Quantum Computers  

According to D-Wave's CEO Vern Brownell, quantum computers have the potential to address problems ranging from finding drugs that can target specific cancers to valuing portfolio risk.

In this interview with McKinsey’s Michael Chui, Vern Brownell, CEO of D-Wave discusses what quantum computing is, how it works, and where it’s headed in the next five years. In 2010 D-Wave introduced the world’s first commercially available quantum computer.

"We’re at the dawn of the quantum-computing age, and it’s really up to us to execute."

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Quantum computing is starting to offer hope for solving more specialized problems that require immensely robust computing. Quantum computers were once thought an impossible technology because they harness the intricate power of quantum mechanics and are housed in highly unconventional environments.

According to Brownell, the advantages that quantum computing can have can even take computing to the next level.

"We’re trying to find the best answer out of a complex set of alternatives. And that could be in portfolio analysis and financial services. It could be trying to find the right types of drugs to give a cancer patient—lots of meaty, very impactful types of applications that are in the sampling world that we believe are very relevant to this," he says.

Brownell is the co-founder and CEO of D-Wave Systems. Michael Chui is a principal at the McKinsey Global Institute and is based in McKinsey’s San Francisco office.

SOURCE  McKinsey & Company

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Quantum Computers  

Researchers at Google’s Quantum AI Lab have confirmed the D-Wave quantum machine that it and NASA have been testing for two years has beaten a conventional computer in a series of tests.

Google's Quantum Artificial Intelligence Lab has announced that it has confirmed that their D-Wave quantum computer is much faster than simulated annealing — a simulation of quantum computation on a classical computer chip.  According to one writer, "If confirmed, this discovery could not only lead to iRobot-style artificial intelligence but also advance the US space program by light years."

"We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing."

Google and NASA partnered to set up the D-Wave test machine in 2013, sharing the purchase and hosting of the machine from the Canadian company.

"We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing," writes Hartmut Neven, Google Director of Engineering of the quantum hardware group on a company blog.

The team also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This method is designed to emulate the behavior of quantum systems, but it runs on conventional processors.

Results of the research have been published in a paper available online.

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• D-Wave Systems Smashes the 1000 Qubit Quantum Computing Barrier 
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"While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 10⁸," write the researchers.

So far, algorithmic simulations of the quantum annealing processes have been much more effective than the first generation complicated D-Wave technology, but it is progressing at faster-than-exponential rates.

"Due to the denser connectivity of next generation annealers, we expect those methods will become ineffective," states Neven.

In our experience we find that lean stochastic local search techniques such as simulated annealing are often the most competitive for hard problems with little structure to exploit. Therefore, we regard simulated annealing as a generic classical competition that quantum annealing needs to beat. We are optimistic that the significant runtime gains we have found will carry over to commercially relevant problems as they occur in tasks relevant to machine intelligence.

More work is needed to turn existing quantum systems like D-Waves into a practical technology, conclude the researchers. "The design of next generation annealers must facilitate the embedding of
problems of practical relevance."

They would specifically like to increase the density and control precision of the connections between the qubits as well as their coherence as well as enhance the representation of quadratic optimization and other higher order optimization scenarios. Researchers at D-Wave and other projects, including other quantum computer projects at Google, are working on systems with larger and larger sets of qubits to meet these demands.

SOURCE  Google Research

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Artificial Intelligence  

Geordie Rose, the founder of D-Wave whose recent clients are Google and NASA, believes that the power of quantum computing is that we can `exploit parallel universes’ to solve problems that we have no other means of confirming. Simply put, quantum computers can think exponentially faster and simultaneously such that as they mature they will out pace us. 

At the rate Geordie Rose’s D-Wave quantum computer is learning he predicts it will out-strip human intelligence by 2028.

According to Rose in his talk given at ideacity earlier this year, equating quantum computers to traditional computers is like comparing horses to airplanes.

Related articles

• Ben Goertzel On Aspects of Artificial General Intelligence 
• Quantum Computer Wins Head-To-Head Test
• Google and NASA Team Up To Explore the Potential of the D-Wave Quantum Computer 

SOURCE  ideacity

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Quantum Computing  

In a new video from D-Wave, Dr. Dominic Walliiman offers an explanation of quantum annealing used in quantum computers.

