Machine Learning in Medical Imaging Market 2020 : Analysis by Geographical Regions, Type and Application Till 2025 | Zebra, Arterys, Aidoc, MaxQ AI -…

Global Machine Learning in Medical Imaging Industry: with growing significant CAGR during Forecast 2020-2025

Latest Research Report on Machine Learning in Medical Imaging Market which covers Market Overview, Future Economic Impact, Competition by Manufacturers, Supply (Production), and Consumption Analysis

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The market research report on the global Machine Learning in Medical Imaging industry provides a comprehensive study of the various techniques and materials used in the production of Machine Learning in Medical Imaging market products. Starting from industry chain analysis to cost structure analysis, the report analyzes multiple aspects, including the production and end-use segments of the Machine Learning in Medical Imaging market products. The latest trends in the pharmaceutical industry have been detailed in the report to measure their impact on the production of Machine Learning in Medical Imaging market products.

Leading key players in the Machine Learning in Medical Imaging market are Zebra, Arterys, Aidoc, MaxQ AI, Google, Tencent, Alibaba

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Product Types:, Supervised Learning, Unsupervised Learning, Semi Supervised Learning, Reinforced Leaning

By Application/ End-user:, Breast, Lung, Neurology, Cardiovascular, Liver

Regional Analysis For Machine Learning in Medical ImagingMarket

North America(the 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.)The Middle East and Africa(Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

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This report comes along with an added Excel data-sheet suite taking quantitative data from all numeric forecasts presented in the report.

Research Methodology:The Machine Learning in Medical Imagingmarket has been analyzed using an optimum mix of secondary sources and benchmark methodology besides a unique blend of primary insights. The contemporary valuation of the market is an integral part of our market sizing and forecasting methodology. Our industry experts and panel of primary members have helped in compiling appropriate aspects with realistic parametric assessments for a comprehensive study.

Whats in the offering: The report provides in-depth knowledge about the utilization and adoption of Machine Learning in Medical Imaging Industries in various applications, types, and regions/countries. Furthermore, the key stakeholders can ascertain the major trends, investments, drivers, vertical players initiatives, government pursuits towards the product acceptance in the upcoming years, and insights of commercial products present in the market.

Full Report Link @ https://grandviewreport.com/industry-growth/Machine-Learning-in-Medical-Imaging-Market-21159

Lastly, the Machine Learning in Medical Imaging Market study provides essential information about the major challenges that are going to influence market growth. The report additionally provides overall details about the business opportunities to key stakeholders to expand their business and capture revenues in the precise verticals. The report will help the existing or upcoming companies in this market to examine the various aspects of this domain before investing or expanding their business in the Machine Learning in Medical Imaging market.

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Machine Learning in Medical Imaging Market 2020 : Analysis by Geographical Regions, Type and Application Till 2025 | Zebra, Arterys, Aidoc, MaxQ AI -...

Impact of COVID-19 on Machine Learning & Big Data Analytics Education Market 2020-2027 Size and Share by Key Players Like Cognizant, Microsoft…

The research report on Machine Learning & Big Data Analytics Education Market gives the todays industry data and future developments, allowing you to understand the products and quit customers using sales increase and profitability of the market. The record gives an in depth analysis of key drivers, leading market key players, key segments, and regions. Besides this, the experts have deeply studied one-of-a-kind geographical areas and presented aggressive situation to assist new entrants, main market players, and buyers decide emerging economies. These insights provided in the record would advantage market players to formulate strategies for the destiny and benefit a robust role within the worldwide market.

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The Global market for Machine Learning & Big Data Analytics Education is estimated to grow at a CAGR of roughly X.X% in the next 8 years, and will reach USD X.X million in 2027, from USD X.X million in 2020.Aimed to provide most segmented consumption and sales data of different types of Machine Learning & Big Data Analytics Education, downstream consumption fields and competitive landscape in different regions and countries around the world, this report analyzes the latest market data from the primary and secondary authoritative source.

