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Category: military – Page 238

Chemical innovation plays a key role in developing cutting-edge technologies for the military. Research chemists design and synthesize new molecules that could enable a slew of next-generation military products, such as novel propellants for spacecraft engines; new pharmaceuticals and medicines for troops in the field; lighter and longer-lasting batteries and fuel cells; advanced adhesives, coatings and paints; and less expensive explosives that are safer to handle. The problem, however, is that existing molecule design and production methods rely primarily on experts’ intuition in a laborious, trial-and-error research process.

DARPA’s Make-It program, currently in year three of a four-year effort, is developing software tools based on machine learning and expert-encoded rules to recommend synthetic routes (i.e., the “recipe” to make a particular molecule) optimized for factors such as cost, time, safety, or waste reduction. The program seeks to free chemists so that they may focus their energy on chemical innovation, rather than testing various molecular synthesis pathways. The program also is developing automated devices that uniformly and reproducibly create the desired chemical based on the software-generated recipe – this one-device, many-molecules concept is a departure from the traditional dedicated reactors in chemical production. Make-It research teams have recently demonstrated significant progress toward fully automated rapid molecule production, which could speed the pace of chemical discovery for a range of defense products and applications.

“A seasoned research chemist may spend dozens of hours designing synthetic routes to a new molecule and months implementing and optimizing the synthesis in a lab,” said Anne Fischer, program manager in DARPA’s Defense Sciences Office. “Make-It is not only freeing chemists to expend brain power in other areas such as molecular discovery and innovation, it is opening chemical synthesis and discovery to a much broader community of scientific researchers who will benefit from faster development of new molecules.”

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I dont see it as a threat. Honestly, some of the US scientific community was getting really cocky, and really lazy, which is never a good combination. The US scientific community wanted to lock Crispr in a closet for 50 years. 30 years ago they could of gotten away with it. With China as it is now, they are forced to do research they would of rather hidden away.

China’s “Thousand Talents” program to tap into its citizens educated or employed in the U.S. is a key part of multi-pronged efforts to transfer, replicate and eventually overtake U.S. military and commercial technology, according to American intelligence officials.

The program, begun in 2008, is far from secret. But its unadvertised goal is “to facilitate the legal and illicit transfer of U.S. technology, intellectual property and know-how” to China, according to an unclassified analysis by the National Intelligence Council, the branch of U.S. intelligence that assesses long-term trends.

More from Bloomberg.com: U.S. Quits UN Human Rights Council, Saying It’s Anti-Israel.

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He formerly headed the U.S. federal safety agency responsible for overseeing all energy & hazmat transportation by air, land, sea, rail and pipelines as the head of the Pipeline and Hazardous Materials Safety Administration (PHMSA) at the U.S. Department of Transportation (USDOT). He also served as the federal government&s;s top trucking, bus, and moving industry attorney as the Chief Counsel of the Federal Motor Carrier Safety Administration (FMCSA), also at the USDOT.

A retired a commissioned officer and naval aviator, his military service included tours of duty in Europe, Asia, Africa, and the Middle East. During his time he participated in military combat and humanitarian relief operations around the globe.

An avid traveler and student of history, he spends his time covering public policy impact issues for Forbes and other publications and provides legal and advisory services to public and private sector clients interested in matters pertaining to defense, energy, transportation, homeland security, and the environment.

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The history of Area 51 stretches back to the 1950s.

Area 51 has been the focal point of alien conspiracy theories in America for decades. The remote military base in the Nevada desert has a lot of history, and has been associated with aliens almost since its inception. Here’s why. Following is a transcript of the video:

In the early 1950s, US planes were conducting low-flying recon missions over the USSR. But there were constant worries of them being spotted and shot down.

So … in 1954, President Eisenhower authorized the development of a top secret, high-altitude recon aircraft Dubbed Project Aquatone. The program required a remote location that wasn’t easily accessible to civilians or spies. Area 51 fit the bill perfectly.

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The point of the experiment was to show how easy it is to bias any artificial intelligence if you train it on biased data. The team wisely didn’t speculate about whether exposure to graphic content changes the way a human thinks. They’ve done other experiments in the same vein, too, using AI to write horror stories, create terrifying images, judge moral decisions, and even induce empathy. This kind of research is important. We should be asking the same questions of artificial intelligence as we do of any other technology because it is far too easy for unintended consequences to hurt the people the system wasn’t designed to see. Naturally, this is the basis of sci-fi: imagining possible futures and showing what could lead us there. Issac Asimov gave wrote the “Three Laws of Robotics” because he wanted to imagine what might happen if they were contravened.

Even though artificial intelligence isn’t a new field, we’re a long, long way from producing something that, as Gideon Lewis-Kraus wrote in The New York Times Magazine, can “demonstrate a facility with the implicit, the interpretive.” But it still hasn’t undergone the kind of reckoning that causes a discipline to grow up. Physics, you recall, gave us the atom bomb, and every person who becomes a physicist knows they might be called on to help create something that could fundamentally alter the world. Computer scientists are beginning to realize this, too. At Google this year, 5,000 employees protested and a host of employees resigned from the company because of its involvement with Project Maven, a Pentagon initiative that uses machine learning to improve the accuracy of drone strikes.

Norman is just a thought experiment, but the questions it raises about machine learning algorithms making judgments and decisions based on biased data are urgent and necessary. Those systems, for example, are already used in credit underwriting, deciding whether or not loans are worth guaranteeing. What if an algorithm decides you shouldn’t buy a house or a car? To whom do you appeal? What if you’re not white and a piece of software predicts you’ll commit a crime because of that? There are many, many open questions. Norman’s role is to help us figure out their answers.

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