Quantum annealing is essentially a way of using the intrinsic effects of quantum physics to help solve certain types of problems. It is the core foundation of the quantum computers built by D-Wave.

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Mainly, these are broken down into optimization problems, but they also relate to a sub-field called probabilistic sampling.

In optimization problems, the aim is to figure out the best configuration out of many different configurations. In Walliiman's example, he reflects how the process may be used to figure out the optimal household maintenance budget, based on a large list of items that could have money spent on them at a given period of time.

In physics, optimization problems are a characteristic of energy  minimization problems. Quantum annealing is an ideal method for finding the minimum energy states of systems.

These processes, in turn, are useful in machine learning, where the goal is to build a probabalistic picture of a system and quantum annealing can help to continuously improve the system over time. So far these types of problems have been extremely challenging for classical computers, and are a major stimulating factor behind the push to build functional quantum computer systems.

SOURCE  D-Wave

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Quantum Computers  

D-Wave has officially broken the 1000 qubit barrier with their newest quantum processor that is about double the size of previous generations, and far exceeds the size of any other quantum processor. This updated processor will allow significantly more complex computational problems.

D-Wave Systems Inc., the world's first quantum computing company, has announced their new 1000 qubit D-Wave 2X quantum computing system. The D-Wave 2X features a over a thousand qubit quantum processor and numerous design improvements that result in larger problem sizes, faster performance and higher precision.

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At the 1000+ qubit level, the D-Wave 2X quantum processor evaluates all of 2¹⁰⁰⁰ possible solutions simultaneously as it converges on optimal or near optimal solutions, more possibilities than there are particles in the observable universe.

According the company's press release, "No conventional computer of any kind could represent this many possibilities simultaneously, further illustrating the powerful nature of quantum computation."

Jeremy Hilton, vice president of processor development at D-Wave, said, “The D-Wave 2X marks the latest step forward in our aggressive performance trajectory. Our first system, the D-Wave Onesystem, was the first scalable quantum computer, but was slower than general-purpose optimization software. The next generation D-Wave Two system significantly outperformed the general-purpose optimization software, but was only comparable to specialized highly tuned heuristic algorithms. With the D-Wave 2X system we have surpassed the performance of these specialized algorithms, providing incentive for users to develop methods to harness this revolutionary technology for their own applications.”

"The next generation D-Wave Two system significantly outperformed the general-purpose optimization software, but was only comparable to specialized highly tuned heuristic algorithms."

To showcase the performance of the new system, a paper outlining benchmark results for a set of problems native to the D-Wave 2X system. The benchmark includes a set of synthetic discrete combinatorial optimization problems intended to be representative of real world challenges.  Some application challenges currently under study at D-Wave involve algorithms that tune stock portfolios or underlie machine learning used in bioinformatics, inductive logic programming, and natural language processing and computer vision.

In addition to scaling beyond 1000 qubits, the new system incorporates other major technological and scientific advancements. These include an operating temperature below 15 millikelvin, near absolute zero and 180 times colder than interstellar space. With over 128,000 Josephson tunnel junctions, the new processors are believed to be the most complex superconductor integrated circuits ever successfully used in production systems. Increased control circuitry precision and a 50% reduction in noise also contribute to faster performance and enhanced reliability.

“Breaking the 1000 qubit barrier marks the culmination of years of research and development by our scientists, engineers and manufacturing team,” said D-Wave CEO Vern Brownell. “It is a critical step toward bringing the promise of quantum computing to bear on some of the most challenging technical, commercial, scientific, and national defense problems that organizations face.”

SOURCE  D-Wave

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 Quantum Computers  

In a milestone development the company says will allow research into more complex quantum calculation problems, D-Wave has announced that it's new processor will break the 1000 quibit barrier.

D-Wave Systems has announced that it has broken the 1000 qubit barrier, developing a processor about double the size of the Canadian company’s previous generation and far surpassing the number of qubits ever developed by D-Wave or any other quantum effort.  This is a major technological and scientific achievement that will allow significantly more complex computational problems to be solved than was possible on any previous quantum computer.

