Lifeboat Foundation: Safeguarding Humanity
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We are using A.I. and Computer Vision Techniques to Determine Age and Assess the Effect of Therapies Against Aging in Mice, Increasing the Pace of Life Extension Research. Please subscribe, share, and fund our campaign today! ►Campaign Link: https://www.lifespan.io/mouseage ►Subscribe: https://www.youtube.com/user/LifespanIO?sub_confirmation=1

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.

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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.

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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?”

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Plenty of obstacles, no regulations, and nobody in a huge rush—sounds like an ideal proving ground for autonomous cars. Self-driving startup Voyage certainly thinks so, because it’s just kicked off a trial at the Villages Golf and Country Club, a 4,000-resident retirement community with 15 miles of roads located in San Jose, California.

Speeds on the roads at the Villages are limited to 25 mph, but most autonomous car tests in cities and suburbs don’t go a great deal faster than that anyway. Still, the roads are full of the same kinds of obstacles you’d find in most suburbs: pedestrians, animals, golf buggies. Okay, maybe the golf buggies are a new hazard to most driverless cars.

But the biggest draw for the move is secrecy. As the New York Times points out, because the community is a private residence, Voyage doesn’t need to comply with the whims of regulators, which means it can try out new things without anyone finding out. And perhaps it can even explore using entirely driver-free vehicles sooner than it could on real roads.

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