The Air Force Research Laboratory’s (AFRL) Autonomy Capability Team (ACT3) is an AI Special Operations organization who’s mission is to Operationalize AI at Scale for the Air Force.  ACT3 is an integrated team with the blue sky vision of an academic institution; the flexibility of an AI startup; and the discipline of a production development company.  We integrate the world’s best under one roof.  Here’s what our colleagues have to say about our ACE Platform:

  • Tom Mitchell, Carnage Mellon University - "…the system architecture and cognitive designs embodied in the USAF ACT3 platform are fundamental to the future of machine learning and with key attention to continuous learning in machine"​

  • Yann LeCun New York University, Director of AI at Facebook, and Turing Award Laureate - "Deep Learning is an exceptional mechanism addressing many research questions in machine learning; it is a computational tool for many applied problems, but it is not the “tool” for everything… what it is necessary to understand is how many different types of “computational tools” work together… this is exactly what ACT3 is doing… dynamically combining various intelligent software agents to learn and reason about various classes of real-world problems… ACT3 is advancing critical machine learning and AI research"

  • Marvin Minsky and Patrick Winston MIT - "Serious advances in the science of AI will require an understanding of the integration of 100s of sophisticated learning and reasoning systems… the ACT3 design provides a creditable means to achieve such an integration… its architecture and multi-representations of knowledge and data extend the state-of-the-art in multi-strategy reasoning and learning"

    • Minsky and Winston both concur that the ACT3 work addresses a famous Minsky quote: "You don't understand anything until you learn it more than one way"

  • Eric Horvitz, Director of AI at Microsoft - "…with the compelling advances in Deep Learning, Reinforcement Learning and many other techniques… the work by the ACT3 team serves the AI/Machine Learning community with significant breakthroughs to integrate various computational AI techniques, thereby obtaining new levels of performance in machine learning… and most critically, engineering the AI scaling challenges due to the dynamic architecture of the ACT3 platform"

  • Vladimir Vapnik and Rauf Izmailov, Columbia University - "The ACT3 engineering is addressing one of the critical concerns, that being, applying context during learning in a situation… such work requires multiple types of representations used in distinct types of diverse reasoning/learning… the Vapnik issue is, without context, the future of machine learning will reach an impass… ACT3 is obtaining a new paradigm for integrated diverse learning machines working in collaboration… ACT3 provides a dynamic means for many different AI systems to work together providing different perspectives of context…  this is the machine learning path to take…"