Autonomy in Defense schedule

• Integrating autonomous capability to extend the reach, survivability, and combat power of manned platforms in contested environments
• Capability Requirements and Mission Sets: An overview of the Air Force’s prioritized roles for the F-47 and autonomous wingmen — from sensing and strike to electromagnetic warfare and decoy operations — and how requirements are shaping platform design
• Balancing Cost, Modularity, and Mass: supporting a scalable force structure through attritable and adaptable design, aligned with strategic goals for operational tempo and risk distribution in peer conflict scenarios

• Driving rapid development and integration of autonomous and AI-enabled tactical systems to enhance operator effectiveness in denied or contested environments
• Leveraging modular open systems architecture (MOSA) and agile acquisition strategies to accelerate fielding of mission-ready capabilities
• Enhancing data-driven decision-making and situational awareness at the tactical edge through multi-domain ISR and secure communications
• Aligning emerging autonomy technologies with USSOCOM’s evolving operational requirements and mission adaptability

• What role does autonomy play in force design strategy over the next 5–10 years? How are you prioritizing autonomy within current modernization efforts?
• What are the biggest operational challenges you face when integrating autonomy into existing mission sets?
• How are you managing the balance between speed of adoption and long-term sustainment?
• How do you see Joint and Cross-Domain interoperability being addressed through autonomy? What is needed to ensure seamless integration between services?
• How are your commands working with industry, DIU, and the innovation ecosystem to accelerate capability delivery?
• Looking ahead to peer conflict scenarios, particularly in the Indo-Pacific, what autonomous capabilities will be most critical to deterrence and survivability?

• Automating digital environments and leveraging data for enhanced decision-making
• Driving Strategic Advantage Through Emerging Technology: accelerating the development and fielding of autonomous systems to outpace competitors and close operational gaps
• Lessons from the Replicator initiative and next steps for rapidly deploying attritable, AI-enabled platforms across domains
• Enabling the Tech-to-Force Pipeline: Bridging the divide between prototyping and warfighter delivery by aligning innovation pathways with acquisition, test, and joint integration priorities

• Outlining the Army’s innovation priorities and pathways for integrating emerging technologies into modernization efforts.
• Successful models for cross-sector collaboration with startups, academia, and industry.
• Agile experimentation and rapid prototyping in accelerating capability development.
• Addressing risk, scalability, and sustainment challenges in unmanned and autonomous tech adoption

• What does the “user” experience look like at echelon?
• Imperative to get training right through “sets and reps”. 
• Testing and harnessing MOSA and MBSE
• Opportunities for fusion with platforms, AI, and energetics

• USMC’s evolving strategy for integrating intelligent robotics and autonomous systems across littoral and distributed operations.
• Share current IRAS initiatives aimed at enhancing mobility, reconnaissance, and sustainment in contested environments.
• Examine the operational trade-offs between autonomy, payload, and survivability for USMC mission sets.
• Discuss cross-Service collaboration and experimentation under the Navy-Marine Corps team to accelerate fielding of unmanned ground and aerial systems

• Integrating autonomous and AI-enabled capabilities into force design.
• Assessing autonomy’s support of Army 2030 priorities—lethality, survivability, and speed—across multi-domain operations.
• Advancing human-machine teaming in training, doctrine, and future operational concepts.
• Addressing challenges and opportunities in aligning autonomy innovation with scalable fielding and soldier readiness

• Enhancing situational awareness, precision navigation, and operational planning in contested environments through autonomous applications
• Integrating AI/ML into terrain analysis, elevation modeling, and data fusion for real-time mission support
• Geospatial data in enabling autonomous maneuver, target recognition, and route optimization across complex terrains
• Delivering high-fidelity geospatial products at the tactical edge

• Embedding responsible AI principles into the lifecycle of GEOINT-enabled autonomous and analytic systems.
• Governance frameworks and risk mitigation strategies for deploying AI in high-consequence defense missions.
• Aligning AI system development with ethical, legal, and operational imperatives.
• The path forward for secure, transparent, and accountable AI integration across the IC and DoD enterprise

• Unpacking the Navy’s vision for disruptive innovation and how the DCO is driving rapid tech transition across domains
• Bridging the gap between emerging capabilities and operational relevance: lessons from early prototyping and field experimentation
• Integrating autonomy, AI, and advanced sensing into naval force design: opportunities and challenges
• Fostering partnerships across DoD, industry, and academia to scale game-changing technologies for maritime advantage

• Explore NIWC Pacific’s priorities for advancing AI-enabled autonomous systems in the maritime domain
• Examine approaches for ensuring reliability, trust, and mission alignment in naval autonomy
• Discuss integration of uncrewed systems into distributed C2 architectures and operational concepts
• Share insights from recent joint demonstrations and cross-service experimentation initiatives

• 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.