Georgia

NAVAL AIR WARFARE CENTER WEAPONS DIVISION (NAWCWD) AIRBORNE ELECTRONIC ATTACK INTEGRATED PRODUCT TEAM (AEA IPT) MACHINE LEARNING SUPPORT

ARTIFICIAL INTELLIGENCE/MACHINE LEARNING-ENABLED AUTONOMOUS

BIOINTELLIGENCE AND BIOSECURITY FOR INTELLIGENCE COMMUNITY (B24IC)RAPID AUTOMATED BIOSOURCING THROUGH MACHINE LEARNING (RABML)

TOPIC A224-016 - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (AI/ML) POWERED PLATFORM FOR ARMY ASSET TRACEABILITY, PREDICTIVE MAINTENANCE, AND QUALITY TRACKING

FY24 SBIR/STTR TOPIC#: OSD234-P002| PHYSICS INFORMED MACHINE LEARNING FOR IMPROVED MULTI-SENSOR FUSION IN THE MARITIME KILL CHAIN

ACCELERATING MULTI-SOURCE INTELLIGENCE ANALYSIS AND DECISION MAKING WITH ARTIFICIAL INTELLIGENCE-DRIVEN MODEL CHAINING

RADOME OPERATIONAL PERFORMANCE EVALUATION AND TUNING WITH MACHINE LEARNING METHODS

MACHINE LEARNING METHODS TO CATALOG SOURCE FROM DIVERSE, WIDELY DISTRIBUTED SENSORS

DEPARTMENT OF DEFENSE CIVILIAN LEADER DEVELOPMENT EXPERIMENT WITH TECHNOLOGY AND ARTIFICIAL INTELLIGENCE, IMPLEMENTING NEW TECHNIQUES THEN TESTING AGAINST PREVIOUS PRACTICES

BROAD AGENCY ANNOUNCEMENT TASK ORDER CONTRACT FOR RESEARCH AND DEVELOPMENT SERVICES INVOLVING ENHANCING SITUATION AWARENESS FOR COMMAND AND CONTROL (C2) THROUGH AGENTIC ARTIFICIAL INTELLIGENCE

SBIR I MACHINE LEARNING-AUGMENTED FAR-FIELD NOISE PREDICTION FOR DISTRIBUTED ELECTRIC PROPULSION AIRCRAFT

THE STRATEGIC CAPABILITIES OFFICE PHASE I SMALL BUSINESS INNOVATION RESEARCH PROGRAM CONTRACT AWARD FOR PHYSICS INFORMED MACHINE LEARNING FOR IMPROVED MULTI-SENSOR FUSION IN THE MARITIME KILL CHAIN

INVESTIGATE THE FEASIBILITY OF LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE {GENAI) TO ENABLE AUTONOMOUS COOPERATION AMONG SMALL UNMANNED AERIAL SYSTEMS {SUAS) OPERATING IN DYNAMIC, NETWORK-CONSTRAINED ENVIRONMENTS.

INVESTIGATE THE FEASIBILITY OF LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) TO ENHANCE DYNAMIC SITUATIONAL AWARENESS THROUGH COLLECTED IMAGERY ANALYSIS.