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If you really have the need for speed, you could get it on the ground. But if you’re looking more for stuff that can break the sound barrier many times over, you should consider looking up. That’s the hint casually dropped by aeronautic manufacturer Lockheed Martin, which has mulled over revisiting the idea of a hypersonic revamp. In this case, they’re reportedly looking at an upgrade of the old SR-71 “Blackbird” that first took to the air nearly 60 years ago.

Lockheed Martin’s Skunk Works department has been making noises about a revival of the legendary bomber, a jet that was capable of flying up to Mach 3. That’s slightly more than 3,700 mph, about one and a half times speedier than the .220 Swift, reportedly the fastest bullet ever produced.

But the Skunk Work’s brain trust claims the SR-72 might even double the speed of its predecessor. That’s a tricky proposition considering the plane’s air intake would be brutal at those speeds, like trying to start a campfire in gale-force winds.

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Lockheed Martin’s Advanced Development Programs, known as Skunk Works, has demonstrated an artificial intelligence-powered intelligence, surveillance and reconnaissance (ISR) pod autonomously searching out and confirming a target.

The demonstration was conducted at Edwards Air Force Base in California using an ISR pod mounted on a Lockheed Martin F-16 fighter, says the company on 8 May. The demonstration was conducted in Air Force Test Pilot School.

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The U.S. Navy is teaming up with DARPA to develop autonomous, robotic ships that are completely human free. The NOMARS (No Mariners Required Ship) concept, if successful, would be a huge leap over current unmanned surface vessel development efforts. The result could be a warship able to do the tedious, dangerous, and dirty jobs all by itself, keeping human-crewed ships safe from harm—and boredom.

The Navy, struggling to grow the fleet on a flat defense budget, is making a big push into unmanned surface vessels, or USVs. The Navy plans to build ten Large Unmanned Surface Vehicle ships, 200 to 300 foot long vessels displacing 2,000 tons, in five years. LUSV would act as a scout, sailing ahead of the fleet to detect threats early, or floating magazine, carrying a large load of missiles. LUSV would ideally be autonomous, or optionally manned with a small crew.

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“The world is currently rightly focused on tackling the global health emergency,” Mark Wright, science director of the U.K. branch of the World Wildlife Fund, told The Guardian. “However, this new research reinforces that, after we are through this extremely difficult time, we will need renewed ambitious action to address the climate and nature crisis.”

More on the environment: Doomsday Report Author: Earth’s Leaders Have Failed

Up next__elon musk says he’ll be working on the tesla assembly line today.

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Of the seven patterns of AI that represent the ways in which AI is being implemented, one of the most common is the recognition pattern. The main idea of the recognition pattern of AI is that we’re using machine learning and cognitive technology to help identify and categorize unstructured data into specific classifications. This unstructured data could be images, video, text, or even quantitative data. The power of this pattern is that we’re enabling machines to do the thing that our brains seem to do so easily: identify what we’re perceiving in the real world around us.

The recognition pattern is notable in that it was primarily the attempts to solve image recognition challenges that brought about heightened interest in deep learning approaches to AI, and helped to kick off this latest wave of AI investment and interest. The recognition pattern however is broader than just image recognition In fact, we can use machine learning to recognize and understand images, sound, handwriting, items, face, and gestures. The objective of this pattern is to have machines recognize and understand unstructured data. This pattern of AI is such a huge component of AI solutions because of its wide variety of applications.

The difference between structured and unstructured data is that structured data is already labelled and easy to interpret. However unstructured data is where most entities struggle. Up to 90% of an organization’s data is unstructured data. It becomes necessary for businesses to be able to understand and interpret this data and that’s where AI steps in. Whereas we can use existing query technology and informatics systems to gather analytic value from structured data, it is almost impossible to use those approaches with unstructured data. This is what makes machine learning such a potent tool when applied to these classes of problems.

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👽 We are running out of sand, Find out why.

Fyodor R.

If you’re planning a beach vacation, you’d better get to it soon. An alarming statistic for you: 67% of Southern California beaches? GONE by 2100. All because of sand. Even if you don’t think about the grainy stuff, you use it daily. You’re reading this off something made with sand, looking at it through a screen made with sand, surrounded by buildings made with concrete. I could let you guess what’s in concrete, but I suspect you’re already catching onto a theme here.

Continue reading “World Is Running Out Of Sand — Why There’s Now A Black Market For It” | >

Young blood plasma is known to confer beneficial effects on various organs in mice. However, it was not known whether young plasma rejuvenates cells and tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly-accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n=593 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain-, liver-, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n=850 human tissue samples to the training data. We employed these six clocks to investigate the rejuvenation effects of a plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers and behavioral responses to assess cognitive functions. Cellular senescence, which is not associated with epigenetic aging, was also considerably reduced in vital organs. Overall, this study demonstrates that a plasma-derived treatment markedly reverses aging according to epigenetic clocks and benchmark biomarkers of aging.

Several authors are founders, owners, employees (Harold Katcher and Akshay Sanghavi) or consultants of Nugenics Research (Steve Horvath and Agnivesh Shrivastava) which plans to commercialize the “Elixir” treatment. Other authors (Kavita Singh, Shraddha Khairnar) received financial support from Nugenics Research. The other authors do not have conflict of interest.

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