The report also tracks the latest market dynamics, such as driving factors, restraining factors, and industry news like mergers, acquisitions, and investments. It provides market size (value and volume), market share, growth rate by types, applications, and combines both qualitative and quantitative methods to make micro and macro forecasts in different regions or countries.The report can help to understand the market and strategize for business expansion accordingly. In the strategy analysis, it gives insights from marketing channel and market positioning to potential growth strategies, providing in-depth analysis for new entrants or exists competitors in the Machine Learning & Big Data Analytics Education industry.The report focuses on the top players in terms of profiles, product analysis, sales, price, revenue, and gross margin.

Major players covered in this report:*Cognizant*Microsoft Corporation*Google*Metacog, Inc.,*IBM Corporation*Querium Corporation.*DreamBox Learning*Bridge-U*Jellynote*Quantum Adaptive Learning, LLC*Jenzabar, Inc.,*Third Space Learning*Blackboard, Inc.,*Pearson*Fishtree*Century-Tech Ltd*Knewton, Inc.,

By Type:*Machine Learning*Big Data Analytics

By Application:*Higher Education*K-12 Education*Corporate Training

Geographically, the regional consumption and value analysis by types, applications, and countries are included in the report. Furthermore, it also introduces the major competitive players in these regions.Major regions covered in the report:*North America*Europe*Asia-Pacific*Latin America*Middle East & Africa

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2015-2026) of the following regions are covered in Chapter 5, 6, 7, 8, 9, 10, 13:*North America (Covered in Chapter 6 and 13): United States, Canada, Mexico

*Europe (Covered in Chapter 7 and 13): Germany, UK, France, Italy, Spain, Russia, Others

*Asia-Pacific (Covered in Chapter 8 and 13): China, Japan, South Korea, Australia, India, Southeast Asia, Others

*Middle East and Africa (Covered in Chapter 9 and 13): Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Others

*South America (Covered in Chapter 10 and 13): Brazil, Argentina, Columbia, Chile, Others

Years considered for this report:*Historical Years: 2015-2019*Base Year: 2019*Estimated Year: 2020*Forecast Period: 2020-2027

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Impact of COVID-19 on Machine Learning & Big Data Analytics Education Market 2020-2027 Size and Share by Key Players Like Cognizant, Microsoft...

news and analysis for omnichannel retailers – Retail Technology Innovation Hub

Machine learning algorithms will learn patterns from the past data and predict trends and best price. These algorithms can predict the best price, discount price and promotional price based on competition, macroeconomic variables, seasonality etc.

To find out the correct pricing in real-time retailers follow the following steps:

Gather input data

In order to build a machine learning algorithm, retailers collect various data points from the customers. These are:

Transactional data

This includes the sales history of each customer and the products, which they have bought in the past.

Product description

The brands, product category, style, photos and the selling price of the previously sold products are collected. Past promotions and campaigns are also analysed to find the effect of price changes on each category.

Customer details

Demographic details and customer feedback are gathered.

Competition and inventory

Retailers also try to find the data regarding the price of products sold by their competitors and supply chain and inventory data.

Depending on the set of key performance indicators defined by the retailers, the relevant data is filtered.

For every industry, pricing would involve different goals and constraints. In terms of the dynamic nature, the retail industry can be compared to the casino industry where machine learning is involved inonline live dealer casino games too.

Like casinos, retail also has the target of profit maximisation and retention of customer loyalty. Each of these goals and constraints can be fed to a machine learning algorithm to generate dynamic prices of products.

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news and analysis for omnichannel retailers - Retail Technology Innovation Hub

AI in Machine Learning Market to Witness Tremendous Growth in Forecasted Period 2020-2027 – NJ MMA News

Reports published inMarket Research Incfor the AI in Machine Learning market are spread out over several pages and provide the latest industry data, market future trends, enabling products and end users to drive revenue growth and profitability. Industry reports list and study key competitors and provide strategic industry analysis of key factors affecting market dynamics. This report begins with an overview of the AI in Machine Learning market and is available throughout development. It provides a comprehensive analysis of all regional and major player segments that provide insight into current market conditions and future market opportunities along with drivers, trend segments, consumer behavior, price factors and market performance and estimates over the forecast period.

