Deep in the bowels of the Smithsonian National Museum of American History in Washington DC sits a large metal cabinet the size of a walk-in wardrobe. The cabinet houses a remarkable computer the front is covered in dials, switches and gauges and inside it is filled with potentiometers controlled by small electric motors. Behind one of the cabinet doors is a 20 x 20 array of light sensitive cells, a kind of artificial eye.

This is the Perceptron Mark I, a simplified electronic version of a biological neuron. It was designed by the American psychologist Frank Rosenblatt at Cornell University in the late 1950s who taught it to recognize simple shapes such as triangles.

Rosenblatts work is now widely recognized as the foundation of modern artificial intelligence but at the time it was controversial. Despite the original success, researchers were unable to build on this, not least because more complex pattern recognition required vastly more computational power than was available at the time. This insatiable appetite prevented further study of artificial neurons and the networks they create.

Todays deep learning machines also eat power, lots of it. And that raises an interesting question about how much they will need in future. Is this appetite sustainable as the goals of AI become more ambitious?

Today we get an answer thanks to the work of Neil Thompson at the Massachusetts Institute of Technology in Cambridge and several colleagues. This team has measured the improved performance of deep learning systems in recent years and show that how it depends on increases in computing power.

By extrapolating this trend, they say that future advances will soon become unfeasible. Progress along current lines is rapidly becoming economically, technically, and environmentally unsustainable, say Thompson and colleagues, echoing the problems that emerged for Rosenblatt in the 1960s.

The teams approach is relatively straightforward. They analyzed over 1000 papers on deep learning to understand how learning performance scales with computational power. The answer is that the correlation is clear and dramatic.

In 2009, for example, deep learning was too demanding for the computer processors of the time. The turning point seems to have been when deep learning was ported to GPUs, initially yielding a 5 15 speed-up, they say.

This provided the horsepower for a neural network called AlexNet, which famously triumphed in a 2012 image recognition challenge where it wiped out the opposition. The victory created huge and sustained interest in deep neural networks that continues to this day.

But while deep learning performance increased by 35x between 2012 and 2019, the computational power behind it increased by an order of magnitude each year. Indeed, Thompson and co say this and other evidence suggests the computational power for deep learning has increased 9 orders of magnitude faster than the performance.

So how much computational power will be required in future? Thompson and co say that error rate for image recognition is currently 11.5 percent using 10^14 gigaflops of computational power at a cost of millions of dollars (ie 10^6 dollars).

They say achieving an error rate of just 1 per cent will require 10^28 gigaflops. And extrapolating at the current rate, this will cost 10^20 dollars. By comparison, the total amount of money in the world right now is measured in trillions ie 10^12 dollars.

Whats more, the environmental cost of such a calculation will be enormous, an increase in the amount of carbon produced of 14 orders of magnitude. Progress along current lines is rapidly becoming economically, technically, and environmentally unsustainable, conclude Thompson and colleagues.

The future isnt entirely bleak, however. Thompson and cos extrapolations assume that future deep learning systems will use the same kinds of computers that are available today.

But various new approaches offer much more efficient computation. For example, in some tasks the human brain can outperform the best supercomputers while running on little more than a bowl of porridge. Neuromorphic computing attempts to copy this. And quantum computing promises orders of magnitude more computing power with relatively little increase in power consumption.

Another option is to abandon deep learning entirely and concentrate on other forms of machine learning that are less power hungry.

Of course, there is no guarantee that these new techniques and technologies will work. But if they dont, its hard to see how artificial intelligence will get much better than it is now.

Curiously, something like this happened after the Perceptron Mark I first appeared, a period that lasted for decades and is now known as the AI winter. The Smithsonian doesnt currently have it on display, but it is surely marks a lesson worth remembering.

Ref: arxiv.org/abs/2007.05558 : The Computational Limits of Deep Learning

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The Computational Limits of Deep Learning Are Closer Than You Think - Discover Magazine

This week the machine learning community had their handsful with OpenAIs new toy GPT-3. Many enthusiasts applied the model for various innovative uses and few even started startups that work on GPT-3. Apart from this, there are also reports of the quarterly earnings, which saw Microsoft performing well, especially in the cloud segment. Know what else has happened in this weeks top AI news.

In a recent development, GitHub moved 21TB of its open-source code and repositories in the form of digital photosensitive archival film into Arctic Code Vault, Svalbard. The boxes of reels are stored in hundreds of meters of permafrost and can last for 1000 years. Done in collaboration with their archive partners, Piql. This initiative, GitHub Archive Program, aims to preserve the open-source software for future generations.

D-Wave Systems, a Canadian quantum computing company announced the expansion of its Leap cloud access and quantum application environment to India and Australia. The company claims that now users in these countries will have real-time access to a commercial quantum computer. In addition to access, Leap offers free developer plans, teaching and learning tools, code samples, demos and an emerging quantum community to help developers, forward-thinking business and researchers get started building and deploying quantum applications.

The race to democratise has made MLaaS a lucrative business model. The result is, today, there are multiple APIs offering similar services. This again, can be challenging. Addressing this issue and to establish a hassle-free ML ecosystem, a group of researchers from Stanford University, introduced a predictive framework called FrugalML that assists the users in switching between APIs in a smart manner. The researchers have detailed about their new framework in a paper titled, To Call or Not to Call?

The results show that FrugalML leads to more than 50% cost reduction when using APIs from Google, Microsoft and Face++ for a facial emotion recognition task. Whereas, experiments on FER+ dataset showed that only 33% cost is needed to achieve accuracies that match those of Microsoft API.

The authors posit that the performance of Frugal ML is likely because the base services quality score is highly correlated to its prediction accuracy, and their framework only needs to call expensive services for a few difficult data points and relies on the cheaper base services for the relatively easy data points.

Microsoft on Wednesday, reported earnings for its fourth fiscal quarter of 2020, including revenue of $38.0 billion, net income of $11.2 billion, and earnings per share of $1.46 (compared to revenue of $33.7 billion, net income of $13.2 billion, and earnings per share of $1.71 in Q4 2019). All three of the companys operating groups saw year-over-year growth.

Organizations that build their own digital capability will recover faster and emerge from this crisis stronger.

Revenue in Intelligent Cloud was $13.4 billion and increased 17% (up 19% in constant currency). The server products and cloud services revenue increased 19% (up 21% in constant currency) driven by Azure revenue growth of 47% (up 50% in constant currency). Whereas, the enterprise Services revenue was relatively unchanged (up 2% in constant currency).

In a recent survey conducted by IEEE Spectrum, it was found that Python has exerted sheer dominance over its contemporaries Java and C. The organisers have devised 11 metrics to check the popularity of 55 languages. One interpretation of Pythons high ranking is that its metrics are inflated by its increasing use as a teaching language: Students are simply asking and searching for the answers to the same elementary questions over and over, stated IEEE in their blog. The rose in Pythons popularity also coincides with that of fields such as machine learning, which have been increasingly introducing libraries and frameworks that encourage Python users. Given the recent trends, it looks like there are no roadblocks in sight for Python.

GPT-3, the worlds largest NLP model, which was released by OpenAI last month became quite popular. From generating codes to believable stories, this model has been put to use for a wide range of applications.

Generative models can display both overt and diffuse harmful outputs, such as racist, sexist, or otherwise pernicious language. This is an industry-wide issue, making it easy for individual organizations to abdicate or defer responsibility. OpenAI will not.

The popularity rose so high that one of the founders of OpenAI, Sam Altman, had to put out a tweet warning how GPT-3 is still far from being perfect. While the OpenAI team is jubilant of this rapid adoption, have listed a set of guidelines explaining how they would be working on making GPT-3 more reliable in the coming days.

DeepMind researchers released a paper that details a meta learning approach that would allow the researchers to automate the discovery of reinforcement learning algorithms, which have been manual so far. The paper claims that the generated algorithms performed well in video games such as Atari.

The proposed approach has the potential to dramatically accelerate the process of discovering new reinforcement learning algorithms by automating the process of discovery in a data-driven way, wrote the researchers.

Home GPT-3 Obsession, Python Reigns Supreme And More In This Weeks Top AI News

According to VICE reports, Four United Kingdom Uber drivers launched a lawsuit on Monday to gain access to Ubers algorithms through Europes General Data Protection Regulation (GDPR).

The union representing the drivers said theyre seeking to gain a deeper understanding of the algorithms that underpin Ubers automated decision-making system. This level of transparency, the union said, is needed to establish the level of management control Uber exerts on its drivers, allow them to calculate their true wages and benchmark themselves against other drivers, and help them build collective bargaining power.

The information asymmetry that allows Uber to selectively share data in forms that paint it in a favorable lightusually by obscuring negative outcomes like dead mileage or arbitrary deactivation. The case is being heard in Amsterdam and the outcome can severely impact the way Uber and other ride hailing companies do their business.

The University of Florida on Wednesday has announced a public-private partnership with NVIDIA that will catapult UFs research strength to address some of the worlds most formidable challenges, create unprecedented access to AI training and tools for underrepresented communities, and build momentum for transforming the future of the workforce.

The initiative is anchored by a $50 million gift $25 million from UF alumnus Chris Malachowsky and $25 million in hardware, software, training and services from NVIDIA, the Silicon Valley-based technology company he co founded and a world leader in AI and accelerated computing.

