Peter Foytik has been a modeling and simulation professional for 8 years at the Virginia Modeling Analysis and Simulation Center (VMASC). Peter has a bachelor’s degree in computer science and a master’s of science in modeling and simulation. With a background in computer science, initial expertise has been in software development of support tools for
Topic: Artificial Intelligence (AI)
Machine learning (ML) may well be The Next Big Thing, but it has yet to register in mainstream enterprise adoption. While breathless prognosticators proclaim 50% of organisations lining up to magically transform themselves in 2017 with ML, more canny observers put the number closer to 15%. And that's being generous.
Powerful machine-learning techniques are making it increasingly easy to manipulate or generate realistic video and audio, and to impersonate anyone you want with amazing accuracy.
Over the last five years or so, Machine Learning, a type of AI, has been a quickly rising tide that’s now starting to permeate nearly every corner of technology.
In one of the most significant tests of autonomous systems under development by the Department of Defense, the Strategic Capabilities Office, partnering with Naval Air Systems Command, successfully demonstrated one of the world’s largest micro-drone swarms at China Lake, California.
The Standard Wargame Integration Facilitation Toolkit (SWIFT), an Office of the Secretary of Defense, Cost Assessment and Program Evaluation (OSD CAPE) product, provides a computer environment that supports Department of Defense (DoD) wargaming. SWIFT complements, but does not substitute for good wargaming practices. Deputy Secretary of Defense Robert Work
Introduction The Air Force Research Laboratory has taken steps to revitalize wargaming across its Enterprise to evaluate the military utility of innovative technology concepts in combat. The integration of Modeling and Simulation (M&S) to improve the analytical rigor of wargames is a fundamental part of this effort. In a period of growing strategic
The robot is envisioned as a 1.2-meter tall humanoid, possibly covered with synthetic skin, with two (or more) arms ending in hands or grippers, and wheeled treads for locomotion. Cameras on its head would stream high-definition video to its simian operator, while other sensors might include infrared and ultraviolet imaging, GPS, touch, proximity and strain