Join CSIAC Tuesday, January 26 from 1100 to 1200 EST for a webinar presentation titled, “Agile Condor: Supercomputing at the Edge for Intelligent Analytics.” Please register in advance at: https://www.anymeeting.com/PIID=EF59DF86894D3E Future military conflicts will take place in contested environments where remote sensors deployed in the field will
Topic: Machine Learning (ML)
ADELPHI, Md. -- Multi-domain operations, the Army's future operating concept, requires autonomous agents with learning components to operate alongside the warfighter. New Army research reduces the unpredictability of current training reinforcement learning policies so that they are more practically applicable to physical systems, especially ground robots.
The Autonomous Vehicle Vision 2021 (AVVision’21) workshop aims to bring together industry professionals and academics to brainstorm and exchange ideas on the advancement of visual environment perception for autonomous driving. This one-day workshop will include regular paper presentations and invited speakers to present the state of the art as well as the
Future military conflicts will take place in contested environments where remote sensors deployed in the field will employ advanced artificial intelligence and machine learning technology to reason about the battlespace in the absence of connectivity to manned ground stations. The Air Force Research Laboratory has developed Agile Condor, a flexible airborne
Mark Barnell received the B.S. degree in optical engineering from the University of Rochester, Rochester, N.Y. in 1987, and the M.S. degree in computer science from SUNY Polytechnic Institute, Utica, N.Y., in 2000. He is a Senior Computer Scientist with the U.S. Air Force Research Laboratory, High Performance Computing Systems Branch (AFRL/RITB),
Join CSIAC Wednesday, August 12th, at 1100 EDT for our next webinar presentation titled "A Fistful of Data, or the Good, Bad and Ugly of Adversarial Machine Learning." Please register in advance for the webinar at: https://www.anymeeting.com/PIID=EF52D880844A3F This webinar provides an overview of Adversarial Machine Learning (AML), its relationship to
This webinar provides an overview of Adversarial Machine Learning (AML), its relationship to Generative (Deep) Learning, and ways to view AML as a potential enabler for deploying more comprehensive system-level Machine Learning capabilities. The basic ideas driving AML and the system-level architecture needs of an effective integrated ML capability are
If AI is really going to make a difference to patients we need to know how it works when real humans get their hands on it, in real situations.
Machine Learning (ML) appears to be the ubiquitous go-to solution for a great many modern problems across many domains. But what is really under the hood of a typical ML solution? And, why are so many problems suddenly becoming good ML candidates? This webinar explores non-mathematically the foundational aspects of ML and how they add up to a satisfactory
The Trump administration is proposing new rules to guide future federal regulation of artificial intelligence used in medicine, transportation and other industries.