Along with an additional $20 million investment from UF, the initiative will create an AI-centric data center that houses the worlds fastest AI supercomputer in higher education. Working closely with NVIDIA, UF will boost the capabilities of its existing supercomputer.

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GPT-3 Obsession, Python Reigns Supreme And More In This Week's Top AI News - Analytics India Magazine

University of Virginia School of Medicinescientists are harnessing the mind-bending potential of quantum computers to help us understand genetic diseases even before quantum computers are a thing.

UVAs Stefan Bekiranov and colleagues have developed an algorithm to allow researchers to study genetic diseases using quantum computers once there are much more powerful quantum computers to run it. The algorithm, a complex set of operating instructions, will help advance quantum computing algorithm development and could advance the field of genetic research one day.

Quantum computers are still in their infancy. But when they come into their own, possibly within a decade, they may offer computing power on a scale unimaginable using traditional computers.

We developed and implemented a genetic sample classification algorithm that is fundamental to the field of machine learning on a quantum computer in a very natural way using the inherent strengths of quantum computers, Bekiranov said. This is certainly the first published quantum computer study funded by the National Institute of Mental Health and may be the first study using a so-called universal quantum computer funded by the National Institutes of Health.

Traditional computer programs are built on 1s and 0s, either-or. But quantum computers take advantage of a freaky fundamental of quantum physics: Something can be and not be at the same time. Rather than 1 or 0, the answer, from a quantum computers perspective, is both, simultaneously. That allows the computer to consider vastly more possibilities, all at once.

The challenge is that the technology is, to put it lightly, technically demanding. Many quantum computers have to be kept at near absolute zero, the equivalent of more than 450 degrees below zero Fahrenheit. Even then, the movement of molecules surrounding the quantum computing elements can mess up the calculations, so algorithms not only have to contain instructions for what to do, but for how to compensate when errors creep in.

Our goal was to develop a quantum classifier that we could implement on an actual IBM quantum computer. But the major quantum machine learning papers in the field were highly theoretical and required hardware that didnt exist. We finally found papers from Dr. Maria Schuld, who is a pioneer in developing implementable, near-term, quantum machine-learning algorithms. Our classifier builds on those developed by Dr. Schuld, Bekiranov said. Once we started testing the classifier on the IBM system, we quickly discovered its current limitations and could only implement a vastly oversimplified, or toy, problem successfully, for now.

The new algorithm essentially classifies genomic data. It can determine if a test sample comes from a disease or control sample exponentially faster than a conventional computer. For example, if they used all four building blocks of DNA (A, G, C or T) for the classification, a conventional computer would execute 3 billion operations to classify the sample. The new quantum algorithm would need only 32.

That will help scientists sort through the vast amount of data required for genetic research. But its also proof-of-concept of the usefulness of the technology for such research.

Bekiranov and collaborator Kunal Kathuria were able to create the algorithm because they were trained in quantum physics, a field that even scientists often find opaque. Such algorithms are more likely to emerge from physics or computer science departments than medical schools. (Both Bekiranov and Kathuria conducted the study in the School of MedicinesDepartment of Biochemistry and Molecular Genetics. Kathuria is currently at the Lieber Institute for Brain Development.)

Because of the researchers particular set of skills, officials at the National Institutes of Healths National Institute of Mental Health supported them in taking on the challenging project. Bekiranov and Kathuria hope what they have developed will be a great benefit to quantum computing and, eventually, human health.

Relatively small-scale quantum computers that can solve toy problems are in existence now, Bekiranov said. The challenges of developing a powerful universal quantum computer are immense. Along with steady progress, it will take multiple scientific breakthroughs. But time and again, experimental and theoretical physicists, working together, have risen to these challenges. If and when they develop a powerful universal quantum computer, I believe it will revolutionize computation and be regarded as one of greatest scientific and engineering achievements of humankind.

The scientists have published their findings in the scientific journalQuantum Machine Intelligence. The algorithm-development team consisted of Kathuria, Aakrosh Ratan, Michael McConnell and Bekiranov.

The work was supported by NIH grants 3U01MH106882-04S1, 5U01MH106882-05 and P30CA044579.

To keep up with the latest medical research news from UVA, subscribe to theMaking of Medicineblog.

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UVA Pioneers Study of Genetic Diseases With Mind-Bending Quantum Computing - University of Virginia

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Canadian quantum computing company D-Wave Systems is launching its cloud service in India, giving developers and researchers in the country real-time access to its quantum computers.

Through this geographic expansion, D-Waves 2000Q quantum computers, hybrid solvers and the application environment can be used via its cloud platform Leap to drive development of business-critical and in-production hybrid applications.

Quantum computing is poised to fundamentally transform the way businesses solve critical problems, leading to new efficiencies and profound business value in industries like transportation, finance, pharmaceuticals and much more, Murray Thom, VP of Software and Services at D-Wave, said in a statement.

The future of quantum computing is in the cloud. Thats why we were eager to expand Leap to India and Australia, where vibrant tech scenes will have access to real-time quantum computers and the hybrid solver service for the first time, unlocking new opportunities across industries.

As part of this rollout, users in India and Australia can work on the D-Waves Leap and Leap 2 platforms.

The two cloud platforms offer updated features and tools, including hybrid solver service that can solve large and complex problems of up to 10,000 variables; and integrated developer environment that has a prebuilt, ready-to-code environment in the cloud configured with the latest Ocean SDK for quantum hybrid development in Python.

D-Waves systems and software have been used in financial modelling, machine learning and route optimization.

Its latest launch in India comes about a year after the countrys Department of Science and Technology (DST) chalked out plans to build its own quantum computers.

In early 2019, DST launched a programme focused on quantum computing, called Quantum-Enabled Science and Technology (QuEST). As part of QuEST, India earmarked 80 crore investment to be spent over a span of three years to facilitate research in setting up quantum computers.

A year later, Finance Minister Nirmala Sitharaman, in her Union Budget 2020 Speech, announced a National Mission on Quantum Technologies and Applications (NM-QTA) with an outlay of 8,000 crore for the next five years.

Quantum technology is opening up new frontiers in computing, communications, cyber security with wide-spread applications, Sitharaman said in her Budget Speech.

It is expected that lots of commercial applications would emerge from theoretical constructs which are developing in this area.

NM-QTAs focus, as outlined by the minister, will be in fundamental science, translation, technology development and, human and infrastructural resource generation.

Other areas of quantum computing applications will include aero-space engineering, numerical weather prediction, simulations, securing communication and financial transactions, cyber-security, and advanced manufacturing.

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D-Waves quantum computing cloud comes to India - The Hindu

WASHINGTON--(BUSINESS WIRE)--Microsoft Executive Vice President Jason Zander says the company has never been more busy partnering with the energy industry on cloud technologies and energy transition; the combination of COVID-19 and the oil market shock has condensed years of digital transformation into a two-month period; the companys return to its innovative roots and its goal to have removed all of the companys historic carbon emissions by 2050 in the latest edition of CERAWeek Conversations.

In a conversation with IHS Markit (NYSE: INFO) Vice Chairman Daniel Yergin, Zanderwho leads the companys cloud services business, Microsoft Azurediscusses Microsofts rapid and massive deployment of cloud-based apps that have powered work and commerce in the COVID-19 economy; how cloud technologies are optimizing business and vaccine research; the next frontiers of quantum computing and its potential to take problems that would take, literally, a thousand years, you might be able to solve in 10 seconds, and more.

The complete video is available at: http://www.ceraweek.com/conversations

Selected excerpts:Interview Recorded Thursday, July 16, 2020

(Edited slightly for brevity only)

Watch the complete video at: http://www.ceraweek.com/conversations

Weve already prepositioned in over 60 regions around the world hundreds of data center, millions and millions of server nodestheyre already there. If you can imagine COVID, if you had to go back and do a procurement exercise and figure out a place to put the equipment, and the supply chains were actually shut down for a while because of COVID. Thats why I say, even three to five years ago we as industries would have been pretty challenged to respond as quickly as we had.

Thats on the more tactical end of the spectrum. On the other end weve also done a lot of things around data sets and advanced data work. How do we find a cure? Weve done things like [protein] folding at home and making sure that those things could be hosted on the cloud. These are thingsthat will be used in the search of a vaccine for the virus. Those are wildly different spectrums from the tactical 'we need to manage and do logistics' to 'we need a search for things that are going to get us all back to basically normal.'

Theres also a whole bunch of stimulus packages and payment systems that are getting created and deployed. Weve had financial services companies that run on top of the cloud. They may have been doing a couple of hundred big transactions a day; weve had them do tens to hundreds of thousands a day when some of this kicked in.

The point is with the cloud I can just go to the cloud, provision it, use it, and eventually when things cool back down, I can just shut it off. I dont have to worry about having bought servers, find a place for them to live, hiring people to take care of them.

There was disruption in supply chain also. Many of us saw this at least in the Statesif you think even the food supply chain, every once in a while, youd see some hiccups. Theres a whole bunch of additional work that weve done around how do we do even better planning around that, making sure we can hit the right levels of scale in the future? God forbid we should have another one of these, but I think we can and should be responsible to make sure that weve got it figured out.

The policy and investment sideit has never been more important for us to collaborate with healthcare, universities, and with others. Weve kicked off a whole bunch of new partnerships and work that will benefit us in the future. This was a good wake up call for all of us in figuring out how to marshal and be able to respond even better in the future.