Request a pdf copy of this report athttps://www.marketresearchinc.com/request-sample.php?id=16243

Key Strategic Manufacturers

:GOOGLE, IBM, BAIDU, SOUNDHOUND, ZEBRA MEDICAL VISION, PRISMA, Company Profile, Main Business Information, SWOT Analysis, Sales, Revenue, Price and Gross Margin, Market Share, TensorFlow, Caffe2 & Apache MXNet

(Market Size & Forecast, Different Demand Market by Region, Main Consumer Profile etc

The report gives a complete insight of this industry consisting the qualitative and quantitative analysis provided for this market industry along with prime development trends, competitive analysis, and vital factors that are predominant in the AI in Machine Learning Market.

The report also targets local markets and key players who have adopted important strategies for business development. The data in the report is presented in statistical form to help you understand the mechanics. The AI in Machine Learning market report gathers thorough information from proven research methodologies and dedicated sources in many industries.

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Key Objectives of AI in Machine Learning Market Report: Study of the annual revenues and market developments of the major players that supply AI in Machine Learning Analysis of the demand for AI in Machine Learning by component Assessment of future trends and growth of architecture in the AI in Machine Learning market Assessment of the AI in Machine Learning market with respect to the type of application Study of the market trends in various regions and countries, by component, of the AI in Machine Learning market Study of contracts and developments related to the AI in Machine Learning market by key players across different regions Finalization of overall market sizes by triangulating the supply-side data, which includes product developments, supply chain, and annual revenues of companies supplying AI in Machine Learning across the globe.

Furthermore, the years considered for the study are as follows:

Historical year 2015-2019

Base year 2019

Forecast period 2020 to 2026

Table of Content:

AI in Machine Learning Market Research ReportChapter 1: Industry OverviewChapter 2: Analysis of Revenue by ClassificationsChapter 3: Analysis of Revenue by Regions and ApplicationsChapter 6: Analysis of Market Revenue Market Status.Chapter 4: Analysis of Industry Key ManufacturersChapter 5: Marketing Trader or Distributor Analysis of Market.Chapter 6: Development Trend of AI in Machine Learning market

Continue for TOC

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AI in Machine Learning Market to Witness Tremendous Growth in Forecasted Period 2020-2027 - NJ MMA News

What’s the state of quantum computing? Led by IBM & Amazon it’s developing rapidly – WRAL Tech Wire

Editors note: Stephanie Long is Senior Analyst with Technology Business Research.

HAMPTON, N.H. Like IBM did with its Selectric typewriters in the 1960s, the company is successfully weaving its quantum computing thread through myriad aspects of the greater quantum ecosystem, underpinned by strategic sponsorships and the inclusion of partners in the IBM Quantum Experience.

Amazon Web Services (AWS) is pushing back on this approach by offering a vendor-agnostic view of quantum cloud computing.

Academia has also thrown its hat into the ring with ongoing innovation and advancements in quantum computing.

The competitive landscape of quantum computing has begun to take on the look and feel of the early classical computing world; however, the modern industry has addressed the mistakes made with classical computing, and therefore progress can be more formulaic and swift.

August 2020 developments are starting to tie pieces of investments together to show a glimpse of when the post-quantum world may come, and as advancements continue the future state appears closer on the horizon than previously thought.

Duke joins $115M program to focus on development of quantum computing

If you would like more detailed information around the quantum computing market, please inquire about TBRsQuantum Computing Market Landscape,a semiannual deep dive into the quantum computing market. Our most recent version, which focused on services, was released in June. Look for our next iteration in December, focused on middleware.

(C) TBR

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What's the state of quantum computing? Led by IBM & Amazon it's developing rapidly - WRAL Tech Wire

Verizon tunes up quantum-based technology trial in Washington D.C. to bolster security – FierceTelecom

In order to better keep communications safe and secure from hackers, Verizon recently conducted a trial of quantum key distribution (QKD) in Washington D.C. Verizon said the successful trial positioned it as one of the first carriers in the U.S. to pilot the use of QKD.

Quantum cryptography could provide a solution for the vulnerability of current cryptographic key implementations. Today, cryptographic techniques encrypt data using a secure key, which is only known to the parties using that key for decrypting the messages between them.

Those cryptographic techniques for key generation are based on highly complex mathematical problems that require long calculations to be resolved. With the growth of computational capacity, the time required to solve these problems becomes shorter, which reduces the security of the keys.

