Planetary Resources is embarking on the world’s first commercial deep space exploration mission. The purpose is to identify and unlock the critical water resources necessary for human expansion in space.
Sourcing water is the first step to creating a civilization in space. Water is used for life support functions and can also be refined into rocket propellant. The initial mission will identify the asteroids that contain the best source of water, and will simultaneously provide the vital information needed to build a commercial mine which will harvest water for use in space.
MouseAGE is working to develop the first photographic biomarker of aging in mice to help validate potential anti-aging interventions, save animal lives, and greatly speed up the pace of longevity research.
To create it we will harness the power of an area of artificial intelligence called Machine Learning, and in particular Deep Learning.
Machine Learning, where a computer system can train itself to become better at a task without explicit programming, has already showed great performance in areas such as human facial recognition, autonomous driving, medical image processing, recommendation engines and many others. While these results are powerful, building up the necessary Neural Networks, or algorithms inspired by the human brain, requires a large dataset of images to use for training: thousands of them.
Due to this, the first stage of the project will be to build a simple instrument for data collection, implemented in a mobile application. This will be distributed among numerous mouse breeding facilities and research universities all over the world to rapidly collect and properly annotate image data for analysis.
Like so many other new technologies, however, AI has generated lots of unrealistic expectations. We see business plans liberally sprinkled with references to machine learning, neural nets, and other forms of the technology, with little connection to its real capabilities. Simply calling a dating site “AI-powered,” for example, doesn’t make it any more effective, but it might help with fundraising. This article will cut through the noise to describe the real potential of AI, its practical implications, and the barriers to its adoption.
What it can — and cannot — do for your organization.
Stephen Paddock’s brother has speculated, “something went wrong in his head.” David Eagleman asks, what precisely was it? We know little about Paddock but quite a bit about biological factors that can be associated with violent behavior, Eagleman says”
“David Eagleman directs the Center for Science and Law and is an adjunct professor of neuroscience at Stanford University. He is the writer and presenter of the PBS series, “The Brain with David Eagleman,” and the author of the New York Times bestseller, “Incognito: The Secret Lives of the Brain.” The opinions expressed in this commentary are his own.”
‘In the wake of the mass shooting in Las Vegas, Stephen Paddock’s brother Eric speculated, “something went wrong in his head.” But what precisely was it?”
Kevin J. Ryan is a staff writer for Inc. He has written for ESPN The Magazine and the Long Island Press and contributed to Mental Floss. He lives in Queens, New York.