Weve had a lot of cases where people have been moving out of their own data centers and into ours. Let us basically take care of that part of the system. We can run it cheaply and efficiently. Im seeing a huge amount of data center accelerationfolks that really want to move even faster on getting their workloads removed. Thats true for oil and gas but its also true for the financial sector and retail.

Specifically, for oil and gas, one of the things that were trying to do in particular is bring this kind of cloud efficiency, this kind of AI, and especially help out with places where you are doing exploration. What these have in common is the ability to take software especially from the [independent software vendors] that work in the spacereservoir simulation, explorationand marry that to these cloud resources where I can spin things up and spin things down. I can take advantage of that technology that Ive got, and I am more efficient. I am not spending capex; I can perhaps do even more jobs than I was doing before. That allows me to go do that scale. If youre going to have less resources to do something, you of course want to increase your hit rate; increase your efficiency. Those are some of the core things that were seeing.

A lot of folks, especially in oil and gas, have some of the most sophisticated high-performance computing solutions that are out there today. What we want to be able to do with the cloud is to be able to enable you to do even more of those solutions in a much more efficient way. Weve got cases where people have been able to go from running one reservoir simulation job a day on premises [to] where they can actually go off to the cloud and since we have all of this scale and all of this equipment, you can spin up and do 100 in one day. If that is going to be part of how you drive your efficiency, then being able to subscribe to that and go up and down its helping you do that job much more efficiently than you used to and giving you a lot more flexibility.

Were investing in a $1 billion fund over the next four years for carbon removal technology. We also are announcing a Microsoft sustainability calculator for cloud customers. Basically, you can help get transparency into your Scope 1,2, and 3 carbon emissions to get control. You can think of us as we want to hit this goal, we want to do it ourselves, we want to figure out how we build technology to help us do that and then we want to share that technology with others. And then all along the way we want to partner with energy companies so that we can all be partnering together on this energy transition.

From a corporate perspective weve made pledges around being carbon negative, but then also working with our energy partners. The way that we look at this is youre going to have continued your requirements and improvements in standards of living around the entire planet. One of the core, critical aspects to that is energy. The world needs more energy, not less. There are absolutely the existing systems that we have out there that we need to continue to improve, but they are also a core part of how things operate.

What we want to do is have a very responsible program where were doing things like figuring out how to go carbon negative and figuring out ways that we as a company can go carbon negative. At the same time, taking those same techniques and allowing others to do the same and then partnering with energy companies around energy transformation. We still want the investments in renewables. We want to figure out how to be more efficient at the last mile when we think about the grid. I generally find that when you get that comprehensive answer back to our employees, they understand what we are doing and are generally supportive.

Coming up is a digital feedback loop where you get enough data thats coming through the system that you can actually start to be making smart decisions. Our expectation is well have an entire connected environment. Now we start thinking about smart cities, smart factories, hospitals, campuses, etc. Imagine having all of that level of data thats coming through and the ability to do smart work shedding or shaping of electrical usage, things where I can actually control brownout conditions and other things based on energy usage. Theres also the opportunity to be doing smart sharing of systems where we can do very efficient usage systemsintelligent edge and edge deployments are a core part of that.

How do we keep all the actual equipment that people are using safe? If you think about 5G and additional connectivity, were getting all this cool new technology thats there. You have to figure out a way in which youre leveraging silicon, youre leveraging software and the best in securityand were investing in all three.

The idea of being able to harness particle physics to do computing and be able to figure out things in minutes that would literally take centuries to go pull off otherwise in classical computing is kind of mind-blowing. Were actually working with a lot of the energy companies on figuring out how could quantum inspired algorithms make them more efficient today. As we get to full scale quantum computing then they would run natively in hardware and would be able to do even more amazing things. That one has just the potential to really, really change the world.

The meta point is problems that would take, literally, a thousand years, you might be able to solve in 10 seconds. Weve proven how that kind of technology can work. The quantum-inspired algorithms therefore allow us to take those same kind of techniques, but we can run them on the cloud today using some of the classic cloud computers that are there. Instead of taking 1,000 years, maybe its something that we can get done in 10 days, but in the future 10 seconds.

About CERAWeek Conversations:

CERAWeek Conversations features original interviews and discussion with energy industry leaders, government officials and policymakers, leaders from the technology, financial and industrial communitiesand energy technology innovators.

The series is produced by the team responsible for the worlds preeminent energy conference, CERAWeek by IHS Markit.

New installments will be added weekly at http://www.ceraweek.com/conversations.

Recent segments also include:

A complete video library is available at http://www.ceraweek.com/conversations.

About IHS Markit (www.ihsmarkit.com)

IHS Markit (NYSE: INFO) is a world leader in critical information, analytics and solutions for the major industries and markets that drive economies worldwide. The company delivers next-generation information, analytics and solutions to customers in business, finance and government, improving their operational efficiency and providing deep insights that lead to well-informed, confident decisions. IHS Markit has more than 50,000 business and government customers, including 80 percent of the Fortune Global 500 and the worlds leading financial institutions. Headquartered in London, IHS Markit is committed to sustainable, profitable growth.

IHS Markit is a registered trademark of IHS Markit Ltd. and/or its affiliates. All other company and product names may be trademarks of their respective owners 2020 IHS Markit Ltd. All rights reserved.

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Microsoft Executive Vice President Jason Zander: Digital Transformation Accelerating Across the Energy Spectrum; Being Carbon Negative by 2030; The...

Computing power has reached its saturation point. If we continue following the same path soon, we may not have enough power to run the machines of the world. The solution to this lies in quantum computing. The origins of quantum computing go back in 1981 when renowned physicist Richard Feynman asked in a Massachusetts Institute of Technology conference that, Can we simulate physics on a computer? While it is not totally based on physics, quantum computing does work on the principles of quantum mechanics. Here it uses two properties called superposition and entanglement.

Current conventional computer systems are built around the idea of binary bits and Boolean logic. A bit can be physically represented as a switch with a value of 0 (off) or 1 (on). When these switches are connected using Boolean logic gates (and, or, xor, and others) they can perform all the complex operations of a modern microprocessor. In contrast, quantum computer use qubits (quantum bits) can also be in both states at the same time, a quantum property called superposition. In addition, qubits are also capable of pairing, which is known as entanglement. Here, the state of one qubit cannot be described independently of the state of the others that allows instantaneous communication. As per anIDC report, 25 percent of the Fortune Global 500 will gain a competitive edge from quantum computing by 2023.

Meanwhile, tech giants like Google, Microsoft, and IBM are battling to be the first to make a working, practically useful quantum computer. Every month there are extensive updates from these companies about their work. Recently Google had announced its quantum computer (which uses quantum annealing) is 100 million times faster than any classical computer in its lab. Further, the interest in quantum computing has been mirrored by investments in this field by players from a broad array of industries.

Quantum computers have four fundamental capabilities that differentiate them from todays conventional computers:

1. quantum simulation, in which quantum computers model complex molecules;

2. optimization (that is, solving multivariable problems with unprecedented speed);

3. quantum artificial intelligence, with better algorithms that could transform machine learning across industries as diverse as pharma and automotive;

4. prime factorization, which could revolutionize encryption.

These advanced computers are predicted to solve previously unapproachable problems, creating valuable solutions for industry and will disrupt current techniques. For instance, NASA is looking at using quantum computing for analyzing the enormous amount of data they collect about the universe, as well asresearch better and safer methods of space travel.Auto manufacturer leader, Volkswagen is using quantum computers to develop battery, transportation, and self-driving technology. It can be utilized to boost security since it can enhance the accuracy of measurements and enable new modalities for sensors and measurements.For example, it can accurately detect masses moving underwater, such as submarines.

Oil and gas companies can employ quantum computing to calculate the ways how atoms and molecules can be configured to protect equipment from corrosion. Even in pharmaceuticals, the discovery of new drugs, minimal development time, potential ways to synthesize new compounds are possible due to this technology. In the chemicals industry, it is used to provide a better understanding of catalytic reactions, reducing the cost of industrial processes. Quantum entanglement has also led to the possibility of quantum teleportation.

It is important to note that quantum computers are very fragile. Any vibration will impact the atoms and cause decoherence. Also, at present, quantum computers need highly sophisticated hardware and supporting infrastructure. For this, some of the existing models use superconductivity to create and maintain a quantum state. This implies that qubits must be kept at a temperature near absolute zero using a dilution refrigerator. This is why theinside of D-Wave Systems quantum computeris -460 degrees Fahrenheit. So, companies may need a cloud model to access quantum services instead of installing their own version of quantum computers on-premises. Therefore, not all can have their quantum systems, at least not in the near future.

Moreover, people need to realize that while quantum computers are the future, but they do not replace the standard ones either. Instead, they should be thought of as devices that enhance the usability of conventional general-purpose computers. According to this model, a core application is executed on a traditional computer that can also handle data storage and other infrastructure-related tasks. At the same time, the quantum part can be applied to deal with only the subset of the overall responsibility thats best suited to its particular strengths.

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Quantum Computing: Navigating Towards The Future Of Computers - Analytics Insight

Three of our gang, you see, were women. On our second morning, all three found their periods had kicked in. They were so charmed and amused by this that they forgot any possible cramps or migraines. This was, they told us ignorant men, menstrual synchrony" the tendency for women who live together to begin menstruating on the same day every month. In 1971, a psychologist called Martha McClintock studied 180 women in a college dormitory. Menstrual synchrony, she concluded then, was real.