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It seems like Rose's Law of Quantum Computing may be as much a self-fulfilling prophecy as it's predecessor, Moore's Law has been.

D-Wave’s quantum computer runs a quantum annealing algorithm to find the lowest points, corresponding to optimal or near optimal solutions, in a virtual “energy landscape.” Every additional qubit doubles the search space of the processor. At 1000 qubits, the new processor considers 21000 possibilities simultaneously, a search space which dwarfs the 2512 possibilities available to the 512-qubit D-Wave Two. ‪In fact, the new search space contains far more possibilities than there are ‪particles in the observable universe.

"D-Wave is at the forefront of this space today with customers like NASA and Google, and this latest advancement will contribute significantly to the evolution of the Quantum Computing industry."

“For the high-performance computing industry, the promise of quantum computing is very exciting. It offers the potential to solve important problems that either can’t be solved today or would take an unreasonable amount of time to solve,” said Earl Joseph, IDC program vice president for HPC. “D-Wave is at the forefront of this space today with customers like NASA and Google, and this latest advancement will contribute significantly to the evolution of the Quantum Computing industry.”

As the sole manufacturer of scalable quantum processors, D-Wave breaks new ground with every succeeding generation it develops. The new processors, comprising over 128,000 Josephson tunnel junctions, are believed to be the most complex superconductor integrated circuits ever successfully yielded.

“Temperature, noise, and precision all play a profound role in how well quantum processors solve problems.  Beyond scaling up the technology by doubling the number of qubits, we also achieved key technology advances prioritized around their impact on performance,” said Jeremy Hilton, D-Wave vice president, processor development. “We expect to release benchmarking data that demonstrate new levels of performance later this year.”

The 1000-qubit milestone is the result of intensive research and development by D-Wave. The research and development effort also means:

• Lower Operating Temperature: While the previous generation processor ran at a temperature close to absolute zero, the new processor runs 40% colder. The lower operating temperature enhances the importance of quantum effects, which increases the ability to discriminate the best result from a collection of good candidates.​
• Reduced Noise: Through a combination of improved design, architectural enhancements and materials changes, noise levels have been reduced by 50% in comparison to the previous generation. The lower noise environment enhances problem-solving performance while boosting reliability and stability.
• Increased Control Circuitry Precision: In the testing to date, the increased precision coupled with the noise reduction has demonstrated improved precision by up to 40%. To accomplish both while also improving manufacturing yield is a significant achievement.
• Advanced Fabrication:  The new processors comprise over 128,000 Josephson junctions (tunnel junctions with superconducting electrodes) in a 6-metal layer planar process with 0.25μm features, believed to be the most complex superconductor integrated circuits ever built.
• New Modes of Use: The new technology expands the boundaries of ways to exploit quantum resources.  In addition to performing discrete optimization like its predecessor, firmware and software upgrades will make it easier to use the system for sampling applications.

“Breaking the 1000 qubit barrier marks the culmination of years of research and development by our scientists, engineers and manufacturing team,” said D-Wave CEO Vern Brownell. “It is a critical step toward bringing the promise of quantum computing to bear on some of the most challenging technical, commercial, scientific, and national defense problems that organizations face.”


SOURCE  D-Wave

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 Quantum Computers

In a new video released by D-Wave, the makers of the first commercial quantum computer, provide a tour of their facilities and a detailed explanation of their system.

Seeing the D-Wave facilities first-hand is a very interesting experience and can now be accessed by a video provided by the company. D-Wave is the world's first commercial quantum computing company, and has sold systems to Google and NASA.

In the video Jeremy Hilton, the company’s VP of Processor Development is the guide for the tour, and helps provide a detailed explanation of the quantum computer system developed by D-Wave. He shows what the cooling system involves, the electromagnetic shielding and how the electronics system programs the quantum processor.

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D-Wave's machines look a lot like computer mainframes did back in the 1960s. There are many mechanical systems, including pumps that control the cooling system of the machine. "This is obviously highly unusual for a data rack," comments Hilton.

The machine's systems also include the quantum server, that allows users from all over the world to interact with the machine.  In the video below, a diagram of how the data is transferred to the quantum processor for calculation.