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With the advent of quantum computers, the principles of quantum mechanics could be applied to break the keys used in today's security implementations. By contrast, QKD could be applied to exchange a key between the two ends of a communication. QKD provides protection against the threat posed by quantum computing to current cryptographic algorithms and provides a high level of security for the exchange of data.

RELATED: Telefnica, Huawei trial quantum cryptography on optical network using SDN

Two years ago, Telefnica and Huawei conducted a successful field trial of quantum cryptography on commercial optical networks by using SDN.

In Verizon's QKD trial, live video was captured outside of three Verizon locations in the D.C. area, including the Washington DC Executive Briefing Center, the 5G Lab in D.C and Verizons Ashburn, Virginia office. Using a QKD network, quantum keys were created and exchanged over a fiber network between Verizon's locations.

In the trial, video streams were encrypted and delivered more securely allowing the recipient to see the video in real-time while instantly exposing hackers. A QKD network derives cryptographic keys using the quantum properties of photons to prevent against eavesdropping.

Verizon also demonstrated that data could be further secured with keys generated using a Quantum Random Number Generator (QRNG) that, as the name suggests, creates random numbers that cant be predicted. With QKD, encryption keys are continuously generated and are immune to attacks because any disruption to the channel breaks the quantum state of photons, which signals that eavesdroppers are present.

"The use of quantum mechanics is a great step forward in data security, said IDC Analyst Christina Richmond, in a statement. Verizon's own tests, as well other industry testing, have shown that deriving 'secret keys' between two entities via light photons effectively blocks perfect cloning by an eavesdropper if a key intercept is attempted.

"Current technological breakthroughs have proven that both the quantum channel and encrypted data channel can be sent over a single optical fiber. Verizon has demonstrated this streamlined approach brings greater efficiency for practical large-scale implementation allowing keys to be securely shared over wide-ranging networks.

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Verizon tunes up quantum-based technology trial in Washington D.C. to bolster security - FierceTelecom

What is the quantum internet? Everything you need to know about the weird future of quantum networks – ZDNet

It might all sound like a sci-fi concept, but building quantum networks is a key ambition for many countries around the world. Recently the US Department of Defense (DoE) published the first blueprint of its kind, laying out a step-by-step strategy to make the quantum internet dream come true, at least in a very preliminary form, over the next few years.

The US joined the EU and China in showing a keen interest in the concept of quantum communications. But what is the quantum internet exactly, how does it work, and what are the wonders that it can accomplish?

WHAT IS THE QUANTUM INTERNET?

The quantum internet is a network that will let quantum devices exchange some information within an environment that harnesses the weird laws of quantum mechanics. In theory, this would lend the quantum internet unprecedented capabilities that are impossible to carry out with today's web applications.

SEE: Managing AI and ML in the enterprise 2020: Tech leaders increase project development and implementation (TechRepublic Premium)

In the quantum world, data can be encoded in the state of qubits, which can be created in quantum devices like a quantum computer or a quantum processor. And the quantum internet, in simple terms, will involve sending qubits across a network of multiple quantum devices that are physically separated. Crucially, all of this would happen thanks to the whacky properties that are unique to quantum states.

That might sound similar to the standard internet. But sending qubits around through a quantum channel, rather than a classical one, effectively means leveraging the behavior of particles when taken at their smallest scale so-called "quantum states", which have caused delight and dismay among scientists for decades.

And the laws of quantum physics, which underpin the way information will be transmitted in the quantum internet, are nothing short of unfamiliar. In fact, they are strange, counter-intuitive, and at times even seemingly supernatural.

And so to understand how the quantum ecosystem of the internet 2.0 works, you might want to forget everything you know about classical computing. Because not much of the quantum internet will remind you of your favorite web browser.

WHAT TYPE OF INFORMATION CAN WE EXCHANGE WITH QUANTUM?

In short, not much that most users are accustomed to. At least for the next few decades, therefore, you shouldn't expect to one day be able to jump onto quantum Zoom meetings.

Central to quantum communication is the fact that qubits, which harness the fundamental laws of quantum mechanics, behave very differently to classical bits.

As it encodes data, a classical bit can effectively only be one of two states. Just like a light switch has to be either on or off, and just like a cat has to be either dead or alive, so does a bit have to be either 0 or 1.

