DEPT OF THE ARMY USA Tender

Updated Attachment To Reflect A Change To Page 40, Removing The Incorrect Hrpo And To Highlight The Email Address For Submissions,ai2c_baa_submissions@army.mil Throughout The Attachment. updated Attachment To Reflect Title Change From W52p1j-23-b-ai2c To W519tc-24-s-ai2c. see Attached Baa For Full Details. this Broad Agency Announcement (baa), For The Army Artificial Intelligence Integration Center (ai2c), Is Issued Under The Provisions Of Paragraph 6.102(d)(2) And 35.016 Of The Federal Acquisition Regulation (far), Which Provides For The Acquisition Of Basic, Applied, And Advanced Research And That Part Of Development Not Related To The Development Of A Specific System Or Hardware Procurement. This Will Be Done Through The Competitive Selection Of Proposals, And 10 U.s.c. 4001, 10 U.s.c. 4021, And 10 U.s.c. 4022, Which Provide The Authorities For Issuing Awards Under This Announcement For Basic, Applied, And Advanced Research. Proposals Submitted In Response To This Baa And Selected For Award Are Considered To Be The Result Of Full And Open Competition And In Full Compliance With The Provisions Of Public Law 98-369, "the Competition In Contracting Act Of 1984" And Subsequent Amendments. the Army Artificial Intelligence Integration Center (ai2c) Is Seeking Artificial Intelligence Research And Development Whitepapers And Proposals In Support Of New Technologies And Translational Research-based Approaches That Support The Identification, Alignment, And Exploitation Of Basic, Applied, And Advanced Research. this Baa May Be Used To Award Far Based Instruments (e.g., Procurement Agreements) Or Instruments Not Subject To The Far (e.g., Grants, Cooperative Agreements, Technology Investment Agreements, And Other Transactions). Those Instruments Not Subject To The Far May Be Referred To As Assistance Agreements In This Baa. Ai2c Will Consider A Wide Range Of Funding Constructs Which Might Include, But Are Not Limited To, Government Funding, Cost Sharing, In-kind Labor Or Facility Sharing By All Parties, Or Any Other Allowable Mechanism. Applicants May Propose Cost Sharing Approaches, But They Are Not Required. Ai2c Envisions Opportunities To Engage In Other Types Of Collaboration Agreements Where No Funds Are Exchanged, Such As Cooperative Research And Development Agreements (cradas) Which Are Negotiated Separately From This Baa. to Be Eligible For An Award Under This Announcement, A Prospective Awardee Must Meet Certain Minimum Standards Pertaining To Financial Resources And Responsibility, Ability To Comply With The Performance Schedule, Past Performance, Integrity, Experience, Technical Capabilities, Operational Controls, And Facilities. In Accordance With Federal Statutes, Regulations, And Department Of Defense (dod) And Army Policies, No Person On Grounds Of Race, Color, Age, Sex, National Origin, Or Disability Shall Be Excluded From Participation In, Be Denied The Benefits Of, Or Be Subjected To Discrimination Under Any Program Or Activity Receiving Financial Assistance From The Army. Areas Of Interest 1. Autonomous Platforms the Army Is Interested In Research In Autonomous Ground And Air Vehicles, Which Must Operate In Open, Urban, And Cluttered Environments. Robotics And Autonomous Systems Regardless Of Their Missions Require Similar Concepts And Technologies Including: ability To Move In Cluttered, Irregular, Urban, And Underground Environments. ability To Move Effectively In Contested Environments And Survive Attacks. technologies To Enable Low Electromagnetic And Physical Profiles. architectures To Enable Autonomous Learning And Adaptation Under Dynamic Conditions. sensing Methods To Detect Obscured And Small Targets And To Characterize Terrain Obstacles. autonomous Ground And Air Structures, Propulsion, And Mobility Components. technologies To Significantly Reduce Logistical Burdens And/or Make Them Autonomous. ability To Have Multiple Land And Air-based Platforms Collaborate To Accomplish Complex Goals Autonomously. 