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Mathematicians have discovered a surprising pattern in the expression of prime numbers, revealing a previously unknown “bias” to researchers.

Primes, as you’ll hopefully remember from fourth-grade math class, are numbers that can only be divided by one or themselves (e.g. 2, 3, 5, 7, 11, 13, 17, etc.). Their appearance in the roll call of all integers cannot be predicted, and no magical formula exists to know when a prime number will choose to suddenly make an appearance. It’s an open question as to whether or not a pattern even exists, or whether or not mathematicians will ever crack the code of primes, but most mathematicians agree that there’s a certain randomness to the distribution of prime numbers that appear back-to-back.

Or at least that’s what they thought. Recently, a pair of mathematicians decided to test this “randomness” assumption, and to their shock, they discovered that it doesn’t actually exist. As reported in New Scientist, researchers Kannan Soundararajan and Robert Lemke Oliver of Stanford University in California have detected unexpected biases in the distribution of consecutive primes.

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Or not.

It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago. Google’s AlphaGo has won two of the first three games against grandmaster Lee Sedol in a Go tournament, showing the dramatic extent to which AI has improved over the years. That fateful day when machines finally become smarter than humans has never appeared closer—yet we seem no closer in grasping the implications of this epochal event.

Indeed, we’re clinging to some serious—and even dangerous—misconceptions about artificial intelligence. Late last year, SpaceX co-founder Elon Musk warned that AI could take over the world, sparking a flurry of commentary both in condemnation and support. For such a monumental future event, there’s a startling amount of disagreement about whether or not it’ll even happen, or what form it will take. This is particularly troubling when we consider the tremendous benefits to be had from AI, and the possible risks. Unlike any other human invention, AI has the potential to reshape humanity, but it could also destroy us.

It’s hard to know what to believe. But thanks to the pioneering work of computational scientists, neuroscientists, and AI theorists, a clearer picture is starting to emerge. Here are the most common misconceptions and myths about AI.

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Microsoft founder optimistic about embryonic technology.

Researchers could be using cloud-based quantum computing power to solve big scientific conundrums within the next decade, Microsoft founder Bill Gates has predicted.

The Microsoft founder turned philanthropist was hopeful about the future of the embryonic technology during an Ask Me Anything interview on Reddit.

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Interesting — DNA Microchips to be released soon.

Researchers presented this incredible work at the national meeting and exposition of the American Chemical Society (ACS) in San Diego, California, on Sunday.

Adam T Woolley, professor of chemistry at Brigham Young University (BYU) said that they are planning to use DNA’s small size and base-pairing capabilities and ability to self-assemble, and direct it to make nanoscale structures that could be used for electronics.

“The problem, however, is that DNA does not conduct electricity very well. So we use the DNA as a scaffold and then assemble other materials on the DNA to form electronics,” Woolley added.

Continue reading “Get ready for DNA-based computer chips!” | >

There are at least 200 forms of cancer and many more subtypes. Cancer is caused by an accumulation of DNA errors, or mutations, that allows cells to proliferate in an uncontrolled manner. Each cancer subtype has its own unique signature of DNA mutations in its genome; identifying these mutations and understanding how they interact to drive the disease is the foundation for improving cancer prevention, early detection and treatment.

TCGA’s finalized tissue collection contains matched tumor and normal tissues from 11,000 patients, and allows for the comprehensive characterization of 33 cancer types and subtypes, including 10 rare cancers. The comprehensive data that have been generated by TCGA’s network approach are freely available and widely used by the cancer community through the TCGA Data Portal and the Cancer Genomics Hub (CGHub).

In 2012, Cycle Computing and a multinational biotechnology company partnered to leverage cloud computing to analyze TCGA data in a unique way. The firm had developed a new end-to-end solution to identify DNA mutations in the TCGA data that could act as markers and risk factors in cancer samples. This solution included the typical SNP and DNA variation workflow, as well as a custom gene fusion, chromosome aberration discovery pipeline.

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Scientists has opened a door to faster, cheaper computer chips with the help of ‘DNA origami.’ “We would like to use DNA’s very small size, base-pairing capabilities and ability to self-assemble, and direct it to make nanoscale structures that could be used for electronics,” Adam T. Woolley said.

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Stanford’s μTug minibots are on a roll lately.

The latest battery of experiments at Stanford’s Biomimetics and Dextrous Manipulation Lab dealt with harnessing the power of ants in robot form— specifically, researchers hoped to replicate ants’ ability to work together to haul very heavy objects. In the experiments, robots that jump or walk with a quick, jerky force were quickly determined to be inefficient in groups, while the μTugs won out due to the longer duration of pulling force they were able to create with their tiny winches. If you’ve ever played tug of war than this strategy already makes intrinsic sense. Not only could the μTug smimc ants through teamwork, but they anchored themselves to the ground with an adhesive borrowed from gecko toes.

To prove just how powerful the robots are, scientists took a group of six μTugs—which can pull up to 52 pounds each —and had them move a full-sized car with a passenger inside. Did we mention the passenger was the author of the research paper? When those things start self-replicating, he’s going to be the first one they come after.

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