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Find similar grantsNVIDIA Inception Program is sponsored by NVIDIA. A program for AI startups providing access to specialized GPU hardware, software tools, and cloud credits to accelerate development of computer vision and spatial AI for home improvement applications.
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Or search similar grants →According to the current listing, eligibility includes: Startups at any stage that are building products based on AI, data science, or GPU-accelerated technologies. Confirm the full requirements in the official notice before applying.
NVIDIA Inception Program is funded by NVIDIA. Verify program details on the funder's official page before applying.
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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.
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.
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