Now, this really didnt apply that weekend in NYC, because these ladies had only spent one day together. Besides, more recent research has questioned McClintocks findings. Even so, those long-ago NYC days came back to me after reading about some even more recent research, at IIT Kanpur. Not about menstruation, but about synchronization, and in the quantum world.

Whats synchronization? Imagine an individual a bird, a pendulum doing a particular motion over and over again. The bird is flapping its wings as it flies, the pendulum is swinging back and forth. Imagine several such individuals near each other, all doing the same motion several birds flying together in a flock, several pendulums swinging while hanging from a beam. When they start out, the birds are flapping to their own individual rhythms, the pendulums going in different directions. But then something beautiful happens: these individual motions synchronize. The birds flap in perfect coordination, so the flock moves as one marvellous whole. The pendulums swing in harmony.

In fact, synchronization was first observed in pendulums. In 1665, the great Dutch scientist Christiaan Huygens attached two pendulum clocks to a heavy beam. Soon after, the two pendulums were in lockstep.

Similarly, fireflies are known to break into spontaneous synchrony. When there are just one or a few, they light up at different timesa pleasant enough sight, but nothing to write home about. But there are spots in the coastal mangroves of Malaysia and Indonesia where whole hosts of the little insects congregate every evening and suddenly, synchrony happens. They switch on and off in perfect unison, putting on a light show like none youve seen.

There are, yes, other examples. At a concert, the audience will tend to applaud in sync. The reason we only ever see one side of the Moon is that the orbital and rotational periods of the Moon have, over time, synchronized with the rotation of our Earth. Your heart beats because the thousands of pacemaker" cells it contains pulse in synchrony. Some years ago, a bridge of a new and radical design was built over the Thames in London. When it was opened, people swarmed onto it on foot. It quickly started swaying disconcertingly from side to side enough, in turn, to force the pedestrians to walk in a certain awkward way just to keep their footing. On video, youll see hundreds of people on the bridge, all walking awkwardly but in step.

In his book Sync: The Emerging Science of Spontaneous Order, the mathematician Steven Strogatz writes: At the heart of the universe is a steady, insistent beat: the sound of cycles in sync. It pervades nature at every scale from the nucleus to the cosmos." He goes on to observe that this tendency for synchronization does not depend on intelligence, or life, or natural selection. It springs from the deepest source of all: the laws of physics". And thats where IIT Kanpur comes in.

In 2018, a team of Swiss researchers looked at the possibility of synchronization at the lower end of that scale that Strogatz mentions, or in some ways even off that end of the scale. Do the most elementary, fundamental particles known to physicists exhibit the same tendency to synchronize as somewhat larger objects such as starlings and pendulums and the moon? Were talking about electrons and neutrons, particles that occupy the so-called quantum" world. Can we get them to synchronize?

They concluded that the smallest quantum particles actually cannot be synchronized. These exhibit a spin"a form of angular momentum, in a sense the degree to which the particle is rotating of 1/2 (half). But there are ways in which such spin-half" particles can combine to form a spin-1" system, and the Swiss team predicted that these combinations are the smallest quantum systems that can be synchronized.

So, a physics research group at IIT Kanpur decided to test this prediction. These are guys, I should tell you, who are thoroughly accustomed to working with atoms: One day in 2016, their professor, Dr Saikat Ghosh, took me into their darkened lab and pointed to a small red glow visible in the middle of their apparatus. Thats a group of atoms," he said with a grin, and then tweaked some settings and the glow dropped out of sight. The point? They are able to manipulate atoms. On another visit, they underlined this particular skill by showing me their work with graphene, a sheet of carbon that is get this one atom thick.

So, after the Swiss prediction, Ghosh and his students took a million atoms of rubidiuma soft, silvery metal and cooled them nearly to whats known as absolute zero", or -273 Celsius. Could they get these atoms to show synchrony?

Lets be clear about what they were dealing with, though. The usual objects that synchronize pendulums, birds are called oscillators" because they are in some regular, rhythmic motion. Strictly, it is that motion of the oscillators that synchronizes. But were dealing here with objects we can see, which means the rules of classical" physics apply. Quantum objects like atoms behave differently. In fact, Ghosh told me that spin-1 atoms are not really oscillating in the same sense as pendulums and starlings in flight. Still, with that caveat in place, there are ways in which we can abstract their motion and treat them as oscillators.

In their experiment, the IIT team shot pulses of light at the group of rubidium atoms. Light is made up of photons, which are like minuscule bundles of energy. When they hit an atom, they flip" its spin. Embodied in that flip is the photons quantum information; in a real way, the photons are actually stored in these flipped atoms. This happens with such precision that you can later flip the atoms back and release the photons, thus retrieving" the stored light. In fact, with this storage and retrieval behaviour, the atoms are like memory cells, and this is part of the mechanism of quantum computing. (See my column from October 2018, Catch a quantum computer and pin it down).

But when the atoms are flipped and they store these photons, something else happens to them. When the light is retrieved, the IIT team found it displays interference fringes" a characteristic pattern of light and shadow (similar in concept to what causes stripes on tigers and zebras, or patterns in the sand on a beach). From this fringe pattern, the scientists can reconstruct the quantum state the atoms were inand voil, theres synchrony.

Did each individual atom synchronize to the light and since all one million atoms did so, is that how they are synchronized with each other as well? Thats to be tested still, but its a good way to think of what happened. Again, take fireflies. In one experiment, a single flashing LED bulb was placed in a forest. When the fireflies appeared, they quickly synchronized to the flashing bulb, and therefore to each other. As Dr Ghosh commented: two fireflies synchronizing is interesting, but an entire forest filled with fireflies lighting up in sync reveals new emergent patterns."

There are implications in all this for, among other things, quantum computing. The IIT teams paper remarks; [The] synchronization of spin-1 systems can provide insights in open quantum systems and find applications in synchronized quantum networks." (Observation of quantum phase synchronization in spin-1 atoms, by Arif Warsi Laskar, Pratik Adhikary, Suprodip Mondal, Parag Katiyar, Sai Vinjanampathy and Saikat Ghosh, published 3 June 2020).

There will be other applications too. But over 350 years after Christiaan Huygens stumbled on classical" synchronization, the IIT team has shown for the first time that this strangely satisfying behaviour happens in the quantum world too. No wonder their paper was chosen recently for special mention in the premier physics journal, Physical Review Letters.

A round of applause for the IIT folks, please. I know it will happen in synchrony.

Once a computer scientist, Dilip DSouza now lives in Mumbai and writes for his dinners. His Twitter handle is @DeathEndsFun

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Opinion |Dance of the synchronized quantum particles - Livemint

Quantum computers have the potential to solve hard computational problems more efficiently than their classical counterparts. Applications notably encompass computational drug design, materials science, machine learning, and optimization problems. With the rapid developments of quantum hardware, practical quantum advantage is within reach.

With many cities turning to e-mobility to tackle environmental challenges, electric utilities have to account for a growing and more complex load to manage for their production facilities and the grid. One example is the need to schedule resource allocation for shared electric vehicles while taking into considerations their expected and real time availability as well as charging constraints. This class of problem is computationally hard to solve even with large supercomputers and it is expected that a quantum algorithm called Quantum Approximate Optimization Algorithm (QAOA) could improve its resolution.

EDF made smart charging and the development of its infrastructures one of the strong point of its Electric Mobility Plan, launched in October 2018. EDF views smart charging as a true asset for electric vehicles users and for the electrical system. Through its subsidiaries, IZIVIA and DREEV, the EDF Group already provides V2G solutions.

Through its Pulse Explorer Program, EDF R&D routinely reaches out to start-ups to explore new ideas in a collaborative way. EDF and Pasqal have formalized a partnership to explore how this algorithm could be implemented on the neutral atoms quantum processor developed at Pasqal and take benefit from its unique properties.

The core of the partnership is to finely tune the algorithms according to the hardwares possibilities and to mitigate the impact of the errors. The level of performance will be gauged on a classical emulator, prior to a real hardware implementation.

Loc Henriet, head of software development at Pasqal explained: we have developed our full software stack with specific tools for generic optimization problems, but it is very important that we engage directly with partners working on applications. We need to focus on practical use cases to show that quantum processors can provide a real advantage.

Marc Porcheron, head of EDF R&Ds Quantum Computing project, said: utilities such as EDF have to be at the forefront of innovation in high performance computing. It is great to collaborate with Pasqal to explore the new possibilities opened by Quantum Computing for hard optimization problems like the ones we face in the decisive field of smart-charging. I am impressed with the results that have already been achieved with Pasqal, and look forward to implement on their upcoming hardware the quantum algorithms we investigate together.

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Pasqal and EDF partner to study smart-charging challenges with Quantum Computing - Quantaneo, the Quantum Computing Source

The UKs decision to ban its mobile providers from buying new Huawei 5G equipment after December 2020 and removing all the companys 5G kit from their networks by 2027 is a blow to Huawei and China, but it is one battle in a long war that the West is currently losing.

5Gs significance for the next generation of technology is indisputable and so is its critical role in helping countries achieve digital transformation and economic success. Not only does it offer faster and better connection speeds and greater capacity, it also transforms the way people interact with online services. And it will allow industry to automate and optimize processes that are not possible today.

