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AI Grant (for open source projects) is sponsored by AI Grant. This program offers grants for open-source projects leveraging AI models in useful or engaging ways. Grants can be in the form of compute credits or cash, with no strings attached.
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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: Anyone can apply; focus on pre-seed/seed-stage startups building AI-native products or open-source AI projects. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates $5,000 - $50,000 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.
Research on Circular Economy, Smart Manufacturing, and Energy-Efficient Microelectronics is sponsored by U.S. Department of Energy (DOE) Advanced Materials & Manufacturing Technologies Office (AMMTO). This funding opportunity supports innovative technology R&D across the manufacturing sector with a focus on circular economy, smart manufacturing, and energy-efficient microelectronics. While the stated deadline for full applications has passed, AMMTO frequently issues similar solicitations, and this highlights a relevant area of interest for the DOE.
AWS Imagine Grant program - Momentum to Modernize Award is sponsored by Amazon Web Services (AWS). This award provides funding for transformational infrastructure projects, helping nonprofit organizations enhance their core mission operations with technology. This includes foundational technology projects, such as migrating servers to the cloud and modernizing new and existing applications.
NIST AI-Focused Manufacturing USA Institute is sponsored by National Institute of Standards and Technology (NIST). NIST announced an open competition for a new Manufacturing USA institute focused on the use of artificial intelligence (AI) to increase the resilience of U.S. manufacturers. The institute will be required to obtain cost-share funds from nonfederal sources.
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