The quantum processor is surrounded by radiation shields, magnetic shields, a vacuum and is contained in a refrigerated environment.

The video above is the first of a three-part tour series that D-Wave intends to release.




SOURCE  D-Wave

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Quantum Computers  

The promise of quantum computers has a big obstacle to overcome—the environments of the devices easily introduce error to the system. Now researchers have created a small quantum computing array that for the first time performs with a Sudoku-like error correction method that might pave the way toward practical devices. The team behind the breakthrough have also just joined Google, to further their research.

R
esearchers in the UC Santa Barbara’s physics professor John Martinis’ lab have developed quantum circuitry that self-checks for errors and suppresses them, preserving a qubits’ state(s) and imbuing the system with the highly sought-after reliability that may be the long sought after foundation for the building large-scale superconducting quantum computers.

Keeping qubits error-free, or stable enough to reproduce the same result time and time again, is one of the major hurdles scientists on the forefront of quantum computing face.

“One of the biggest challenges in quantum computing is that qubits are inherently faulty,” said Julian Kelly, graduate student researcher and co-lead author of a research paper that was published in the journal Nature. “So if you store some information in them, they’ll forget it.”

Unlike classical computing, in which the computer bits exist on one of two binary (“yes/no”, or “true/false”) positions, qubits can exist at any and all positions simultaneously, in various dimensions. It is this property, called “superpositioning,” that gives quantum computers their phenomenal computational power, but it is also this characteristic which makes qubits prone to “flipping,” especially when in unstable environments, and thus difficult to work with.

 “It’s hard to process information if it disappears,” said Kelly.

However, that obstacle may just have been cleared by Kelly, postdoctoral researcher Rami Barends, staff scientist Austin Fowler and others in the Martinis Group.

The error process involves creating a scheme in which several qubits work together to preserve the information, said Kelly. To do this, information is stored across several qubits.

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“And the idea is that we build this system of nine qubits, which can then look for errors,” he said. Qubits in the grid are responsible for safeguarding the information contained in their neighbors, he explained, in a repetitive error detection and correction system that can protect the appropriate information and store it longer than any individual qubit can.

“This is the first time a quantum device has been built that is capable of correcting its own errors,” said Fowler. For the kind of complex calculations the researchers envision for an actual quantum computer, something up to a hundred million qubits would be needed, but before that a robust self-check and error prevention system is necessary.

Key to this quantum error detection and correction system is a scheme developed by Fowler, called the surface code. It uses parity information — the measurement of change from the original data (if any) — as opposed to the duplication of the original information that is part of the process of error detection in classical computing. That way, the actual original information that is being preserved in the qubits remains unobserved as follows quantum physics.

"This is the first time a quantum device has been built that is capable of correcting its own errors."

“You can’t measure a quantum state, and expect it to still be quantum,” explained Barends. The very act of measurement locks the qubit into a single state and it then loses its superpositioning power, he said. Therefore, in something akin to a Sudoku puzzle, the parity values of data qubits in a qubit array are taken by adjacent measurement qubits, which essentially assess the information in the data qubits by measuring around them.

“So you pull out just enough information to detect errors, but not enough to peek under the hood and destroy the quantum-ness,” said Kelly.

This development represents a meeting of the best in the science behind the physical and the theoretical in quantum computing — the latest in qubit stabilization and advances in the algorithms behind the logic of quantum computing.

“It’s a major milestone,” said Barends. “Because it means that the ideas people have had for decades are actually doable in a real system.”

The Martinis Group continues to refine its research to develop this important new tool. This particular quantum error correction has been proved to protect against the “bit-flip” error, however the researchers have their eye on correcting the complimentary error called a “phase-flip,” as well as running the error correction cycles for longer periods to see what behaviors might emerge.

Martinis and the senior members of his research group have, since this research was performed, entered into a partnership with Google.

The recruitment of the Martinis group signals Google's intent to recruit or tap into talent with wide-ranging expertise at the Google Quantum Artificial Intelligence Lab which also involves NASA. The move also inaugurates a new era of cooperation between academic researchers and D-Wave (under the Google umbrella). The scenario would have seemed unbelievable just several years ago because of the skepticism and heated debates surrounding D-Wave's machines.