Due to its transformative importance, what is in essence a technological issue has turned into a contest over global technological leadership that extends beyond the US-China rivalry and has created tensions between the US and its long-time allies. Yet 5G is just one key technology in a more expansive landscape that will underpin the future of the worlds critical infrastructure, including in areas such as quantum computing, biotechnology, artificial intelligence, the internet of things and big data.

To achieve technological leadership in these domains requires governments to invest in a long-term, strategic and agile vision that is able to encompass the interdependencies between these areas and then leverage the resulting technological advances for economic progress. It also requires governments working with each other and with the private sector to support research and development and to create companies with leading-edge technologies that can compete globally.

China understands this and has a national and international vision to establish itself as a technological superpower. Re-balancing from a hub oflabour-intensivemanufacturing to a global innovation powerhouse is the absolute priority of the ruling Chinese Communist Party.

In the earlier part of this journey, commercial espionage and IP theft of western R&D were at the heart of the Chinese way of competing. Now, Beijing is cultivating national champions that can drive Chinas technological innovation, with the goal of using domestic suppliers to reducereliance on foreign technology at home as well as extending its international outreach.

In the 5G area, Beijing has introduced domestically the so-called New Infrastructure Investments Fund, which earmarks special loans to boost 5G technology applications in medical devices, electric vehicles and communication platforms. This Fund constitutes a major part of the stimulus package for Chinas post-COVID economic recovery.

Apart from 5G, China's recent launch of a second state-fundedsemiconductor development fundvalued at $29 billion, following an earlier $20 billion fund for the same purpose, shows the extent to which state financial resources are being utilized in Chinas quest to become technologically self-sufficient.

It is too early to know if the Chinese governments industrial policies will eventually achieve the technological self-sufficiency Beijing has long desired. But its growing national capabilities have stoked serious concerns across the West and led to the current US administrations determined effort to dismantle Chinese high-tech companies.

Chinas approach to macroeconomic management diverges significantly from that of the US and other market economies, particularly in its policy towards driving innovation. Due to the legacy of a state-planned economy, China is certain that simply relying on market forces is insufficient.

While Beijing financially supports government-controlled technological enterprises, Washington takes a laissez-faire, light-touch approach by the state to the business sector. The US believes that a politicized process of distributing public money is inherently susceptible to rent-seeking and corruption, and gets in the way of competitive innovation. In line with most liberal economists, many Western governments believe the government should refrain from market intervention. For its part, Beijing stresses a state-dominated economy as a necessary precondition both to the future growth of the Chinese economy and to the legitimization of one-party rule.

If the pro-market economists view iscorrect, the USshould have little to fear from Chinese industrial innovation policy in the long-term. Let Beijing waste money and distort resource allocation, while Washingtonfollows its private sector-led principles, condent that this approach will produce a more competitive economy in the long run.

But one area that should concern the US and that illustrates the Chinese vision for global technological dominance is technical standard setting. Technical standards determine how technologies work with each other, enabling their interoperability around the world, meaning they can function irrespective of where they are being used.

The Chinese leadership has long understood the relationship between technical standards and economic power. Standards help to monetize technological innovation and research and can help shape new technologies. China has therefore been playing an increasingly active role in international standards organizations to legitimize Chinese technologies, whereas the US, which historically has been highly influential in this area, has not been participating as much or as effectively.

China has also been using its Belt and Road Initiative (BRI) as an opportunity to internationalize thedistribution of its standards tocountries signed up to the BRI.The so-called Digital Silk Road, which has been described as Chinas most important global governance initiative, acts as a route to accelerate this process.Later this year, China is expected to launch its new China Standards 2035 plan, which aims to shape how the next generation of technologies will work together.

Chinas preferred model and its recent actions have given Western leaders much to worry about. But standing up to Chinas growing global influence in high technology and re-establishing the Wests desired technological edge will take much more than achieving a common front on excluding China from their 5G networks. It requires a long-term vision built on the power of competitive markets, backed by solid investment in the next generation of technology. This will require, in turn, much greater cooperation between Western governments and between them and their private sectors.

And, whilst recent protective steps taken in Washington and other Western capitals may slow down Chinas trailblazing in the technology sphere, it will only hasten China's determination to become tech self-sufficient in the long term. This will increase the probability of a splintered internet, which will have negative repercussions for all.

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The UKs Huawei Decision: Why the West is Losing the Tech Race - Chatham House

Quantum Computing Market Research Report Cover Covid-19 Outbreak:

Brand Essence Market Research has developed a concise study on the Quantum Computing market to depict valuable insights related to significant market trends driving the industry. The report features analysis based on key opportunities and challenges confronted by market leaders while highlighting their competitive setting and corporate strategies for the estimated timeline.

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TheMajorPlayersCovered in this Report:Hewlett Packard, Alibaba Quantum Computing Laboratory, Booz Allen Hamilton Inc., QxBranch, SPARROW QUANTUM A/S, SeeQC Quantum Circuits, Inc., Anyon Systems Inc, Rigetti Computing, Toshiba Research Europe Ltd. Others & More.

By Vertical Aerospace & Defense BFSI Energy & Power Healthcare Information Technology & Telecommunication Transportation OthersBy Technology Superconducting loops technology Trapped ion technology Topological qubits technologyBy Offering Systems Consulting SolutionsBy Component Hardware Software ServicesBy Industry Defense Banking & Finance Energy & Power Chemicals Healthcare & PharmaceuticalsBy Application Optimization Machine Learning Simulation Others

Results of the recent scientific undertakings towards the development of new Quantum Computing products have been studied. Nevertheless, the factors affecting the leading industry players to adopt synthetic sourcing of the market products have also been studied in this statistical surveying report. The conclusions provided in this report are of great value for the leading industry players. Every organization partaking in the global production of the Quantum Computing market products have been mentioned in this report, in order to study the insights on cost-effective manufacturing methods, competitive landscape, and new avenues for applications.

Global Quantum ComputingMarket: Regional SegmentationFor further clarification, analysts have also segmented the market on the basis of geography. This type of segmentation allows the readers to understand the volatile political scenario in varying geographies and their impact on the global Quantum Computingmarket. On the basis of geography, the global market for Quantum Computinghas been segmented into:

North America(United States, Canada, and Mexico)Europe(Germany, France, UK, Russia, and Italy)Asia-Pacific(China, Japan, Korea, India, and Southeast Asia)South America(Brazil, Argentina, Colombia, etc.)Middle East and Africa(Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

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The information enclosed in this report is based upon both primary and secondary research methodologies.

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Table of Content:

Market Overview: The report begins with this section where product overview and highlights of product and application segments of the Global Quantum Computing Market are provided. Highlights of the segmentation study include price, revenue, sales, sales growth rate, and market share by product.

Competition by Company: Here, the competition in the Worldwide Global Quantum Computing Market is analyzed, By price, revenue, sales, and market share by company, market rate, competitive situations Landscape, and latest trends, merger, expansion, acquisition, and market shares of top companies.

Company Profiles and Sales Data: As the name suggests, this section gives the sales data of key players of the Global Quantum Computing Market as well as some useful information on their business. It talks about the gross margin, price, revenue, products, and their specifications, type, applications, competitors, manufacturing base, and the main business of key players operating in the Global Quantum Computing Market.

Market Status and Outlook by Region: In this section, the report discusses about gross margin, sales, revenue, production, market share, CAGR, and market size by region. Here, the Global Quantum Computing Market is deeply analyzed on the basis of regions and countries such as North America, Europe, China, India, Japan, and the MEA.

Application or End User: This section of the research study shows how different end-user/application segments contribute to the Global Quantum Computing Market.

Market Forecast: Here, the report offers a complete forecast of the Global Quantum Computing Market by product, application, and region. It also offers global sales and revenue forecast for all years of the forecast period.

Research Findings and Conclusion: This is one of the last sections of the report where the findings of the analysts and the conclusion of the research study are provided.

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Europe Quantum Computing Market 2020 | Scope of Current and Future Industry 2025 - Owned

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Quantum Software Market 2020: Potential Growth, Challenges, and Know the Companies List Could Potentially Benefit or Loose out From the Impact of...

The industry of software outsourcing in Sri Lanka has long since been garnering demand to deliver products and services that are uniquely focused towards customers needs both locally and internationally. As businesses both large and small compete to understand their end consumers better, building digital products and services that are oriented towards customer experience arent an embellishment on top of core offerings theyre an essential. As a result, the approach you adopt towards delivering customer-centric products and services can make or break your business in this day and age, especially in light of fierce business competition, as well as a pandemic that has long since enforced lockdowns and invited economic downturns.

In spite ofthe compromised circumstances we are all in on a global scale, business hasstill been functioning as usual. How? Thanks to the cloud, of course. Makingremote work a possibility at record time and at scale, even organizations thatoperated by conventional means up until then experienced little to no downtimeduring transition. Likewise, fast-paced customer centricity has also been madepossible by the cloud, which therefore makes it an integral foundation for thedigital landscape we heavily rely on today.

Asindispensable as it is, the cloud is here to stay, no doubt. But what else doesit have in store for the future? Here are a few such trends, all of which areoffshoots from the world of cloud computing.