Not so much with qubits. Instead, qubits are superposed: they can be 0 and 1 simultaneously, in a special quantum state that doesn't exist in the classical world. It's a little bit as if you could be both on the left-hand side and the right-hand side of your sofa, in the same moment.

The paradox is that the mere act of measuring a qubit means that it is assigned a state. A measured qubit automatically falls from its dual state, and is relegated to 0 or 1, just like a classical bit.

The whole phenomenon is called superposition, and lies at the core of quantum mechanics.

Unsurprisingly, qubits cannot be used to send the kind of data we are familiar with, like emails and WhatsApp messages. But the strange behavior of qubits is opening up huge opportunities in other, more niche applications.

QUANTUM (SAFER) COMMUNICATIONS

One of the most exciting avenues that researchers, armed with qubits, are exploring, is security.

When it comes to classical communications, most data is secured by distributing a shared key to the sender and receiver, and then using this common key to encrypt the message. The receiver can then use their key to decode the data at their end.

The security of most classical communication today is based on an algorithm for creating keys that is difficult for hackers to break, but not impossible. That's why researchers are looking at making this communication process "quantum". The concept is at the core of an emerging field of cybersecurity called quantum key distribution (QKD).

QKD works by having one of the two parties encrypt a piece of classical data by encoding the cryptography key onto qubits. The sender then transmits those qubits to the other person, who measures the qubits in order to obtain the key values.

SEE: The UK is building its first commercial quantum computer

Measuring causes the state of the qubit to collapse; but it is the value that is read out during the measurement process that is important. The qubit, in a way, is only there to transport the key value.

More importantly, QKD means that it is easy to find out whether a third party has eavesdropped on the qubits during the transmission, since the intruder would have caused the key to collapse simply by looking at it.

If a hacker looked at the qubits at any point while they were being sent, this would automatically change the state of the qubits. A spy would inevitably leave behind a sign of eavesdropping which is why cryptographers maintain that QKD is "provably" secure.

SO, WHY A QUANTUM INTERNET?

QKD technology is in its very early stages. The "usual" way to create QKD at the moment consists of sending qubits in a one-directional way to the receiver, through optic-fibre cables; but those significantly limit the effectiveness of the protocol.

Qubits can easily get lost or scattered in a fibre-optic cable, which means that quantum signals are very much error-prone, and struggle to travel long distances. Current experiments, in fact, are limited to a range of hundreds of kilometers.

There is another solution, and it is the one that underpins the quantum internet: to leverage another property of quantum, called entanglement, to communicate between two devices.

When two qubits interact and become entangled, they share particular properties that depend on each other. While the qubits are in an entangled state, any change to one particle in the pair will result in changes to the other, even if they are physically separated.The state of the first qubit, therefore, can be "read" by looking at the behavior of its entangled counterpart. That's right: even Albert Einstein called the whole thing "spooky action at a distance".

And in the context of quantum communication, entanglement could in effect, teleport some information from one qubit to its entangled other half, without the need for a physical channel bridging the two during the transmission.

HOW DOES ENTANGLEMENT WORK?

The very concept of teleportation entails, by definition, the lack of a physical network bridging between communicating devices. But it remains that entanglement needs to be created in the first place, and then maintained.

To carry out QKD using entanglement, it is necessary to build the appropriate infrastructure to first create pairs of entangled qubits, and then distribute them between a sender and a receiver. This creates the "teleportation" channel over which cryptography keys can be exchanged.

Specifically, once the entangled qubits have been generated, you have to send one half of the pair to the receiver of the key. An entangled qubit can travel through networks of optical fibre, for example; but those are unable to maintain entanglement after about 60 miles.

Qubits can also be kept entangled over large distances via satellite, but covering the planet with outer-space quantum devices is expensive.

There are still huge engineering challenges, therefore, to building large-scale "teleportation networks" that could effectively link up qubits across the world. Once the entanglement network is in place, the magic can start: linked qubits won't need to run through any form of physical infrastructure anymore to deliver their message.

During transmission, therefore, the quantum key would virtually be invisible to third parties, impossible to intercept, and reliably "teleported" from one endpoint to the next. The idea will resonate well with industries that deal with sensitive data, such as banking, health services or aircraft communications. And it is likely that governments sitting on top secret information will also be early adopters of the technology.