SOURCE  UCSB

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 Quantum Computing  

As Time's Lev Grossman demonstrates, quantum computers make use of bizarre effects like quantum superposition and quantum entanglement, to function.  These features may have the potential to unlock massive amounts of processing power, and to solve problems and jump-start artificial intelligence breakthroughs.

Recently writing for Time Magazine, Lev Grossman covered the quantum computer era being ushered in by Burnaby, B.C.'s D-Wave. D-Wave has so few customers so far and its computer is so radical and strange, that people are still trying to figure out what it's for and how to use it.

It could represent an enormous new source of computing power according to Grossman, with the potential to solve problems that would take conventional computers centuries.  The D-Wave Two and next generation offerings from the company may have revolutionary consequences for fields ranging from cryptography to nanotechnology, pharmaceuticals to artificial intelligence.

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D-Wave was founded by Geordie Rose, a leading advocate for quantum computing and physics-based processor design.

Rose's ambitious approach to building quantum computing technology has received coverage in MIT Technology Review magazine, The Economist, New Scientist, Scientific American and Science magazines, and one of his business strategies was profiled in a Harvard Business School case study. He has received several awards and accolades for his work with D-Wave, including being short-listed for a 2005 World Technology Award.

Rose holds a PhD in theoretical physics from the University of British Columbia, specializing in quantum effects in materials. While at McMaster University, he graduated first in his class with a BEng in Engineering Physics, specializing in semiconductor engineering.

"If it succeeds it will be as revolutionary as the microprocessor," says Grossman.  "You have to imaging the whole field of computing starting over, and we're starting a new story."



Grossman also discussed his article with Charlie Rose:



SOURCE  Bloomberg, Time via Geordie Rose

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 Quantum Computing  

Announced in May, Google and NASA's Quantum Artificial Intelligence Lab has now been introduced in a film takes a look at various researchers working on the project, as well as the computer itself.

Google has produced a video introducing some of the people involved with the newly founded Quantum Artificial Intelligence Lab.

In May, in partnership with NASA, Google announced the Quantum A.I. Lab, a place where researchers from around the world can experiment with the incredible powers and possibilities of quantum computing.  The facility, located in a NASA research center uses D-Wave's quantum computers.

It is still early days, but Google thinks quantum computing can help solve some of the world’s most challenging computer science problems. The company is particularly interested in how quantum computing can advance machine learning, which can then be applied to virtually any field: from finding the cure for a disease to understanding changes in our climate.

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D-Wave's Geordie Rose, who is featured in the video commented on his blog,

There are some great memes in the video. One of my favorites was raised by Sergio Boixo. He says at 4:25, '... [this machine] teaches us that we shouldn't be naive about the world, and we shouldn't think about the world as a simple machine. It forces us to consider more sophisticated notions of how the reality around us is actually shaped.'

In the video, Rose comments that the ultimate problem for quantum computers to work on are optimization problems.  Speaking non-technically he also offers,

How amazing is it that we, with our monkey heritage and monkey brains and monkey fingers, have lucked into a brain that allows us to ask legitimate questions about the nature of physical reality. That's so cool.

The film also features commentator Jason Silva ruminating on the possibilities of the technology. Silva also gets the poetic last words:

It's that human risk to go forth into that unknown frontier, whether it's space exploration or quantum exploration.  We do it because we must.  We do it because that what it means to be human.

SOURCE  Google Quantum A.I. Lab Team

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 Quantum Computers  

In a new video from Big Think, physicist and author Lawrence Krauss describes quantum computing and the technical obstacles we need to overcome to realize this ambitious technological goal.

In the video above from Big Think, Lawrence Krauss describes quantum computing and the technical obstacles we need to overcome to realize this Holy Grail of processing.

According to Krauss, author of A Universe from Nothing, the difference between a quantum computer and a regular computer, is at some level. In a regular computer, you've got ones and zeros, which you store in binary form and you manipulate them and they do calculations.