At a timewhen everyone was more or less compelled to shift to working remotely (elserisk shutting down their businesses), the cloud has been the driving forcebehind every single transition, complex or otherwise. This has also broughtUnified Communications as a Service (UCaaS) ever more to the forefront, as cloud-basedproviders leading the sector have proactively stepped up to assist businessesin moving over to a remote work environment as smoothly as possible.

Whetherits a basic web conferencing solution to conduct weekly meetings with yourteam, or a remote call centre to handle inquiries from all over the world,UCaaS has been massively beneficial while being completely based and managedon the cloud.

The conceptof automation has long since been abuzz with discussion, and with ampleinfluence from the cloud as well. In due course of the recent turn of eventshowever, automation is an endeavour that is growing in importance for thebenefit of getting things done through minimal contact. While this is one morereason for automation to be taken seriously by businesses of all sizes, itsprofound impact on both a consumer (customized product recommendations) andenterprise (containerized applications that are based across multiple nodes)are just some of the many reasons as to why automation is going to gain evenmore traction as time rolls on by.

Automationclosely ties in over here too, as comprehensive analytics is a prerequisite forautomating operations, including IoT devices. With almost any device now opento the possibility of being transformed into a smart device, telemetry (theprocess of gathering data from endpoints) has improved both in terms of qualityand quantity thereby opening greater opportunities to train your cloud-basedsystems to be more intuitive via AI and machine learning.

As cloudcomputing becomes a crucial component for todays digital landscape, it alsobecomes more vulnerable in terms of cyber security. With businesses andconsumers alike connected and dependent on the cloud 24/7, a large number ofendpoints make cloud-based networks vulnerable to cyber breaches of all kinds,ranging from theft to espionage. As a result, the industry of securitysoftware, which includes both security for your cloud networks as well as SaaSsecurity solutions is constantly on the rise, as organizations plan on how toprevent and mitigate future risks.

Cloud support services arent reserved for consumers and businesses alone; in a fast-paced world which requires equally fast yet accurate problem-solving, quantum computing has been the answer to providing solutions that even the most robust supercomputers of today take years to deliver on. With minimal use cases as of current, as well as research and development still in the works, leading technology giants have been at the centre of it with the cloud providing a strong foundation for operations and analytics to take place.

In a nutshell

While customer centricity had been a major factor behind the advent and innovation of cloud computing, the current pandemic has introduced a whole host of reasons to depend on the very same, all the more. As a dedicated AWS partner, weve been witnessing numerous trends that are rising from the world of cloud computing, with a steady shift to remote work being one of the biggest. Although automation has been a trend in the cloud landscape for a long time, it is slowly gaining traction, as it enables seamless operations on both an enterprise and consumer level.

A growingnumber of endpoints, particularly IoT devices have been the source for advancedtelemetry, thereby enabling round-the-clock collection of data, which can thenbe used to proactively control devices. AI and machine learning further enhancethis process, as cloud networks can now be trained to function in a mannerthats more intuitive, resulting in analytics that are accurate even whenmaking future predictions.

With agrowing interest and reliance on cloud computing, networks are also more proneto vulnerabilities such as data theft, fraud and espionage. The securitysoftware industry (which includes both security for cloud networks, as well assingle-purpose, SaaS-based security solutions) has also experienced asignificant increase in demand. Last but not the least, quantum computing isanother emerging trend in the field of complex problem solving, with leadingtech giants using the cloud as an integral base to conduct research,development and deployments.

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Cloud computing for the future: current trends, what to expect and more. - Lanka Business Online

QMI comes with an in-depth analysis and prediction report on the Quantum Computing in Aerospace and Defense Market. A new research has been carried out across many regions and sectors. It offers a wide-ranging survey report of market players, product type and application level from all key regions like North America, Europe, Asia Pacific, Middle East & Africa, and South America.

This study report shows growth in revenues of Quantum Computing in Aerospace and Defense market in USD from the 2020-2028 forecast periods. The Global Quantum Computing in Aerospace and Defense Market Research Report covers all of the significant developments that are being implemented recently across the global market. The study also offers reliable industry values highly dependent on the end-user as well as manufacturers in Global Quantum Computing in Aerospace and Defense market. The Quantum Computing in Aerospace and Defense market study also makes extensive mention of the major market players operating in this sector.

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Companies Covered:D-Wave Systems Inc, Qxbranch LLC, IBM Corporation, Cambridge Quantum Computing Ltd, 1qb Information Technologies Inc., QC Ware Corp., Magiq Technologies Inc., Station Q-Microsoft Corporation, and Rigetti Computing

A lot of companies are key players in the Quantum Computing in Aerospace and Defense market which are studied extensively in this report. To strengthen their product portfolio and increase their market share the key manufacturers/ companies are constantly improvising their goods and services. The report provides an in-depth review of the Growth Factors, Potential Challenges, Distinctive Patterns and Market Participant Opportunities to allow readers to fully understand the Quantum Computing in Aerospace and Defense market. Major vendors included in the market study along with stock determinations, market share, and sales, figures, efficiency, size, production, cost, and revenue. The QMIs chief objective is to offer crucial insights into current trends, competitive positioning, market potential, alternative related statistics, and growth rates.

The segmentation of Quantum Computing in Aerospace and Defense market is done By Component (Hardware, Software, Services), By Application (QKD, Quantum Cryptanalysis, Quantum Sensing, Naval).

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The report answers the following questions-1. What is the market share of important countries in each of the regions?1. Which regions and countries will show the highest growth potential in the forecast period?2. At what rate the Quantum Computing in Aerospace and Defense market is expanding globally and what are the key upcoming trends in this market?3. Which product and applications are at the top and hold a good potential and chances of growth?4. Which are the main Quantum Computing in Aerospace and Defense market players and their competitors?5. What are the constraints currently impacting the market growth and the main market drivers influencing growth over the period of forecast?

This is anticipated to drive the Global Quantum Computing in Aerospace and Defense Market over the forecast period. This research report covers the market landscape and its progress prospects in the near future. After studying key companies, the report focuses on the new entrants contributing to the growth of the market. Most companies in the Global Quantum Computing in Aerospace and Defense Market are currently adopting new technological trends in the market.

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Quantum Computing in Aerospace and Defense Market To 2028 Report Reviews Size, In-depth Qualitative Insights, Explosive Growth Opportunity, Regional...

Within the next decade, quantum computers will help create the chemicals needed to make energy-efficient fertilizers and significantly cut carbon emissions, an expert told a technology panel last month.

Quantum computers may create molecules that replace chemical catalysts needed for fertilizer production, Jean-Franois Bobier, a Boston Consulting Group partner said at a presentation during the Quantum.Techs Digital Week online conference. Those catalysts consume 3%-5% of the worlds natural gas, cost nearly $300 billion a year and are responsible for 2% of annual worldwide CO2 emissions, Bobier said.

Its a really frustrating problem because we know there is a better way, said Bobier, head of Boston Consultings research and development initiative on quantum computing and technology. Nature is able to do it for free, using just water, air and sunlight. Its just that we can reproduce it at scale in a factory setting.

Todays classical computers, which process information in bits or zeroes and ones, would take over 800,000 years to model the molecules to replace these chemicals. A quantum computer, which processes information in qubits or the superposition of its basis vectors, would require a day, Bobier estimates.

The first replacements for chemicals to synthesize fertilizers, or catalysts, modeled on quantum computers are within our grasp, Bobier said. Although they wont be carbon-neutral, they will be far more carbon-efficient than the 100-year old catalysts in use today.

Quantum computers have the potential to tackle carbon storage, carbon capture and energy production issues that will help stem the tide of CO2 emissions needed to meet the Paris Agreements goal of limiting global warming to less than 2C.

Quantum computers arent quite there yet. Still, Googles quantum computer last year solved in just over 3 minutes a math problem that the tech giant claimed would take the best supercomputer 10,000 years to solve.

Googles quantum computer has 54 qubits. While powerful, this is far from the millions of qubits needed to operate a universal quantum computer with the potential to model the world in a way envisioned by Nobel prize-winning scientist Richard Feynman.

These early quantum computers may be enough to model smaller and less complex molecules such as catalysts.

Catalysts are small molecules, up to 250 atoms, Bobier said. That will be within the grasp of the qubits we will have.

Big corporations are taking note of these first quantum machines under development by Google, IBM, Canadian start-up D-Wave and others which may have enough power to provide an advantage for the development of climate-fighting technologies.

Fertilizer chemical giant BASF teamed up with quantum software consultants HQS to explore algorithms to solve complex problems that may eventually run on quantum computers. Aerospace giant Airbus, automotive company VW and chemical company Evonik, are also exploring the use of quantum computer algorithms now for when the hardware becomes available.

Yes, it will be a long time, and yes, we are going to have to be patient for the use cases, but we need to be prepared now, Bobier said.

Continued here:

Quantum Computing to Be Harnessed in Climate Control Effort - Karma

BOSTON, MA July 14, 2020 New survey results fromthe Pistoia Alliance, the Quantum Economic Development Consortium (QED-C) and QuPharm show almost one-third (31 percent) of life science organizations polled are set to begin quantum computing evaluation this year. A further 39 percent are planning to evaluate next year or have quantum computing on their radar, while 30 percent have no current plans to evaluate.