WHAT ELSE COULD WE DO WITH THE QUANTUM INTERNET?

'Why bother with entanglement?' you may ask. After all, researchers could simply find ways to improve the "usual" form of QKD. Quantum repeaters, for example, could go a long way in increasing communication distance in fibre-optic cables, without having to go so far as to entangle qubits.

That is without accounting for the immense potential that entanglement could have for other applications. QKD is the most frequently discussed example of what the quantum internet could achieve, because it is the most accessible application of the technology. But security is far from being the only field that is causing excitement among researchers.

The entanglement network used for QKD could also be used, for example, to provide a reliable way to build up quantum clusters made of entangled qubits located in different quantum devices.

Researchers won't need a particularly powerful piece of quantum hardware to connect to the quantum internet in fact, even a single-qubit processor could do the job. But by linking together quantum devices that, as they stand, have limited capabilities, scientists expect that they could create a quantum supercomputer to surpass them all.

SEE: Guide to Becoming a Digital Transformation Champion (TechRepublic Premium)

By connecting many smaller quantum devices together, therefore, the quantum internet could start solving the problems that are currently impossible to achieve in a single quantum computer. This includes expediting the exchange of vast amounts of data, and carrying out large-scale sensing experiments in astronomy, materials discovery and life sciences.

For this reason, scientists are convinced that we could reap the benefits of the quantum internet before tech giants such as Google and IBM even achieve quantum supremacy the moment when a single quantum computer will solve a problem that is intractable for a classical computer.

Google and IBM's most advanced quantum computers currently sit around 50 qubits, which, on its own, is much less than is needed to carry out the phenomenal calculations needed to solve the problems that quantum research hopes to address.

On the other hand, linking such devices together via quantum entanglement could result in clusters worth several thousands of qubits. For many scientists, creating such computing strength is in fact the ultimate goal of the quantum internet project.

WHAT COULDN'T WE DO WITH THE QUANTUM INTERNET?

For the foreseeable future, the quantum internet could not be used to exchange data in the way that we currently do on our laptops.

Imagining a generalized, mainstream quantum internet would require anticipating a few decades (or more) of technological advancements. As much as scientists dream of the future of the quantum internet, therefore, it is impossible to draw parallels between the project as it currently stands, and the way we browse the web every day.

A lot of quantum communication research today is dedicated to finding out how to best encode, compress and transmit information thanks to quantum states. Quantum states, of course, are known for their extraordinary densities, and scientists are confident that one node could teleport a great deal of data.

But the type of information that scientists are looking at sending over the quantum internet has little to do with opening up an inbox and scrolling through emails. And in fact, replacing the classical internet is not what the technology has set out to do.

Rather, researchers are hoping that the quantum internet will sit next to the classical internet, and would be used for more specialized applications. The quantum internet will perform tasks that can be done faster on a quantum computer than on classical computers, or which are too difficult to perform even on the best supercomputers that exist today.

SO, WHAT ARE WE WAITING FOR?

Scientists already know how to create entanglement between qubits, and they have even been successfully leveraging entanglement for QKD.

China, a long-time investor in quantum networks, has broken records on satellite-induced entanglement. Chinese scientists recently established entanglement and achieved QKD over a record-breaking 745 miles.

The next stage, however, is scaling up the infrastructure. All experiments so far have only connected two end-points. Now that point-to-point communication has been achieved, scientists are working on creating a network in which multiple senders and multiple receivers could exchange over the quantum internet on a global scale.

The idea, essentially, is to find the best ways to churn out lots of entangled qubits on demand, over long distances, and between many different points at the same time. This is much easier said than done: for example, maintaining the entanglement between a device in China and one in the US would probably require an intermediate node, on top of new routing protocols.

And countries are opting for different technologies when it comes to establishing entanglement in the first place. While China is picking satellite technology, optical fibre is the method favored by the US DoE, which is now trying to create a network of quantum repeaters that can augment the distance that separates entangled qubits.

In the US, particles have remained entangled through optical fibre over a 52-mile "quantum loop" in the suburbs of Chicago, without the need for quantum repeaters. The network will soon be connected to one of the DoE's laboratories to establish an 80-mile quantum testbed.

