Lifeboat Foundation

Cognitive computing (CC) technology revolves around making computers adept at mimicking the processes of the human brain, which is basically making them more intelligent. Even though the phrase cognitive computing is used synonymously with AI, the term is closely associated with IBM’s cognitive computer system, Watson. IBM Watson is a supercomputer that leverages AI-based disruptive technologies like machine learning (ML), real-time analysis, natural language processing, etc. to augment decision making and deliver superior outcomes.

If you shrank yourself down and entered a proton, you’d experience among the most intense pressures found anywhere in the universe.

Finding the best light-harvesting chemicals for use in solar cells can feel like searching for a needle in a haystack. Over the years, researchers have developed and tested thousands of different dyes and pigments to see how they absorb sunlight and convert it to electricity. Sorting through all of them requires an innovative approach.

Now, thanks to a study that combines the power of supercomputing with data science and experimental methods, researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Cambridge in England have developed a novel “design to device” approach to identify promising materials for dye-sensitized solar cells (DSSCs). DSSCs can be manufactured with low-cost, scalable techniques, allowing them to reach competitive performance-to-price ratios.

The team, led by Argonne materials scientist Jacqueline Cole, who is also head of the Molecular Engineering group at the University of Cambridge’s Cavendish Laboratory, used the Theta supercomputer at the Argonne Leadership Computing Facility (ALCF) to pinpoint five high-performing, low-cost dye materials from a pool of nearly 10,000 candidates for fabrication and device testing. The ALCF is a DOE Office of Science User Facility.

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The gravitational pull of a black hole is so strong that nothing, not even light, can escape once it gets too close. However, there is one way to escape a black hole — but only if you’re a subatomic particle.

As black holes gobble up the matter in their surroundings, they also spit out powerful jets of hot plasma containing electrons and positrons, the antimatter equivalent of electrons. Just before those lucky incoming particles reach the event horizon, or the point of no return, they begin to accelerate. Moving at close to the speed of light, these particles ricochet off the event horizon and get hurled outward along the black hole’s axis of rotation.

Known as relativistic jets, these enormous and powerful streams of particles emit light that we can see with telescopes. Although astronomers have observed the jets for decades, no one knows exactly how the escaping particles get all that energy. In a new study, researchers with Lawrence Berkeley National Laboratory (LBNL) in California shed new light on the process. [The Strangest Black Holes in the Universe].

Dr. Rico explained: “When we compare human genomes from different people, we see that they are way more different than we initially expected when the Human Genome Project was declared to be ”completed” in 2003. One of the main contributions to these differences are the so called Copy Number Variable (CNV) regions. CNV regions are in different copy number depending on each individual, and their variability can be greater in some human populations than others. The number of copies of CNV regions can contribute to both normal phenotypic variability in the populations and susceptibility to certain diseases.

Research has shown a direct relationship between mutations in introns and variability in human populations.

One of the greatest challenges of genomics is to reveal what role the ”dark side” of the human genome plays: those regions where it has not yet been possible to find specific functions. The role that introns play within that immense part of the genome is especially mysterious. The introns, which represent almost half the size of the human genome, are constitutive parts of genes that alternate with regions that code for proteins, called exons.

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A participation in the annual Supercomputing conference taking place in Salt Lake City, UT, USA from November 14–17, 2016.

Trying to streamline an operation that spends more than $5 billion a year on developing new drugs, Novartis dispatched teams to jetmaker Boeing Co. and Swissgrid AG, a power company, to observe how they use technology-laden crisis centers to prevent failures and blackouts. That led to the design of something that looks like the pharma version of NASA’s Mission Control: a global surveillance hub where supercomputers map and chart Novartis’s network of 500 drug studies in 70 countries, trying to predict potential problems on a minute-by-minute basis.

A third of development costs comes from clinical trials. Novartis wants to make them cheaper and faster.

CERN has revealed plans for a gigantic successor of the giant atom smasher LHC, the biggest machine ever built. Particle physicists will never stop to ask for ever larger big bang machines. But where are the limits for the ordinary society concerning costs and existential risks?

CERN boffins are already conducting a mega experiment at the LHC, a 27km circular particle collider, at the cost of several billion Euros to study conditions of matter as it existed fractions of a second after the big bang and to find the smallest particle possible – but the question is how could they ever know? Now, they pretend to be a little bit upset because they could not find any particles beyond the standard model, which means something they would not expect. To achieve that, particle physicists would like to build an even larger “Future Circular Collider” (FCC) near Geneva, where CERN enjoys extraterritorial status, with a ring of 100km – for about 24 billion Euros.

Experts point out that this research could be as limitless as the universe itself. The UK’s former Chief Scientific Advisor, Prof Sir David King told BBC: “We have to draw a line somewhere otherwise we end up with a collider that is so large that it goes around the equator. And if it doesn’t end there perhaps there will be a request for one that goes to the Moon and back.”

“There is always going to be more deep physics to be conducted with larger and larger colliders. My question is to what extent will the knowledge that we already have be extended to benefit humanity?”

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Neuroscientists have used a classic branch of maths in a totally new way to peer into the structure of our brains. What they’ve discovered is that the brain is full of multi-dimensional geometrical structures operating in as many as 11 dimensions.

We’re used to thinking of the world from a 3D perspective, so this may sound a bit tricky, but the results of this new study could be the next major step in understanding the fabric of the human brain – the most complex structure we know of.

This latest brain model was produced by a team of researchers from the Blue Brain Project, a Swiss research initiative devoted to building a supercomputer-powered reconstruction of the human brain.

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