The three organizations have collaborated to establish a cross-industry Community of Interest (CoI) to explore the opportunities for quantum computing to enhance the efficiency and effectiveness of biopharma R&D. The CoI aims to support companies that need help navigating the pathway to quantum computing and will facilitate collaboration between stakeholders, propose new ideas for quantum computing projects, and help interested parties define and articulate potential use cases.

The interest in quantum computing across many sectors is high, yet most biopharmaceutical companies are only just beginning the journey and exploring the potential for accelerating discovery, commented Emir Roach, one of the leaders of QuPharm. Quantum computing is a completely new paradigm of computing, and our mission is to accelerate its implementation in life sciences. We are looking forward to working with the Pistoia Alliance and QED-C to help educate the life science and health care industry on the benefits.

The survey showed that more than four out of five respondents (82 percent) believe quantum computing will impact the industry within the next decade. The same proportion of respondents believe discovery and development will be first to benefit from quantum computing deployments in the biopharmaceutical industry.

Quantum computing is likely to have a profound impact on precision medicine, enabling accelerated genomics and proteomics correlation, as well as the calculation of multiple probabilities and outcomes. It will also help organizations deliver new molecules and therapies to market faster by streamlining the discovery process and enabling quantum energy calculations for molecules, as predicted in the Pistoia Alliances 2030 vision report. In the future, such technology could help the industry more quickly and accurately model disease pathways caused by novel coronaviruses.

The CoI has come together to help organizations address the key issues that need to be solved if the extraordinary benefits of quantum computing are to be realized. Potential barriers identified in the survey include a shortage of skills and a lack of access to quantum computing infrastructure (both cited by 28 percent of respondents) and the need for clearly defined use cases (31 percent).

There are myriad opportunities for quantum computing in life sciences and health care, and through this community of interest the pharmaceutical and quantum computing sectors can work together to identify and communicate areas of early and high potential, commented Celia Merzbacher, deputy director at QED-C. While quantum computing is still emerging, now is the time to jointly define use cases and challenges in pharmaceutical discovery and development that quantum computing can address. Better understanding of the pharmaceutical bottlenecks can accelerate quantum computing hardware and software development for overcoming those.

Given the interest in quantum computing amongst our members, we wanted to create the community of interest to address their needs and questions. We are now looking for more companies to get involved and commit resources to help us explore use cases, commented John Wise, a member of the Pistoia Alliance Operations Team supporting the new quantum computing CoI. The shared-risk, shared-reward advantages of pre-competitive collaboration are an ideal way for companies to explore the opportunities and challenges of quantum computing. Those organisations that do not begin to evaluate quantum computing now are at risk of being left behind once its value is realized. Those that are equipped to adopt the technology when it matures will be significantly ahead.

The research survey was conducted at the Community of Interests inaugural webinar in June 2020. More than 240 attendees from life science and quantum computing organisations across the US and Europe participated. To find out more about the CoI and help to steer future projects on quantum computing, please contact John Wise at the Pistoia Alliance via john.wise@pistoiaalliance.org or Celia Merzbacher via celia.merzbacher@sri.com.

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Almost One-Third of Life Science Companies Set to Begin Quantum Computing Evaluation This Year - Lab Manager Magazine

The unprecedented onset of a pandemic crisis such as COVID-19 has been instrumenting dominant alterations in the global growth trajectory of the Topological Quantum Computing Market. The event marks a catastrophic influence affecting myriad facets of the Topological Quantum Computing market in a multi-dimensional setting. The growth course that has been quite unabashed in the historical times, seems to have been struck suddenly in various unparalleled ways and means, which is therefore also affecting the normal growth prospects in the Topological Quantum Computing market. This thoughtfully compiled research report underpinning the impact of COVID-19 on the growth trajectory is therefore documented to encourage a planned rebound.

A thorough analytical review of the pertinent growth trends influencing the Topological Quantum Computing market has been demonstrated in the report. Adequate efforts have been directed to influence an unbiased and time-efficient market related decision amongst versatile market participants, striving to find a tight grip in the competition spectrum of the aforementioned Topological Quantum Computing market. The report also illustrates minute details in the Topological Quantum Computing market governing micro and macroeconomic factors that seem to have a dominant and long-term impact, directing the course of popular trends in the global Topological Quantum Computing market.

The study encompasses profiles of major companies operating in the Topological Quantum Computing Market. Key players profiled in the report includes:

MicrosoftIBMGoogleD-Wave SystemsAirbusRaytheonIntelHewlett PackardAlibaba Quantum Computing LaboratoryIonQ

The report is rightly designed to present multidimensional information about the current and past market occurrences that tend to have a direct implication on the onward growth trajectory of the Topological Quantum Computing market.

The following sections of this versatile report on the Topological Quantum Computing market specifically shed light on popular industry trends encompassing both market drivers as well as dominant trends that systematically affect the growth trajectory visibly. The report is a holistic, ready-to-use compilation of all major events and developments that replicate growth in the Topological Quantum Computing market. Besides presenting notable insights on Topological Quantum Computing market factors comprising above determinants, the report further in its subsequent sections of this detailed research report on Topological Quantum Computing market states information on regional segmentation.

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By the product type, the market is primarily split into

SoftwareHardwareService

By the end-users/application, this report covers the following segments

CivilianBusinessEnvironmentalNational SecurityOthers

In the subsequent sections of the report, readers are also presented with versatile understanding about the current state of geographical overview, encompassing various regional hubs that consistently keep witnessing growth promoting market developments directed by market veterans, aiming for ample competitive advantage, such that their footing remains strong and steady despite the cut throat competition characterizing the aforementioned Topological Quantum Computing market. Each of the market players profiled in the report have been analyzed on the basis of their company and product portfolios, to make logical deductions.

Global Topological Quantum Computing Geographical Segmentation Includes: North America (U.S., Canada, Mexico) Europe (U.K., France, Germany, Spain, Italy, Central & Eastern Europe, CIS) Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific) Latin America (Brazil, Rest of L.A.) Middle East and Africa (Turkey, GCC, Rest of Middle East)

Some Major TOC Points: Chapter 1. Report Overview Chapter 2. Global Growth Trends Chapter 3. Market Share by Key Players Chapter 4. Breakdown Data by Type and Application Chapter 5. Market by End Users/Application Chapter 6. COVID-19 Outbreak: Topological Quantum Computing Industry Impact Chapter 7. Opportunity Analysis in Covid-19 Crisis Chapter 9. Market Driving ForceAnd Many More

Continued

Research Methodology Includes:

The report systematically upholds the current state of dynamic segmentation of the Topological Quantum Computing market, highlighting major and revenue efficient market segments comprising application, type, technology, and the like that together coin lucrative business returns in the Topological Quantum Computing market.

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Target Audience:* Topological Quantum Computing Manufactures* Traders, Importers, and Exporters* Raw Material Suppliers and Distributors* Research and Consulting Firms* Government and Research Organizations* Associations and Industry Bodies

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Global Topological Quantum Computing Market Register a xx% CAGR in Terms of Revenue By 2025 With COVID-19 Outbreak: Microsoft, IBM, Google, D-Wave...

The Quantum Information Processing market growth prospects have been showing good great promise all over the world with immense growth potential in terms of revenue generation and this growth of the Quantum Information Processing market is expected to be huge by 2026.The growth of the market is driven by key factors such as manufacturing activity in accordance with the current market situation and demand that seems to be seeing a major upward trend in some time, risks of the market, acquisitions, new trends, assessment of the new technologies and their implementation.

Top Companies covering This Report :- Airbus, Anyon Systems, Cambridge Quantum Computing, D-Wave Systems, Google, Microsoft, IBM, Intel, QC Ware, Quantum, Rigetti Computing, Strangeworks.

This report has been detailed and is structured in a manner that covers all of the aspects required to gain a complete understanding of the pre-market conditions, current conditions as well as a well-measured forecast in order for the client to establish a strong position in the Quantum Information Processing market.

The report has been segmented and discussed in detail with the consideration of the COVID-19 situation, and is as per the examined essential aspects such as sales, revenue, market size, and other aspects that are crucial to post good growth numbers in the market and emerge as a leader in the market.

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Description:

In this report, we are providing our readers with the most updated data on the Quantum Information Processing market and as the international markets have been changing very rapidly over the past few years the markets have gotten tougher to get a grasp of and hence our analysts have prepared a detailed report while taking in consideration the history of the market and a very detailed forecast along with the market issues and their solution.

The given report has focused on the key aspects of the markets to ensure maximum benefit and growth potential for our readers and our extensive analysis of the market will help them achieve this much more efficiently. The report has been prepared by using primary as well as secondary analysis in accordance with porters five force analysis which has been a game-changer for many in the Quantum Information Processing market. The research sources and tools that we use are highly reliable and trustworthy. The report offers effective guidelines and recommendations for players to secure a position of strength in the Quantum Information Processing market. The newly arrived players in the market can up their growth potential by a great amount and also the current dominators of the market can keep up their dominance for a longer time by the use of our report.

Quantum Information Processing Market Type Coverage:

HardwareSoftware

Quantum Information Processing Market Application Coverage:

BFSITelecommunications and ITRetail and E-CommerceGovernment and DefenseHealthcareManufacturingEnergy and UtilitiesConstruction and EngineeringOthers

Market Segment by Regions, regional analysis covers

North America (United States, Canada, Mexico)

Asia-Pacific (China, Japan, Korea, India, Southeast Asia)

South America (Brazil, Argentina, Colombia, etc.)

