An Android Trojan's code has been found in more than 60 games distributed via the official Google Play Store, and is using steganography techniques to secretly receive further malicious code for execution on infected devices.
Eric Ladizinsky visited the Quantum AI Lab at Google LA to give a talk "Evolving Scalable Quantum Computers." This talk took place on March 5, 2014.
"The nineteenth century was known as the machine age, the twentieth century will go down in history as the information age. I believe the twenty-first century will be the quantum age". Paul Davies
Quantum computation represents a fundamental paradigm shift in information processing. By harnessing strange, counterintuitive quantum phenomenon, quantum computers promise computational capabilities far exceeding any conceivable classical computing systems for certain applications. These applications may include the core hard problems in machine learning and artificial intelligence, complex optimization, and simulation of molecular dynamics .. the solutions of which could provide huge benefits to humanity.
Realizing this potential requires a concerted scientific and technological effort combining multiple disciplines and institutions ... and rapidly evolving quantum processor designs and algorithms as learning evolves. D-Wave Systems has built such a mini-Manhattan project like effort and in just a under a decade, created the first, special purpose, quantum computers in a scalable architecture that can begin to address real world problems. D-Wave's first generation quantum processors (now being explored in conjunction with Google/NASA as well as Lockheed and USC) are showing encouraging signs of being at a "tipping point" .. matching state of the art solvers for some benchmark problems (and sometimes exceeding them) ... portending the exciting possibility that in a few years D-Wave processors could exceed the capabilities of any existing classical computing systems for certain classes of important problems in the areas of machine learning and optimization.
In this lecture, Eric Ladizinsky, Co-Founder and Chief Scientist at D-Wave will describe the basic ideas behind quantum computation , Dwave's unique approach, and the current status and future development of D-Wave's processors. Included will be answers to some frequently asked questions about the D-Wave processors, clarifying some common misconceptions about quantum mechanics, quantum computing, and D-Wave quantum computers.
Speaker Info: Eric Ladizinsky is a physicist, Co-founder, and Chief Scientist of D-Wave Systems. Prior to his involvement with D-Wave, Mr. Ladizinsky was a senior member of the technical staff at TRW's Superconducting Electronics Organization (SCEO) in which he contributed to building the world's most advanced Superconducting Integrated Circuit capability intended to enable superconducting supercomputers to extend Moore's Law beyond CMOS. In 2000, with the idea of creating a quantum computing mini -Manhattan-project like effort, he conceived, proposed, won and ran a multi-million dollar, multi-institutional DARPA program to develop a prototype quantum computer using (macroscopic quantum) superconducting circuits. Frustrated with the pace of that effort Mr. Ladizinsky, in 2004, teamed with D-Wave's original founder (Geordie Rose) to transform the then primarily IP based company to a technology development company modeled on his mini-Manhattan-project vision. He is also responsible for designing the superconducting (SC) IC process that underlies the D-Wave quantum processors ... and transferring that process to state of art semiconductor production facilities to create the most advanced SC IC process in the world.
A pulsating star in the constellation Lyra generates a unique fractal pattern that hints at unknown stellar processes.
What struck John Learned about the blinking of KIC 5520878, a bluish-white star 16,000 light-years away, was how artificial it seemed. A “variable” star, KIC 5520878 brightens and dims in a six-hour cycle, seesawing between cool-and-clear and hot-and-opaque. Overlaying this rhythm is a second, subtler variation of unknown origin; this frequency interplays with the first to make some of the star’s pulses brighter than others. In the fluctuations, Learned had identified interesting and, he thought, possibly intelligent sequences, such as prime numbers (which have been floated as a conceivable basis of extraterrestrial communication). He then found hints that the star’s pulses were chaotic.
But when Learned mentioned his investigations to a colleague, William Ditto, last summer, Ditto was struck by the ratio of the two frequencies driving the star’s pulsations. “I said, ‘Wait a minute, that’s the golden mean.’” This irrational number, which begins 1.618, is found in certain spirals, golden rectangles and now the relative speeds of two mysterious stellar processes. It meant that the blinking of KIC 5520878 wasn’t an extraterrestrial signal, Ditto realized, but something else that had never before been found in nature: a mathematical curiosity caught halfway between order and chaos called a “strange nonchaotic attractor.”
