Is AI Really a Threat to Humanity?
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.
Capability Boost: Trials Demonstrate Enhanced ViDAR/ScanEagle Package
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.
Google Ponders the Shortcomings of Machine Learning
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.
AI-Based Virtual Tutors – The Future of Education?
“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.
Glimpse: How Electronic Tattoos Will Change The World — And Ourselves
Scientists have developed a means to 3D print electronics onto the skin as a form of wearable technology akin to a tattoo. It is proposed that further development of this technology will allow these tattoos to monitor our vitals, and feed us personalized health advice in real time.
Artificial intelligence system uses transparent, human-like reasoning to solve problems
This article describes a method by which a computer can recognise objects using Transparency by Design Network (TbD-Net) developed at the MIT Lincoln Laboratory. Researchers have used human-like reasoning to develop an algorithm which they claim can outperform other visual recognition software and algorithms because humans can view its reasoning process to determine where and how it is making mistakes.
Why Would Prosthetic Arms Need to See or Connect to Cloud AI?
This summary of a lecture by Microsoft’s CTO discusses the integration of sensor technology and cloud based AI in low cost, 3D printed prosthetic arms.
Neuro Embodied Design: How We’ll Become Cyborgs and Extend Human Potential
Humans will soon have new bodies that forever blur the line between the natural and synthetic worlds, says bionics designer Hugh Herr. In an unforgettable talk, he details "NeuroEmbodied Design," a methodology for creating cyborg function that he's developing at the MIT Media Lab, and shows us a future where we've augmented our bodies in a way that will redefine human potential -- and, maybe, turn us into superheroes. "During the twilight years of this century, I believe humans will be unrecognizable in morphology and dynamics from what we are today," Herr says. "Humanity will take flight and soar."
Queryable Earth: A Searchable database of Earth
What if you could search the surface of the Earth the same way you search the internet? Will Marshall and his team at Planet use the world's largest fleet of satellites to image the entire Earth every day. Now they're moving on to a new project: using AI to index all the objects on the planet over time -- which could make ships, trees, houses and everything else on Earth searchable, the same way you search Google. He shares a vision for how this database can become a living record of the immense physical changes happening across the globe. "You can't fix what you can't see," Marshall says. "We want to give people the tools to see change and take action."