
Oliver Hennigh , predicting steady state fluid flow using deep neural networks ( video ). Manasi Vartak , a system to manage machine learning models ( video ). simulation of many-body quantum systems with neural networks ( video ).
Liam Patrick Atkinson , a neural network to generate puns ( video ). Natalia Mykhaylova , training datasets and source identification algorithms for sensor networks that improve public health ( video ). Mark Wronkiewicz , Majid Mirbagheri and Nicholas Foti , to simulate human brain activity using tools recently development in machine learning ( video ).
Zbigniew Wojna (co-author of Inception-v3, one of the first better-than-humans perception models), object detection and instance segmentation for small objects ( paper ). Flora Ponjou Tasse , turning hand-drawn sketches into 3D objects using generative models ( video ). Radim Rehurek , is going to make gensim (hugely popular open-source library for topic modeling) support many of the latest-and-greatest research papers ( video ).
Byron Knoll, author of cmix , a library that uses deep learning to compress files ( video ). Brian Nord , for using AI to model the physics of strong gravitational lensing ( video ). Samuel Lee , Neal Jean , Tracey Hong and Feiya Shao , Bob Zheng , will make neural networks that detect child abuse in X-Rays ( video ).
Darius Barušauskas , AI to assist doctors interpreting brain stroke scans with 3D Computerized Tomography ( video ). Hannah Davis , creating a dataset of sceneries that evoke different emotional responses ( video ). David Koes , AI that checks for docking of various drugs to accelerate structure-based drug design ( video ).
A. Mira Chung and Hooyeon Lee , use DL to generate art for video games ( video ). Sarah Newman , a series of thought experiments about human values in speculative AI futures ( video ).
Alex Wang , AI that protects you from face recognition systems ( video ). Aidan Gomez , cipher cracking(!) using generative adversarial neural networks ( video ).
Ranjay Krishna , extracting object and relationship classifications from video ( video ). Kaden Hazzard , predicting quantum dynamics from short-time dynamics using machine learning ( video ). Ariel Kanevsky , a DNN algorithm capable of analyzing free tissue transfers and detect abnormal vascular flow within blood vessels ( video ).
Jake Bian , Firebug, for deep learning ( video ). Daniel Soudry , a neural network that predicts the validation error of another neural network ( video ). Tejpal Virdi , John Guibas and Peter Li , use GANs to generate usable and privacy preserving training data.
Ekta Prashnani , a metric to assess image quality consistent with human perception of image quality. Established in 2017 by Nat Friedman and Daniel Gross .
Based on current listing details, eligibility includes: Seed-stage AI startup founders building AI-native product startups Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $250,000 (SAFE) + $350,000 Azure credits + $250,000 additional credits Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. 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.
Yes — AI tools like Granted can help research funders, draft proposal sections, and check compliance. However, always review and customize AI-generated content to reflect your organization's unique strengths and the specific requirements of the solicitation.
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.
Dollar General Literacy Foundation Youth Literacy Grants is sponsored by Dollar General Literacy Foundation. These grants provide funding to schools, public libraries, and nonprofit organizations to help students who are below grade level or experiencing difficulty reading. Funds can be used for new or expanded literacy programs, technology/equipment, or books/materials/software.
The J.M.K. Innovation Prize is a grant from The J.M. Kaplan Fund recognizing early-stage social entrepreneurs working on environmental, heritage, and social justice challenges. The prize rewards individuals and organizations demonstrating innovative, entrepreneurial approaches to enduring problems. Applications for the 2025 prize were accepted February 11 through April 25, 2025 via an online portal. Spanish-language applications are welcomed, and a Spanish application form is available for download. The prize is biennial and open to a broad range of applicants across the United States working on forward-thinking solutions at the intersection of environment, community, and cultural heritage.