LTCOL Jasmin Diab uses the example of her recent work in supporting the International Atomic Energy Agency to ask us to consider the future of machine learning and its ability to support military decision making.
Our interaction with the technological world today is changing rapidly. We are no longer limited by screens or even reality as we knew it.
The TED Talk examines the origins of Cognitive Bias, its advantages, drawbacks and challenges with Biased AI. The solution might lie within ourselves.
The F-35 heralds a revolution in how the ADF will fight, as units learn to integrate with 5th Generation technologies and operate as a network, leveraging stealth and information fusion. This article explores the ‘night versus day’ change, which opens the door for related opportunities including man-machine teaming and the ‘loyal wingman’ concept.
On science fiction, JPME and thinking about future military institutions.
This article comments on the impact of Cognitive Bias, found in AI systems, on our future. It provides the examples of the biased systems and asks the fundamental questions on our strategy going forward. The article is suitable for all the levels of JMPE continuum, and will be of interest to those particularly interested in Cognitive computing or Artificial Intelligence.
Kurzweil Network is a small format digest — featuring hand-picked, specially curated stories and resources. This website is also home to the permanent collection of writings and commentary by Ray Kurzweil. It follows progress in the science and technology landscape, with topics including biology, nanotech, materials science, electronics, computation, artificial intelligence, robotics, web, pattern recognition, virtual reality, and prosthetics + body augmentation.
This article from Jane’s International Defence Review discusses the use of Visual Detection and Ranging (ViDAR) technology on the ScanEagle unmanned aerial system (UAS) platform to provide detection capabilities comparable to radar using Electrooptical (EO) and Infra Red (IR) sensors.
This article explores some of the important aspects of AI and its subfields, including a brief history of its development. It defines key AI terminology and language and set a useful start-state for further targeted study.
This article discusses Google’s AI research project Google Brain and DeepMind and their explanation for why, despite advances in computing power, machine learning still lags behind human cognitive skills, particularly the ability to “generalize beyond one’s experience”. The article describes the use of graphs of relationships to replicate neural networks as a potential area of future advancement in machine learning and artificial intelligence.
“This blog post is about the UC Berkeley Virtual Tutor project and the speech recognition technologies that were tested as part of that effort. We share best practices for machine learning and artificial intelligence techniques in selecting models and engineering training data for speech and image recognition.