In the quantum world, explains Krausss, particles like electrons are actually spinning in all directions at the same time, one of the weird aspects of quantum mechanics. We may measure, by doing a measurement of an electron, find it's spinning this way. But before we did the measurement, it was spinning this way and this way and that way and that way all at the same time.

This means, if the electron's spinning in many different directions at the same time, if we don't actually measure it, it can be doing many computations at the same time. "And so a quantum computer is based on manipulating the state of particles like electrons so that during the calculation, many different calculations are being performed at the same time, and only making a measurement at the end of the computation."

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If we could exploit that fact of quantum mechanics that particles could do many things at the same time, we would be able to do many computations at same time. And that's what would make a quantum computer so powerful.

"One of the reasons it's so difficult to make a quantum computer, and one of the reasons I'm a little skeptical at the moment, is that - the reason the quantum world seems so strange to us is that we don't behave quantum mechanically. I don't -- you know, you can - not me, but you could run towards the wall behind us from now 'til the end of the universe and bang your head in to it and you'd just get a tremendous headache," states Krauss. "But if you're an electron, there's a probability if I throw it towards the wall that it will disappear and appear on the other side due to something called quantum tunneling, okay."

Krauss is therefore in the camp that says the D-Wave system is not, in fact, a quantum computer. This despite the rising support that the Burnaby B.C.-based company's product is the real thing.  

Krauss maintains that the problem with a quantum computer is essentially quantum behavior.

"You want to make this macroscopic object, you want to keep it behaving quantum mechanically which means isolating it very carefully from, within itself, all the interactions and the outside world. And that's the hard part, Is isolating things enough to maintain this what's called quantum coherence. And that's the challenge and it's a huge challenge."

The potential of quantum computers is unbelievably great. Once you can engineer materials on a scale where quantum mechanical properties are important, a whole new world of phenomenon opens up.

Krauss says, "You might be able to say - as we say, if we created a quantum computer, and I'm not - I must admit I'm skeptical that we'll be able to do that in the near-term, but if we could, we'd be able to do computations in a finite time that would take longer than the age of the universe right now. We'd be able to do strange and wonderful things. And of course, if you ask me what's the next big breakthrough, I'll tell you what I always tell people, which is if I knew, I'd be doing it right now."


SOURCE  Big Think

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 Quantum Computers  

In a recent conversation with Singularity Weblog's Nikola Danaylov, D-Wave Computer's Geordie Rose covered a variety of interesting topics such as: how wrestling competitively created an opportunity for him to discover Quantum Mechanics; why he decided to become an entrepreneur building computers at the edge of science and technology.

Geordie Rose is a founder and Chief Technology Officer at D-Wave Computers.

During a recent conversation with Singularity Weblog's Nikola Danaylov, Rose covered a variety of interesting topics such as: how wrestling competitively created an opportunity for him to discover Quantum Mechanics; why he decided to become an entrepreneur building computers at the edge of science and technology; what the name D-wave stands for; what is a quantum computer; and why fabrication technology is the greatest limiting factor towards commoditizing quantum computing.

Rose also explains Vesuvius – D-Wave’s latest model, and the kinds of problems it can compute; Rose’s Law as the quantum computer version of Moore’s Law; how D-wave resolves the de-coherence/interference problem; the traditional von Neumann architecture behind classical computer design and why D-Wave had to move beyond it; Vesuvius’ computational power as compared to similarly priced classical super-computers and the inherent difficulties in accurate bench-marking; Eric Ladizinski’s qubit and the velodrome metaphor used to describe it; the skepticism among numerous scientists as to whether D-Wave really makes quantum computers or not; whether Geordie feels occasionally like Charles Babbage trying to build his difference engine; his prediction that quantum computers will help us create AI by 2029; whether the brain is more like a classical or quantum computer; and how you can apply for programming time on the two D-wave quantum computers.

In the interview, Rose also offers his take on the technological Singularity.

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According to Rose, “Machine learning is progressing faster than you think and will become more broadly available on shorter timescales than you might have hoped.”

Rose is a founder and CTO of D-Wave. He is a leading advocate for quantum computing and physics-based processor design, and has been invited to speak on these topics in venues ranging from the 2003 TED Conference to the 2013 HPC User Forum.