In the EU, the Quantum Internet Alliance was formed in 2018 to develop a strategy for a quantum internet, and demonstrated entanglement over 31 miles last year.

For quantum researchers, the goal is to scale the networks up to a national level first, and one day even internationally. The vast majority of scientists agree that this is unlikely to happen before a couple of decades. The quantum internet is without doubt a very long-term project, with many technical obstacles still standing in the way. But the unexpected outcomes that the technology will inevitably bring about on the way will make for an invaluable scientific journey, complete with a plethora of outlandish quantum applications that, for now, cannot even be predicted.

Read more:
What is the quantum internet? Everything you need to know about the weird future of quantum networks - ZDNet

Assistant director of NSFs Computer and Information Science and Engineering to give virtual talk Sept. 11 – Vanderbilt University News

By Jenna Somers and Jane Hirtle

Margaret Martonosi, assistant director of Computer and Information Science and Engineering at the National Science Foundation, will speak at a virtual campus visit on Friday, Sept. 11, from 2 to 4 p.m. CT hosted by Vice Provost for Research Padma Raghavan. Faculty, students and staff are invited to register to attend the presentation and take part in an open discussion and Q&A session about CISE and its key focus areas, including cyberinfrastructure, computing and communication, computer and network systems and information and intelligent systems, as well as funding opportunities and NSF future directions in these areas.

Register for the event here. >>

I am pleased to welcome my close colleague Dr. Margaret Martonosi to Vanderbilt, said Raghavan, who serves as a member of the advisory boards for the CISE Directorate and the Office of Advanced Cyberinfrastructure. Margaret is a preeminent computer scientist who has made foundational contributions to computer architecture and hardware-software interfaces in both classical and quantum computing systems. Now as the assistant director of CISE, she stewards the development of strategy and programs to strengthen fundamental research and education in order to advance U.S. leadership in computing, communications and information science and engineering. I am delighted to welcome her to share her insights with the Vanderbilt community and join us in a roundtable discussion.

Under Martonosis guidance, CISE also strengthens innovation in research cyberinfrastructure and promotes inclusive, transparent participation in an information-based society to ensure the success of the computer and information technology workforce in the global market.

Along with the Office of the Assistant Director, CISE includes the Office of Advanced Cyberinfrastructure, Division of Computing and Communication Foundations, Division of Computer and Network Systems, and the Division of Information and Intelligent Systems. Each of these units manages a portfolio of proposal competitions and grants while collaborating across units and directorates to achieve the mission of CISE.

Noteworthy examples of CISE-funded programs include Broadening Participation in Computing Alliances, which aims to increase the diversity and amount of college graduates in computing and computationally-intensive disciplines; the Foundations of Emerging Technologies, which supports fundamental research in disruptive technologies and models in computing and communication; and the Big Data Regional Innovation Hubs, which engage state and local government officials, local industry and nonprofits and regional academic institutions to use big data research to address regional concerns.

Most recently, NSF partnered with the Department of Agriculture, the Department of Homeland Security and the Department of Transportation to launch the National Artificial Intelligence (AI) Research Institutes. As the name suggests, these institutes will serve to accelerate AI research nationwide, developing the U.S. workforce and protecting and advancing society across many aspects of daily life from education to natural disaster preparedness.

While serving as the assistant director of CISE, Martonosi is on leave from Princeton University, where she is the Hugh Trumbull Adams 35 Professor of Computer Science. Her research focuses on computer architecture and mobile computing. Martonosi has received numerous awards, including the 2019 SIGARCH Alan D. Berenbaum Distinguished Service Award, the 2018 IEEE Computer Society Technical Achievement Award, and the 2010 Princeton University Graduate Mentoring Award, among many others. Additionally, she is an elected member of the American Academy of Arts and Sciences and a fellow of the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers.

Please visit CISE to learn more about its programs, funding opportunities and awards.

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Assistant director of NSFs Computer and Information Science and Engineering to give virtual talk Sept. 11 - Vanderbilt University News

The Quantum Dream: Are We There Yet? – Toolbox

The emergence of quantum computing has led industry heavyweights to fast track their research and innovations. This week, Google conducted the largest chemical simulation on a quantum computer to date. The U.S. Department of Energy, on the other hand, launched five new Quantum Information Science (QIS) Research Centers. Will this accelerate quantum computings progress?