Dynamical systems — such as pendulums, the weather and variable stars — tend to fall into circumscribed patterns of behavior that are a subset of all the ways they could possibly behave. A pendulum wants to swing from side to side, for example, and the weather stays within a general realm of possibility (it will never be zero degrees in summer). Plotting these patterns creates a shape called an “attractor.”
Mathematicians in the 1970s used attractors to model the behavior of chaotic systems like the weather, and they found that the future path of such a system through its attractor is extremely dependent on its exact starting point. This sensitivity to initial conditions, known as the butterfly effect, makes the behavior of chaotic systems unpredictable; you can’t tell the forecast very far in advance if the flap of a butterfly’s wings today can make the difference, two weeks from now, between sunshine and a hurricane. The infinitely detailed paths that most chaotic systems take through their attractors are called “fractals.” Zoom in on a fractal, and new variations keep appearing, just as new outcrops appear whenever you zoom in on the craggy coastline of Great Britain. Attractors with this fractal structure are called “strange attractors.”
Then in 1984, mathematicians led by Celso Grebogi, Edward Ott and James Yorke of the University of Maryland in College Park discovered an unexpected new category of objects — strange attractors shaped not by chaos but by irrationality. These shapes formed from the paths of a system driven at two frequencies with no common multiple — that is, frequencies whose ratio was an irrational number, like pi or the golden mean. Unlike other strange attractors, these special “nonchaotic” ones did not exhibit a butterfly effect; a small change to a system’s initial state had a proportionally small effect on its resulting fractal journey through its attractor, making its evolution relatively stable and predictable.
“It was quite surprising to find these fractal structures in something that was totally nonchaotic,” said Grebogi, a Brazilian chaos theorist who is now a professor at the University of Aberdeen in Scotland.
Though no example could be positively identified, scientists speculated that strange nonchaotic attractors might be everywhere around and within us. It seemed possible that the climate, with its variable yet stable patterns, could be such a system. The human brain might be another.
The first laboratory demonstration of strange nonchaotic dynamics occurred in 1990, spearheaded by Ott and none other than William Ditto. Working at the Naval Surface Warfare Center in Silver Spring, Maryland, Ditto, Ott and several collaborators induced a magnetic field inside a metallic strip of tinsel called a “magnetoelastic ribbon” and varied the field’s strength at two different frequencies related by the golden ratio. The ribbon stiffened and relaxed in a strange nonchaotic pattern, bringing to life the mathematical discovery from six years earlier. “We were the first people to see this thing; we were pleased with that,” Ditto said. “Then I forgot about it for 20 years.
The study of variable stars entered boom times in 2009 with the launch of the Kepler telescope, which looked for small aberrations in starlight as a sign of distant planets. The telescope gathered a trove of unprecedented data on the pulsations of variable stars throughout the galaxy. Other, ground-based surveys have added further riches.
The data revealed subtle variations in many of the stars’ pulsations that hinted at stellar processes beyond those described by Eddington. The pulses of starlight could be separated into two main frequencies: a faster one like the beat of a snare drum and a slower one like a gong, with the two rhythms played out of sync. And in more than 100 of these variable stars — including those, like KIC 5520878, belonging to a subclass called “RRc” — the ratios defining the duration of one frequency relative to the other inexplicably fell between 1.58 and 1.64.
Understanding how the brain works: “The brain is 400 different computers.”Modeling and building a brain: “You can’t do it from the bottom up.”Backing up the brain: “There’s no ‘you.’ … I’m not exactly like I was five minutes ago….”Is the brain “just” a machine? “There’s no person in here … identity is an illusion.”Emotional intelligence: “‘Emotions are different from thinking’: that’s nonsense.”Human-level artificial intelligence: “We will need AIs because longevity is increasing. … There will be no one to do the work. … We’ll need to find something else to do.”Unfriendly AI: “Machines may re-compile themselves. … People say, ‘Scientists should be more responsible for what they do.’ The fact is, the scientist is no better and possibly worse than the average person at deciding what’s good and what’s bad, and if you ask scientists to spend a lot of time deciding what to invent or not, all you can get from that is that they won’t invent some things that might be wonderful.”Is the Singularity near? “Yes, depending on what you mean by ‘near’ … It may well be, within our lifetimes.”
Via Dr. Stefan Gruenwald
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