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DARPA's AI Forward initiative explores new directions for artificial intelligence research that will result in trustworthy systems for national security missions. The program emphasizes three core research areas: foundational theory, AI engineering, and human-AI teaming.
AI Forward operates as an umbrella initiative funding multiple specific programs including EMHAT (Embodied Human-AI Teams), FACT (Conversational Accountability), FoundSci (Foundation Models for Scientific Discovery), and the AI Next Campaign. Funding flows through AI Exploration (AIE) opportunities with streamlined contracting procedures designed to rapidly advance promising AI concepts.
Awardees must begin work within three months of opportunity announcement and operate on 18-month feasibility timelines, enabling rapid exploration of high-risk, high-reward AI research directions for defense applications.
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Or search similar grants →According to the current listing, eligibility includes: Open to qualified researchers and experts in artificial intelligence including U.S. universities, research institutions, nonprofit research organizations, small businesses, and large defense contractors. Applicants should demonstrate technical capability in foundational AI theory, AI engineering for production systems, or human-AI teaming. Foreign participants generally require additional review. Specific eligibility per AIE topic announcement. Confirm the full requirements in the official notice before applying.
The current listing shows funding flows through AI Exploration (AIE) opportunities with streamlined contracting procedures. AIE awards typically up to $1 million for 18-month feasibility studies. Awardees must begin work within three months of opportunity announcement. Specific award amounts vary by individual program announcement under AI Forward umbrella. Verify award ceilings, matching requirements, and allowable costs in the official notice.
DARPA AI Forward Initiative for Trustworthy AI in National Security Missions is funded by Defense Advanced Research Projects Agency (DARPA). 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.
The FY2026 Department of Defense Multidisciplinary University Research Initiative (MURI) program supports basic research in science and engineering at U.S. institutions of higher education, with emphasis on multidisciplinary research where more than one traditional discipline interacts. The Army, Navy, and Air Force basic research offices are seeking applications across 22 topic areas including artificial intelligence and autonomy, information sensing and processing, and systems manipulation. MURI grants typically provide $1.25 million to $1.5 million per year for three years with option to extend two additional years. Approximately $170 million in total funding is available annually across all topics. The program is administered through the Office of Naval Research (ONR), Army Research Office (ARO), and Air Force Office of Scientific Research (AFOSR).
The NSF Convergence Accelerator is a grant from the National Science Foundation (NSF) that funds multidisciplinary teams working to solve national-scale societal challenges through convergence research and innovation. Launched in 2019 under NSF's Directorate for Technology, Innovation and Partnerships, the program operates in two phases: Phase 1 awards are up to $750,000, with successful teams advancing to larger Phase 2 awards. Eligible applicants include institutions of higher education and nonprofit or for-profit organizations. Track I and Track K focus on specific high-priority topics announced each funding cycle. The next deadline is June 15, 2026. Proposals must comply with updated NSF research security policies effective July 2025.
DICE asks for something most multi-agent AI research quietly assumes away: a collective of heterogeneous AI agents that holds its mission together with no central controller, under active adversarial pressure, over long time horizons, and still stays under human control. Issued by DARPA's Information Processing Techniques Office as BAA HR001126S0010 on June 10, 2026 with Susmit Jha as program manager, the program funds the theory and algorithms for decentralized coordination and local inference control rather than fielded systems - all demonstration and evaluation is in simulation, which meaningfully lowers the barrier for university and software-only teams that cannot support hardware integration. The work splits into three technical areas: TA1 decentralized coordination and consensus, TA2 local inference control that keeps individual agents role-coherent and mission-aligned without global oversight, and TA3 testing and evaluation in simulation. TA2 is the conceptual core and the hardest sell - it targets the failure mode where individually reasonable agents drift collectively off mission, which is precisely the behavior that makes decentralized LLM-agent swarms unusable for defense today. The program runs 36 months in three phases: 9 months for Phase 1 (Decentralization), 15 months for Phase 2 (Adversarial Robustness), and 12 months for Phase 3 (Scale), so proposals must show a credible path through adversarial robustness rather than only demonstrating clean-environment coordination. DARPA has not published an award ceiling; multiple awards are anticipated and DARPA may use Procurement Contracts, Other Transaction Agreements or Cooperative Agreements, meaning nontraditional performers can structure around an OTA. A Proposers Day was held under DARPA-SN-26-72. Full proposals are due August 25, 2026, so teams engaging now are at the deadline and should look to abstract feedback and any amendment extensions.
DPA26BZ05-DV019 asks small businesses to reduce ISR video transmission from small drones by 90 to 99 percent while preserving what an operator actually needs, on a Jetson-class board at a 2-watt final power budget. It is Direct-to-Phase-II, up to $1.5 million base plus a $500,000 option, and its exclusion list — no weapon release, no lethal engagement, no named-person identification — is the most strategically revealing paragraph in DARPA's FY26 Release 5.
Read articleDPA26BZ05-DV018 is the largest award in DARPA's FY26 SBIR Release 5 — up to $3 million over 18 months, Direct-to-Phase-II only. It funds four subsystem tracks for an underwater 3D concrete printer that uses seafloor sediment and seawater with under 20 percent binder. Here is what the Trenton program already proved, why the track structure is really a supplier-qualification exercise, and who can clear the prior-feasibility bar in the four weeks that remain.
Read articleTwo weeks after the DARPA Lift Challenge ended with the winner at 3.84:1 — short of the 4:1 target — DARPA posted a Direct-to-Phase-II SBIR that requires empirical proof of a 4:1 payload-to-weight ratio to bid. DPA26BZ05-DV022 offers up to $1.5 million over 24 months across two tracks that map exactly onto the Challenge's two design prizes. Here is who can actually clear the entry bar, what the month-9, month-18, and month-24 gates demand, and why the certification language is the real story.
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