On August 27, Real-Time Innovations (RTI) announced that it has been awarded a $1.25 million Small Business Innovation Research (SBIR) Phase II contract. With this contract, RTI will help create a secure, standardized, and reliable AI framework for interaction between software agents, humans, and the target environment–enabling rapid deployment and reuse of cutting-edge AI technologies. RTI Connext was chosen as the data-centric, open standards communication backbone due to its battle-tested features related to simulation support, modularity, scalability, security, and resilience in intelligent systems.
As autonomous systems become an increasingly critical part of defense strategies, distributed intelligence will allow real-time data processing across multiple devices and locations. This will optimize performance and improve decision-making, facilitating seamless AI integration and innovation on the battlefield and beyond.
“For AI to effectively work in large distributed real-world systems, our customers require modular, non-monolithic solutions; they also require data-centric security, which has not been addressed within enterprise AI solutions today,” said Paul Pazandak, director of research at RTI. “Connext is the only technology today that offers the advanced features required to enable this reality. We are excited to receive continued funding to advance our open standards-based generative agentic framework to help facilitate the development of AI-enabled training solutions for our warfighters.”
Based on the Data Distribution Service (DDS) standard, Connext addresses all distributed communication needs for critical systems of all sizes, allowing for more modularity and less code, which substantially reduces development costs. Connext offers access control, security, self-discovery, extensive operational deployment in critical systems, and is supported by both open-source and commercial implementations.
RTI’s contract is part of a larger collection of SBIR-funded efforts focused on applying technology developments, such as generative AI, to improve the autonomous capabilities of unmanned platforms as well as their human-machine interfaces. This effort will use model-based systems engineering and robust testing to create autonomous systems that meet the safety, security and reliability requirements needed for fielding long range, non-lethal drones for surveillance, electronic warfare and communications.
Source: RTI
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