Autonomy in Defense schedule

Today's military systems are often rigidly linked, creating for example fragile "kill chains" that are vulnerable to single points of failure and also slow to upgrade. The Family of Autonomous Combat Systems (FACS), an architectural framework designed to address these vulnerabilities exploits modern AI to overcome these limitations. FACS enables the flexible and dynamic combination of different military systems to create an antifragile "Family" of interconnected systems that can be assembled and reassembled on the fly using AI. This enables mission success through multiple avenues (savage equifinality), making the overall force antifragile. Ultimately, FACS offers a decisive advantage by enabling the rapid integration of cutting-edge technology, shifting the paradigm from the slow pace of acquisition to the speed of AI enabled autonomous innovation.

• Advancing autonomous capabilities to enhance Combat Air Force mission effectiveness
• Integrating human–machine teaming across air operations and multi-domain environments
• Aligning capability development with operational needs and emerging technologies
• Scaling autonomous systems to support future Air Force force design and readiness

• Deploy autonomous AI workflows that retrieve, analyze, and synthesize mission documents
• Accelerate decision-making with citation-backed, auditable AI insights that analysts can trust
• Scale intelligence across missions and data sources while keeping humans in the loop

• Aligning Autonomy with Naval Operational Priorities: AI to support distributed maritime operations, unmanned integration, and decision-making at the tactical edge
• Enterprise-Level Technology Strategy: driving coordination across platforms, mission systems, and digital infrastructure to enable scalable, secure autonomous capabilities
• Modularity, Data, and Interoperability: open architecture, data-driven development, and multi-domain integration in achieving long-term autonomy goals across the fleet

• Challenges of Transparent battlefield and emerging roles for autonomous systems.
• ARL research in adaptive behaviors, advanced mobility, and physical AI to enable capabilities of autonomous & resilient tactical maneuver, swarm, and ISR
• Unique facilities, laboratory infrastructure, and resources along with success stories of transitions and impact.
• Opportunities for industry and academic partnerships to accelerate innovation and transition of research

• Reducing friction between frontier-tech founders and defense decision-makers
• Accelerating autonomy innovation through capital access and ecosystem design
• Creating trusted spaces for collaboration across government, investors, and operators
• Strengthening America’s competitive edge by aligning policy insight with technological advancement

• Enabling real-time decision superiority through next-generation AI and machine learning research
• Bridging autonomy, data fusion, and edge computing to support warfighters in contested environments
• Understanding risk, trust, and control: the human-machine teaming dynamic in high-stakes missions
• Accelerating transition from research to reality—delivering scalable autonomy for DoD operations

• How can defense organizations bridge the gap between breakthrough research, commercial innovation, and the operational deployment of autonomous capabilities?
• What technical, operational, and organizational factors are required to build trust in AI-enabled autonomous systems operating in mission-critical environments?
• How can autonomous systems be scaled across defense missions while ensuring resilience in contested, degraded, and data-constrained environments?
• What new models of collaboration between government, academia, and industry are needed to accelerate innovation and field next-generation autonomous capabilities?

• Modernizing personnel management with AI and automation to improve speed, accuracy, and adaptability across the Total Force
• Advancing autonomous tools for workforce analytics, talent optimization, and predictive readiness
• Reducing administrative burden and enabling digital-first service delivery through intelligent systems
• Aligning manpower strategies with emerging mission demands and joint force transformation initiatives

• Aligning autonomy development with platform and weapons portfolios for future joint warfighting advantage
• Accelerating integration of modular, cyber-resilient autonomous systems across air, ground, and maritime platforms
• Leveraging digital engineering and mission thread analysis to field capabilities with greater speed, safety, and flexibility
• Building resilient infrastructure to ensure autonomy operates in contested, degraded, and cyber-threatened environments

• How is your organization designing autonomous systems to meet modularity, interoperability, and upgradeability demands across services?
• What does “trustworthy autonomy” mean from an industry perspective — and how are you addressing testing, validation, and operator confidence?
• In light of initiatives like Replicator, how is industry preparing to meet DoD’s demand for speed, scale, and attritable platforms?
• How can government and industry better collaborate to reduce integration friction, accelerate acquisition timelines, and deliver capabilities that meet operational needs?