2. Artificial Intelligence And Machine Learning Algorithms (ai/ml) the Army Is Interested In Core Algorithmic Improvements Such As: scaling Machine Learning Methods To Operate On Larger Data Sets In Shorter Periods Of Time And/or With Reduced Computation, Memory, And/or Power Requirements. improving The Data Efficiency Of Learning Algorithms (e.g., Low-shot, Zero- Shot Learning). developing Foundation Models Across Multiple Modalities Such As Language, Vision, And Segmentation. adapting Existing Foundation Models To Novel Tasks. improving Methods For Collecting, Labeling, Managing, And Tracking Data And The Models Learned From Them. 3. Ai/ml Decision Support the Army Is Interested In Research On Ai Algorithms And Systems To Improve Decision Making Across All Echelons Including: core Reinforcement Learning, Game Theoretic, Optimal Control Algorithms. algorithms For Improved Online, Operational Decision Making. algorithms For Improved Offline Strategic Planning Including Tactics And Portfolio Optimization Of Assets. algorithms For Increased Autonomy And Speed In Decision Making. 4. Human-ai Integration the Army Is Interested In Ai/ml Research In Areas Which Can Reduce The Cognitive Burden On Humans And Improve Overall Performance Through Human-machine Integration. Ai/ml Research Is Needed In Areas Such As: speech And Language Algorithms That Support More Efficient Human-machine Integration. algorithms That Raise The Level Of Autonomy In Systems (i.e., Increase The Number And Size Of Tasks That Can Be Accomplished Without Human Input And/or Reduce The Level Of Details Required In Human Commands To Machines). methods To Process And Summarize Large Amounts Of Data For Human Analysis. robust And Rigorous Methods For Evaluating The Outputs Of Complex Ai Systems. methods For Understanding And Explaining Ai/ml Results And The Uncertainty Of Those Results. understanding The Impacts Of Ai/ml On Human Decision Making. ethical Considerations For Human-machine Integrated Formations In High Risk And Complex Environments. quantitative Approaches To Measure Ethical Compliance Of Ai Systems. methods To Train Users And Developers At Various Technical Skill-levels To Interact And Use Ai And Ml More Effectively. techniques To Investigate Human And Non-human Behavior And Interactions In Various Online Social Settings. 5. Synthetic Environments the Army Is Interested In Research That Enables Improved Situational Awareness And The Visualization And Navigation Of Large Data Sets To Enhance Operational Activities And Training And Readiness. Research Is Needed In The Visualization Of Data In Following Areas: novel Visualization And Synthetic Environment Approaches To Enable Improved Training synthetic Environments And Networked Instrumentation Approaches For Virtual-live Validation Of Concepts And Prototypes 6. Distributed Ai the Army Is Interested In Effectively Leveraging Modern Ai And Ml Techniques For Both Enterprise And Tactical Applications. Research Is Needed In The Areas Related To The Following: methods For Governing A Large Portfolio Of Distributed Ml Models. algorithms For Efficiently Leveraging Hardware Across A Large, Heterogeneous Network Of Enterprise And Tactical Computer Systems For Various Ai And Ml Tasks. methods For Effective Multi-agent Collaboration And Multi-agent Systems. techniques To Attack And Compromise Ai And Ml Systems. techniques And Best Practices For Defending Ai And Ml Models And Infrastructure From Attacks. improve Ml Performance Of Inference And Training On Small, Rugged Edge Devices. cyber Protection Technologies, Methodologies, And Concepts To Protect Army Systems, Especially In The Context Of Distributed Systems. 7. Underpinning Methodologies the Army Is Interested In Methodologies, Frameworks, Tools, Facilities, Techniques, And Experimentation Concepts, Which Underpin And Enable Advanced Research And Development, Including Those Which Enhance The Following: collection, Standardization, Transformation, And Maintenance Of Data To Focus Research And Validate Concepts. rapid Modeling, Development, And Assessment Of Technologies Across Widely Distributed Research Teams. integrate Innovative Technology Applications Into Current Or Future Warfighting Systems, Applications, And Analysis Systems To Assess The Potential Operational Effectiveness Of Novel New Technology Elements. frameworks That Integrate Testing And Evaluation Into The Artificial Intelligence Workflow. 8. Special Topics as A Part Of This Baa, Ai2c Will Post Specific Areas With Strong Potential For Funding As An Amendment To This Baa On Sam.gov. These Topics Will Generally Have Clear Deadlines For Submission And May Have Other Specific Preparation Guidelines.