Europe, Middle East and Africa (Germany, France, UK, Russia and Italy, Saudi Arabia, UAE, Egypt, Nigeria, South Africa)

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Competition analysis

As the markets have been advancing the competition has increased by manifold and this has completely changed the way the competition is perceived and dealt with and in our report, we have discussed the complete analysis of the competition and how the big players in the Quantum Information Processing market have been adapting to new techniques and what are the problems that they are facing.

Our report which includes the detailed description of mergers and acquisitions will help you to get a complete idea of the market competition and also give you extensive knowledge on how to excel ahead and grow in the market.

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Huge Investment in Quantum Information Processing Market Expected to Witness the Highest Growth 2026 | D-Wave Systems, Google, Microsoft, IBM, Intel,...

In this research, the analysts perform a thorough analysis of the globalQuantum Computing Market, taking into account key factors such as drivers, barriers, recent developments, opportunities, advances, and competitive landscape. This study offers a good picture of the global industrys current as well as possible scenarios. The researchers have deployed research techniques such as PESTLE and Porters Five Forces analysis. They also provided accurate data on the development, capacity, demand, expense, margin, and revenue of to help players gain a better understanding of the current and future overall market situation.

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Global Quantum Computing Market: Competitive Landscape

In order to keep their position in the market and combat competition, manufacturers across the globe have developed and implemented marketing strategies. These strategies include collaboration, mergers and acquisitions, product innovation, and others. These strategies have been studied by the researchers to understand the current market trend which is boosting the global market. Furthermore, it also helps anticipate how these trends are expected to affect the global market.

Key Players Mentioned in the Global Quantum Computing Market Research Report:

International Business Machines (IBM) Corporation, Google Inc, Microsoft Corporation, Qxbranch LLC, Cambridge Quantum Computing Ltd, 1QB Information Technologies Inc, QC Ware Corp., Magiq Technologies Inc, D-Wave Systems Inc, Rigetti Computing

Global Quantum Computing Market: Segmentation

The segmentation chapters help readers to understand business factors such as their products, accessible technologies, and the same applications. Such chapters are written in a way that explains their growth over the years and the direction they are likely to take in the years to come. The research report also provides insightful information on emerging trends that are likely to define these segments progress over the coming years.

Segmentation on the basis of component:

HardwareSoftwareServicesSegmentation on the basis of application:

SimulationOptimizationSamplingSegmentation on the basis of end-use industry:

DefenseHealthcare & pharmaceuticalsChemicalsBanking & financeEnergy & power

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Global Quantum Computing Market: Regional Segmentation

For a deeper understanding, the research report includes geographical segmentation of the global Quantum Computing market. It provides an assessment of the volatility of the political scenarios and is likely to make amends to the regulatory structures. This assessment provides an accurate analysis of the global markets regional growth.

(GCC Countries and Egypt) The Middle East and Africa

(the United States, Mexico, and Canada)- North America

(Brazil, etc.)- South America

(France, Turkey, Germany, Russia UK, Italy, etc.)- Europe

(Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)- Asia-Pacific

Key questions answered in the report:

What is the growth potential of the Quantum Computing market?

Which segment of the product is taking a lions share?

Which regional market will emerge as a front-runner in the years to come?

Which application segment is going to grow at a robust rate?

What are the growth opportunities that may emerge in Quantum Computing industry in the years to come?

What are the key challenges that the global Quantum Computing market may face in the future?

Which are the leading companies in the global Quantum Computing market?

Which key trends have a positive impact on market growth?

Which are the growth strategies considered by the players to sustain hold in the global Quantum Computing market?

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Global Quantum Computing Market: Research Methodology

The research methodologies used by the analysts play an integral role in the way the publication has been collated. Analysts have used primary and secondary research methodologies to create a comprehensive analysis. For an accurate and precise analysis of the global Quantum Computing market, analysts have bottom-up and top-down approaches.

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Quantum Computing Market In Depth Analysis on Trends, Growth, Opportunities and Forecast 2029 - Sound On Sound Fest

The new head of defense research and engineering comes from the White House with a relatively light resume.

Updated: 10:20a.m.

The Pentagons new 33-year-old head of research and engineering lacks a basic science degree but brings deep connections to Donald Trump and controversial Silicon Valley venture capitalist PeterThiel.

Defense officials announced Monday that Michael Kratsios,the White Houses chief technology officer, would serve as acting undersecretary for research and engineering, a post that oversees top-priority projects in hypersonics, quantum computing, microelectronics, and other fields.He will continue to serve in his White Houserole.

In seeking to fill this position we wanted someone with experience in identifying and developing new technologies and working closely with a wide range of industry partners, said Defense Secretary Mark Esper in a statement on Monday. We think Michael is the right person for this job and we are excited to have him on theteam.

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Be the first to receive updates.

Kratsios came to the White House in 2017 as deputy CTO, and moved up to CTO last year. He led efforts to further White House investment in artificial intelligence and quantum science and to expand U.S. partnerships in those areas. As the COVID-19 pandemic took hold, he helped launch a project to apply U.S. supercomputers to the U.Sresponse.

But Kratsios was a weird pick for these senior technical roles, according to one person who has served as both a senior White House and Defense Department official advising on technologyissues.

Kratsios graduated from Princeton with a bachelors degree in political science and a focus on ancient Greek democracy. The person hes replacing, Michael Griffin, holds a Ph.D. in aerospace engineering and served as a NASA administrator. Indeed, Kratsios will be less academically credentialled than most of the program-managers he oversees. So how did he gethere?

After Princeton, he went to work for Peter Thiel, soon becoming CFO of Clarium Capital Management, Thiels investment company. He then became chief of staff for the tech billionaire, who was an early backer of the Trump campaign and who has played a key role in the administrations approach totechnology.

Thiel-backed ventures like Anduril and Palantir are playing a growing role in the Defense Department. The former official said theoverlap between Thiel-backed defense contractors and his protege Kratsios need not be a cause for concern. The Department has spent years trying to improve its relationship with the private tech world from which Kratsios emerged. But the official said Kratsios might not prove to be the most effectiveambassador.

Its not clear to me that Kratsios is warming up Silicon Valley, the former official said. I dont know how the rest of Silicon Valley thinks ofKratsios.

Thiel has made a variety of enemies in the tech world and beyond; for example, he has slammed Google as being too accommodating toChina.

The development, however, is good news for the Peter Thiel portion of Silicon Valley, the former officialsaid.

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Peter Thiel's New Man In The Defense Department - Defense One

Computing companies are racing to develop next generation computing technologies to solve a myriad of problems ranging from integrating artificial intelligence (at the chipset, IC, and component level) and cognitive computing to improving the efficiency and effectiveness of supercomputers. There are many technologies involved, including distributed computing (swarm computing), computational collaboration (bio-computing), improving performance of existing supercomputers, and completely new computer architectures (Quantum Computing).

The GlobalNext Generation Computing Marketreport provides a holistic evaluation of the market for the forecast period. The report comprises various segments as well as an analysis of the trends and factors that are playing a substantial role in the market. These factors; the market dynamics involve the drivers, restraints, opportunities, and challenges through which the impact of these factors in the market is outlined. The drivers and restraints are intrinsic factors whereas opportunities and challenges are extrinsic factors of the market.

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By Top Market Players:ABM,Advanced Brain Monitoring,Amazon,Agilent Technologies,Alibaba Cloud,Google,Bosch,SAP,Huawei,Hewlett,IBM,Intel,Microsoft,Oracle,Samsung,Nokia,NEC,Emotiv,Cisco Systems,Toshiba,Fujitsu,Atos SE,Dell

The report begins with a brief introduction and market overview, in which the Next Generation Computing industry is first defined before estimating its market scope and size. Next, the report elaborates on the market scope and market size estimation. This is followed by an overview of the market segmentations such as type, application, and region. The drivers, limitations, and opportunities are listed for the Next Generation Computing industry, followed by industry news and policies.

The report includes an analysis of the growth rate of every segment with the help of charts and tables. In addition, the market across various regions is analyzed in the report, including North America, Europe, Asia-Pacific, and LAMEA. The report manifests the growth trends and future opportunities in every region.

Global Next Generation Computing market is presented to the readers as a holistic snapshot of the competitive landscape within the given forecast period. It presents a comparative detailed analysis of the all regional and player segments, offering readers a better knowledge of where areas in which they can place their existing resources and gauging the priority of a particular region in order to boost their standing in the global market.

The Global Next Generation Computing Market is gaining pace and businesses have started understanding the benefits of analytics in the present day highly dynamic business environment. The market has witnessed several important developments over the past few years, with mounting volumes of business data and the shift from traditional data analysis platforms to self-service business analytics being some of the most prominent ones.

By Type:Swarm Computing,Bio-computing,Quantum Computing

By Application:Small and Medium Enterprises,Large Enterprises

For the future period, sound forecasts on market value and volume are offered for each type and application. In the same period, the report also provides a detailed analysis of market value and consumption for each region. These insights are helpful in devising strategies for the future and take necessary steps. New project investment feasibility analysis and SWOT analysis are offered along with insights on industry barriers. Research findings and conclusions are mentioned at the end.

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Next Generation Computing Market Size Industry Insights, Top Trends, Drivers, Growth and Forecast To 2026 - 3rd Watch News