Rose’s innovative and ambitious approach to building quantum computing technology has received coverage in MIT Technology Review magazine, The Economist, New Scientist, Scientific American, Nature and Science magazines, and one of his business strategies was profiled in a Harvard Business School case study. He has received several awards and accolades for his work with D-Wave, including winning the 2011 Canadian Innovation Exchange Innovator of the Year award.

Dr. Rose holds a PhD in theoretical physics from the University of British Columbia, specializing in quantum effects in materials. While at McMaster University, he graduated first in his class with a BEng in Engineering Physics, specializing in semiconductor engineering. He also is a two-time Canadian national wrestling champion, the 2010 NAGA Brazilian Jiu-Jitsu world champion, and a member of the McMaster University sports Hall of Fame.



SOURCE  Singularity Weblog

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 Quantum Computing  

The new NASA Quantum Artificial Intelligence Laboratory (QuAIL) has the goal to demonstrate that quantum computing and quantum algorithms may someday dramatically improve the agency’s ability to solve difficult optimization problems for missions in aeronautics, Earth and space sciences, and space exploration.

NASA’s Quantum Artificial Intelligence Laboratory (QuAIL) has been introduced via a new website.  The program was announced earlier this year, in cooperation with Google. QuAIL is the American space agency's new hub for an experiment to assess the potential of quantum computers to perform calculations that are difficult or impossible using conventional supercomputers.

The QuAIL team aims to demonstrate that quantum computing and quantum algorithms may someday dramatically improve the agency’s ability to solve difficult optimization problems for missions in aeronautics, Earth and space sciences, and space exploration.  For now, the concentration is more on fundamental research.

The hope is that quantum computing will vastly improve a wide range of tasks that can lead to new discoveries and technologies, and which may significantly change the way we solve real-world problems.

Initiating their work with the D-Wave Two quantum computer, NASA’s QuAIL team will will evaluate various quantum computing approaches to help address NASA challenges. Initial work will focus on theoretical and empirical analysis of quantum annealing approaches to difficult optimization problems.

The team is also studying how the effects of noise, imprecision in the quantum annealing parameters, and thermal processes affect the efficacy and robustness of quantum annealing approaches to these problems. Over the next five years, the research team will also develop quantum AI algorithms, problem decomposition and hardware embedding techniques, and quantum-classical hybrid algorithms.

Quantum computing is based on quantum bits or qubits. Unlike traditional computers, in which bits must have a value of either zero or one, a qubit can represent a zero, a one, or both values simultaneously. For NASA's researchers, representing information in qubits allows the information to be processed in ways that have no equivalent in classical computing, taking advantage of phenomena such as quantum tunneling and quantum entanglement. It has been suggested that quantum computers may theoretically be able to solve certain problems in a few days that would take millions of years on a classical computer.

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NASA is exploring the potential of quantum computing—and quantum annealing algorithms in particular—to aid in the many challenging computational problems involved in NASA missions.

One initial target application area the QuAIL team will be exploring is related to the NASA Kepler mission’s search for habitable, Earth-sized exoplanets.

The complex computational task of identifying and validating the transit signals of smaller planets as they orbit their host stars is currently based on heuristic algorithms (designed to find approximate solutions when classic methods don’t find exact solutions), implying that some planets could remain undiscovered due to this computational limitation. Using a quantum computer to perform Kepler’s data-intensive search for transiting planets among the more than 150,000 stars in the spacecraft’s field of view has the potential to provide a unique, complementary approach to the task of discovering potential new Earth-like exoplanets.

Another early target application area the team will explore is in the area of planning and scheduling. Determining the very best use of limited resources during space missions—such as time and power—can require hours, days or even weeks to solve with classical algorithms. Automated planners have their origins in robotics and have been used extensively in space applications. 

Some examples of these applications developed at NASA Ames include automated planners for the ongoing Mars Curiosity mission and software that helps optimize operations of the International Space Station’s solar arrays. NASA researchers are mapping planning problems from a variety of areas, including planetary rover exploration, to forms suitable to be run on quantum computing systems.


SOURCE  NASA QuAIL via Geordie Rose

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