1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
NVIDIA Inception is a non-dilutive accelerator program for AI startups with no fees, no equity requirement, no cohort deadlines, and no minimum funding required to apply. Members can receive up to $100,000 in AWS credits, up to $100,000 in NVIDIA DGX Cloud credits for H100 capacity, preferred GPU pricing, go-to-market and venture-capital exposure, and free technical training.
As of 2026 the program has grown to more than 19,000 AI startup members globally, and it is designed to run alongside other non-dilutive programs such as cloud provider startup credits.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →According to the current listing, eligibility includes: Startups building products or services in AI, data science, or accelerated computing; applications accepted on a rolling basis with no equity or fee requirements. Confirm the full requirements in the official notice before applying.
The current listing shows free membership; up to $100,000 in AWS credits and up to $100,000 in NVIDIA DGX Cloud (H100) credits, plus preferred GPU pricing and free technical training. Verify award ceilings, matching requirements, and allowable costs in the official notice.
NVIDIA Inception Program for AI Startups (Cloud Credits, GPU Pricing, and Technical Support) is funded by NVIDIA. 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.
NVIDIA's Academic Hardware Grant Program donates GPU hardware to qualifying academic researchers, with a specific track focused on AI Safety and Trustworthy AI research (including interpretability, alignment, evaluation, red-teaming, and bias/fairness). Awardees receive workstation- or datacenter-class NVIDIA GPUs delivered to their institutions for use in research projects. Applications are accepted on a rolling basis through the NVIDIA Higher Education and Research portal. Projects must produce a publishable research output or open-source artifact and acknowledge NVIDIA's hardware contribution. The AI Safety track is specifically highlighted by NVIDIA's collaboration with the AI Safety Directory and prioritizes researchers working on interpretability, evaluations, robustness, and trustworthy ML. Strong fit for graduate students, postdocs, and early-career faculty doing AI safety, alignment, or interpretability research at universities without existing GPU access, as well as nonprofit AI safety research organizations.
NVIDIA's Applied Research Accelerator Program provides academic researchers with GPU hardware, cloud compute, and cash support in three tiers: Base ($20K for projects with real-world impact potential), Adoption ($60K for projects with commercial or government adoption plans), and Production ($160K when organizations invest in production conversion). The program supports research with practical applications in GPU-accelerated computing, AI, machine learning, data analytics, and HPC. Applications are reviewed quarterly with four annual cycles: Q1 submissions decided June, Q2 decided September, Q3 decided December, Q4 decided March.
The Merck Stimulating Innovative Research Grant Program 2026 includes a dedicated grant topic for artificial intelligence in cell culture media and process development, offering up to EUR 150,000 per year for up to 3 years. The program accelerates innovation through collaborative research, early engagement with industry experts, and translation of novel ideas into practical solutions. In 2026, priority areas also include in-vitro models for neuroinflammatory diseases (EUR 250,000/year for 2 years) and innovative approaches to contaminated materials remediation (EUR 150,000/year for 2 years). The two-stage application process begins with non-confidential submissions, followed by deep-dive workshops where finalists collaborate with Merck scientists and managers to jointly optimize proposals. The AI-specific grant focuses on applying machine learning and AI to optimize cell culture media formulation, bioprocess parameter optimization, and manufacturing quality control.
The Sony Research Award Program is Sony's principal channel for funding external academic research, and the Focused Research Award is its collaborative track: up to 150,000 dollars for focused joint research between a university or research institute and Sony. The 2026 research areas are unusually broad for a corporate program and cover most of the modern AI stack alongside Sony's hardware interests - AI and large language models, computer vision, machine learning, robotics, human-computer interaction, affective computing, speech and language technologies, audio technologies, RF sensing, wireless communications, cybersecurity, sports technology, digital humans, generative AI, content creation and neural rendering, plus device-level areas including MicroLED and optical metasurfaces. For AI and robotics groups this makes it one of the wider corporate calls available, though the breadth is deceptive: Sony funds work that connects to its own research agenda, and proposals are strongest when there is an identifiable Sony research counterpart for the collaboration. Eligibility is tightly drawn around the principal investigator rather than the institution. The PI must be a full-time faculty member or researcher at a recognized institution - Assistant Professor, Associate Professor, Professor or equivalent researcher - and must be able to supervise PhD students. Co-PIs are permitted but must be from the same institution and meet the same requirements, which rules out the cross-institutional consortia common in public funding. The 2026 deadline is 15 September 2026 at 11:59pm Pacific, with a separate India-specific time given as 16 September 2026. Submission guidelines are on the Sony Research Award Program site.
The Meta Research PhD Fellowship supports doctoral students conducting research in areas central to Meta's technical agenda, with several of its annual award tracks dedicated to artificial intelligence and machine learning. Current AI-relevant tracks include AI System Hardware/Software Co-Design (high-performance AI algorithms spanning model compression, numerical optimization, benchmarking, and distributed inference and training), Applied Statistics (bias and variance estimation and correction in models and datasets, uncertainty quantification), AR/VR Human Understanding (efficient ML techniques that run on AR/VR devices), and Programming Languages (program synthesis, probabilistic and differentiable programming). Recipients receive two years of paid tuition and fees, a $42,000 annual stipend covering living expenses and conference travel, and a paid visit to Meta headquarters for the annual Fellowship Summit; the award carries no intellectual property claim on the student's research. The 2027 cycle opened August 3, 2026 with applications closing September 20, 2026, reference letters due in October 2026, and winners notified in January 2027.
NSF 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleThe OMAI project — led by AI2, funded by NSF and NVIDIA — will create fully open multimodal AI models for scientific research. For researchers priced out of commercial AI, this changes the equation.
Read article