Information Processing Techniques Office Office-Wide
Multiple awards.
Abstract Due Date: June 22, 2027 at 2:00 PM
Proposal Due Date: By Invitation Only, a due date will be provided in the Invitation to Proceed.
The BAA Coordinator for this effort may be reached at: HR001126S0011@darpa.mil
DARPA/ IPTO
ATTN: HR001126S0011
675 North Randolph Street
Arlington, VA 22203-2114
This Broad Agency Announcement (BAA) seeks revolutionary research ideas for topics not being addressed by ongoing I2O programs or other published solicitations.
Potential proposers are highly encouraged to visit the I2O technical office page (https://www.darpa.mil/about/offices/i2o) to view current and upcoming I2O programs and solicitations in order to avoid proposing efforts that duplicate existing activities or that are responsive to other published I2O solicitations.
The Information Processing Techniques Office (IPTO) creates technological surprise through
groundbreaking information science, technology development, and the delivery of fundamentally
new information capabilities for national security. The office's current portfolio is centered on
three primary thrust areas:
AI Innovation and Execution
We envision vastly more energy-efficient and assured artificial intelligence (AI) systems
to advance asymmetric capabilities at the edge of the network and to provide trustworthy,
understandable AI to warfighters where and when they need it. We also seek to mitigate
risks of misalignment of machine actions and human interests.
Inherent Security and Privacy
We seek to create a new generation of systems that are inherently secure and inherently
private, together with security and privacy tools that are more effective and more adaptable
– both in the moving-target and reactive senses – than current solutions. We aim to develop
more trustworthy and resilient systems based on the fundamental principles of the cyber
networking, computing, and storage environment, and to create an asymmetric advantage
in cyberspace.
Resilient Megasystems
We aim to develop machine-derived abstractions and models that expose the governing
principles of highly complex and interconnected systems – like supply chains and power
grids – to identify hidden systemic risks and emergent properties, and to enable the precise
targeting of interventions and the proactive assurance of mission-critical functions.