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Find similar grantsThis program supports local infrastructure projects deemed to have a positive impact on the military value of installations within the state.
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Or search similar grants →According to the current listing, eligibility includes: Florida counties, municipalities, special districts, and state agencies. Confirm the full requirements in the official notice before applying.
Florida Defense Infrastructure Grant (DIG) Program is funded by FloridaCommerce. Verify program details on the funder's official page before applying.
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DARPA's TIAMAT (Transfer from Imprecise and Abstract Models to Autonomous Technologies) program develops sim-to-real transfer techniques that train autonomous systems in low-fidelity, abstract simulations and reliably deploy them in unpredictable physical environments. Research targets foundations for rapid sim-to-real generalization, robustness to physics-model error, and transfer learning across morphology and sensor configurations. The program is structured as two 18-month phases and supports applications including ground autonomy, aerial autonomy, and robotic manipulation in adversarial, novel, or contested settings. Awards have included University of Central Florida ($1.2M) and other academic and industry performers. TIAMAT is a core DARPA investment in foundational autonomy R&D.
The DHS Counter-Unmanned Aircraft Systems (Counter-UAS) Grant Program was established to support state and local law enforcement, critical infrastructure operators, and other eligible entities in deploying AI-enabled detection, tracking, identification, and mitigation technologies against malicious drones. The program received $500 million in appropriated funding, with FY2026 prioritizing $250 million for the 11 states hosting FIFA World Cup 2026 matches (California, Florida, Georgia, Massachusetts, Missouri, New Jersey, New York, Pennsylvania, Texas, Washington, and the New Jersey/New York Metropolitan area) and for the National Capital Region. Funds may be used for radar, RF detection, computer vision, machine learning-based UAS classification, sensor fusion, autonomous response systems, training, and integration with public safety command and control. The program prioritizes AI-enabled C-UAS capable of distinguishing hostile drones from authorized aircraft in cluttered urban airspace.