Lifeboat Foundation

April 5 (UPI) — The U.S. Defense Advanced Research Projects Agency has completed a round of testing for its vertical takeoff and landing X-Plane program.

The agency began testing for the program in March 2016 using sub-scale aircraft developed and fabricated by Aurora Flight Sciences. The platform is comprised of 24 electric ducted fans, 18 of which are distributed within the main wings. The remaining six are placed in the canard surfaces.

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A team of researchers has developed artificial synapses that are capable of learning autonomously and can improve how fast artificial neural networks learn.

Developments and advances in artificial intelligence (AI) have been due in large part to technologies that mimic how the human brain works. In the world of information technology, such AI systems are called neural networks. These contain algorithms that can be trained, among other things, to imitate how the brain recognizes speech and images. However, running an Artificial Neural Network consumes a lot of time and energy.

Now, researchers from the National Center for Scientific Research (CNRS) in Thales, the University of Bordeaux in Paris-Sud, and Evry have developed an artificial synapse called a memristor directly on a chip. It paves the way for intelligent systems that required less time and energy to learn, and it can learn autonomously.

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It isn’t easy to capture the best shots in a golf tournament that is being televised. And that’s why IBM is applying the artificial intelligence of its Watson platform to the task of identifying the best shots at The Masters golf tournament.

For the first time at a sporting event, IBM is harnessing Watson’s ability to see, hear, and learn to identify great shots based on crowd noise, player gestures, and other indicators. IBM Watson will create its own highlight reels.

With 90 golfers playing multiple rounds over four days, video from every tee, every hole, and multiple camera angles can quickly add up to thousands of hours of footage.

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Deep learning owes its rising popularity to its vast applications across an increasing number of fields. From healthcare to finance, automation to e-commerce, the RE•WORK Deep Learning Summit (27−28 April) will showcase the deep learning landscape and its impact on business and society.

Of notable interest is speaker Jeffrey De Fauw, Research Engineer at DeepMind. Prior to joining DeepMind, De Fauw developed a deep learning model to detect Diabetic Retinopathy (DR) in fundus images, which he will be presenting at the Summit. DR is a leading cause of blindness in the developed world and diagnosing it is a time-consuming process. De Fauw’s model was designed to reduce diagnostics time and to accurately identify patients at risk, to help them receive treatment as early as possible.

Joining De Fauw will be Brian Cheung, A PhD student from UC Berkeley, and currently working at Google Brain. At the event, he will explain how neural network models are able to extract relevant features from data with minimal feature engineering. Applied in the study of physiology, his research aims to use a retinal lattice model to examine retinal images.

https://www.youtube.com/watch?v=fzcLsCXR8qE&feature=share

Ray Kurzweil is probably the most qualified individual to talk about the future of technology. He does it at CeBIT in a captivating presentation about technologies that will be as important as the internet. Ray is an Inventor, Entrepreneur, Futurist, Writer, founder of the Singularity University and now at Google. (Intro is temporally missing). March 2017.

Here’s my speech topic at Moogfest on the Immortality Bus and #transhumanism on May 20 at 4:30PM:

View more about this event at Moogfest 2017.

The year is 2030. Former president Donald Trump’s border wall, once considered a political inevitability, was never built. Instead, its billions of dollars of funding were poured into something the world had never seen: a strip of shared territory spanning the border between the United States and Mexico. Otra Nation, as the state is called, is a high-tech ecotopia, powered by vast solar farms and connected with a hyperloop transportation system. Biometric checks identify citizens and visitors, and relaxed trade rules have turned Otra Nation into a booming economic hub. Environmental conservation policies have maximized potable water and ameliorated a new Dust Bowl to the north. This is the future envisioned by the Made Collective, a group of architects, urban planners, and others who are proposing what they call a “shared co-nation” as a new kind of state.

Many people have imagined their own alternatives to Trump’s planned border wall, from the plausible — like a bi-national irrigation initiative — to the absurd — like an “inflatoborder” made of plastic bubbles. Made’s members insist that they’re serious about Otra Nation, though, and that they’ve got the skills to make it work. That’s almost certainly not true — but it’s also beside the point. At a time when policy proposals should be taken “seriously but not literally,” and facts are up for grabs, Otra Nation turns the slippery Trump playbook around to offer a counter-fantasy. In the words of collective member Marina Muñoz, “We can really make the complete American continent great again.”

SAN FRANCISCO, April 4, 2017 /PRNewswire/ — Enlitic, a medical deep learning company, is pleased to announce that it has executed a Memorandum of Understanding (“MOU”) with Beijing Hao Yun Dao Information & Technology Co., Ltd (“Paiyipai”) to provide Enlitic’s deep learning solution to Paiyipai for diagnostic imaging in Health Check centers across China.

Paiyipai is a medical big data company. The company is a market leader in China in the analysis of individual laboratory medical test results, and the storage and distribution of user medical records.

The MOU forms the basis of collaboration for the first large-scale commercial deployment of Enlitic’s deep learning technology in China. It was executed following a successful 10,000 chest x-ray trial of Enlitic’s patient triage platform.

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This wasn’t the first such event – the agricultural revolution had upended human lives 12,000 years earlier.

A growing number of experts believe that a third revolution will occur during the 21st century, through the invention of machines with intelligence which far surpasses our own. These range from Stephen Hawking to Stuart Russell, the author of the best-selling AI textbook, AI: A Modern Approach.

Rapid progress in machine learning has raised the prospect that algorithms will one day be able to do most or all of the mental tasks currently performed by humans. This could ultimately lead to machines that are much better at these tasks than humans.

Continue reading “Positively shaping development of artificial intelligence” »