• Aligning Autonomy with Naval Operational Priorities: AI to support distributed maritime operations, unmanned integration, and decision-making at the tactical edge
• Enterprise-Level Technology Strategy: driving coordination across platforms, mission systems, and digital infrastructure to enable scalable, secure autonomous capabilities
• Modularity, Data, and Interoperability: open architecture, data-driven development, and multi-domain integration in achieving long-term autonomy goals across the fleet

• Exploring frameworks for integrating emerging technologies into the defense acquisition ecosystem with speed and accountability
• Lessons learned from leading cross-functional innovation initiatives that align policy, workforce development, and mission outcomes
• Strategies for scaling AI literacy and readiness across acquisition and operational communities
• Human-centered design and modern learning models for cultural and institutional transformation within the DoD

• How is autonomy being used to modernize defense support functions like personnel, procurement, and logistics?
• What lessons have been learned from deploying AI and automation tools at the enterprise level?
• How do open architectures, shared data environments, and enterprise cloud enable these capabilities?
• Where are the highest-impact areas for reducing manual workload or increasing responsiveness in support operations?
• How can the Department better coordinate across services and agencies to accelerate enterprise autonomy adoption?

• Bridging Commercial Innovation and National Security Needs:
• Enabling Autonomy Through Challenge- Based Acquisition: Leveraging SBIR/STTR, STRATFI/TACFI, and open topic models to de-risk emerging technologies and transition autonomous capabilities into operational programs.
• Partnering for Scalable Impact: collaboration with startups, academia, and traditional industry to develop resilient, intelligent space systems in support of contested domain operations

• Enabling real-time decision superiority through next-generation AI and machine learning research
• Bridging autonomy, data fusion, and edge computing to support warfighters in contested environments
• Understanding risk, trust, and control: the human-machine teaming dynamic in high-stakes missions
• Accelerating transition from research to reality—delivering scalable autonomy for DoD operations

• Trustworthy AI Initiative
• Engineering methods to enable trusted behavior using untrusted or partially trusted AI components
• Exploring systems engineering frameworks for uncertainty, failure modes, and explainability in AI-enabled systems
• Evaluating the broader implications for acquisition, lifecycle management, and test & evaluation of autonomous and AI-integrated defense platforms

• Unpacking the APFIT Program’s mandate to bridge the gap between R&D and fielding for autonomous and AI-enabled systems.
• Lessons learned from recent successful transitions of autonomous technologies into operational units.
• Key criteria and evaluation processes used to select APFIT-funded projects- what autonomy vendors need to know.
• Strategies for non-traditional vendors to align with DoD priorities and overcome barriers to entry.
• How APFIT is supporting broader defense innovation goals by scaling dual-use tech and streamlining acquisition timelines
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• Research Priorities in Robotic Ground Systems: advancing core autonomy technologies—from perception and mobility to AI-driven decision-making to support the Army's NGCV portfolio
• Human-Machine Teaming and Trust at the Tactical Edge: Engineering approaches to enable reliable, effective interaction between soldiers and autonomous systems in complex, contested environments.
• Path to Fielding: From Lab to Formation:
  Bridging the gap between applied research, experimentation, and operational relevance to deliver scalable robotic combat capabilities

• Present advancements in autonomous ground systems capable of operating in GPS-denied, communication-constrained, and cluttered environments
• Research on tactile sensing, proprioception, and adaptive control for complex manipulation and terrain navigation
• Army priorities in enabling human-robot teaming for contested logistics, subterranean missions, and forward-deployed autonomy.
• Lessons learned from field experimentation and simulation efforts under Army Futures Command's robotics modernization strategy

• Ensuring performance assurance for autonomous and AI-enabled naval systems.
• Explore measurement science innovations supporting the reliability, safety, and interoperability of autonomous platforms in contested environments.
• Discuss current initiatives to standardize calibration protocols across emerging uncrewed and intelligent systems.
• Share Navy METCAL’s strategic vision for advancing test and evaluation frameworks aligned with autonomy-driven capability development.

• Advancing space domain awareness, dynamic tasking, and real-time threat response with autonomous solutions
• Integrating AI/ML into space operations, including satellite constellations, ISR, and on-orbit decision-support.
• Exploring challenges and opportunities in deploying trusted autonomy in contested space environments.
• Strategic priorities for autonomy-enabled resilience, joint interoperability, and future force design in multi-domain operations

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.