Quantum technology is the next big wave in the tech landscape. As opposed to traditional computers where all the information emails, tweets, YouTube videos, and Facebook photos are streams of electrical pulses in binary digits, 1s and 0s; quantum computers rely on quantum bits or qubits to store information. Qubits are subatomic particles, such as electrons or photons which change their state regularly. Therefore, they can be 1s and 0s at the same time. This enables quantum computers to run multiple complex computational tasks simultaneously and faster when compared to digital computers, mainframes, and servers.

Introduced in the 1980s, quantum computing can unlock the complexities across different industries much faster than traditional computers. A quantum computer can decipher complex encryption systems that can easily impact digital banking, cryptocurrencies, and e-commerce sectors, which heavily depend on encrypted data. Quantum computers can expedite the discovery of new medicines, aid in climate change, power AI, transform logistics, and design new materials. In the U.S., technology giants, including IBM, Google, Honeywell, Microsoft, Intel, IonQ, and Rigetti Computing, are leading the race to build quantum computers and gain a foothold in the quantum computing space. Whereas Alibaba, Baidu, Huawei are leading companies in China.

For a long time, the U.S. and its allies, such as Japan and Germany, had been working hard to compete with China to dominate the quantum technology space. In 2018, the U.S. government released the National Strategy Overview for Quantum Information Science to reduce technical skills gaps and accelerate quantum computing research and development.

In 2019, Google claimed quantum supremacy for supercomputers when the companys Sycamore processor performed specific tasks in 200 seconds, which would have taken a supercomputer 10,000 years to complete. In the same year, Intel rolled out Horse Ridge, a cryogenic quantum control chip, to reduce the quantum computing complexities and accelerate quantum practicality.

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Whats 2020 Looking Like For Quantum Computing?

In July 2020, IBM announced a research partnership with the Japanese business and academia to advance quantum computing innovations. This alliance will deepen ties between the countries and build an ecosystem to improve quantum skills and advance research and development.

More recently, in June 2020, Honeywell announced the development of the worlds highest-performing quantum computer. AWS, Microsoft, and several other IaaS providers have announced quantum cloud services, an initiative to advance quantum computing adoption. In August 2020, AWS announced the general availability of its Amazon Braket, a quantum cloud service that allows developers to design, develop, test, and run quantum algorithms.

Since last year, auto manufacturers, such as Daimler and Volkswagen have been leveraging quantum computers to identify new methods to improve electric vehicle battery performance. Pharmaceutical companies are also using the technology to develop new medicines and drugs.

Last week, the Google AI Quantum team used their quantum processor, Sycamore, to simulate changes in the configuration of a chemical molecule, diazene. During the process, the computer was able to describe the changes in the positions of hydrogen accurately. The computer also gave an accurate description of the binding energy of hydrogen in bigger chains.

If quantum computers develop the ability to predict chemical processes, it would advance the development of a wide range of new materials with unknown properties. Current quantum computers, unfortunately, lack the augmented scaling required for such a task. Although todays computers are not ready to take on such a challenge yet, computer scientists hope to accomplish this in the near future as tech giants like Google invest in quantum computing-related research.

Tech news: Will Googles Nearby Share Have Anything Transformative to Offer?

It, therefore, came as a relief to many computer scientists when the U.S. Department of Energy announced an investment of $625 million over the next five years for five newly formed Quantum Information Science (QIS) Research Centers in the U.S. The newly formed hubs are an amalgam of research universities, national labs, and tech titans in quantum computing. Each of the research hubs is led by the Energy Departments Argonne National Laboratory, Oak Ridge National Laboratory, Brookhaven National Laboratory, Fermi National Laboratory, and Lawrence Berkeley National Laboratory; powered by Microsoft, IBM, Intel, Riggeti, and ColdQuanta. This partnership aims to advance quantum computing commercialization.

Chetan Nayak, general manager of Quantum Hardware at Microsoft, says, While quantum computing will someday have a profound impact, todays quantum computing systems are still nascent technologies. To scale these systems, we must overcome a number of scientific challenges. Microsoft has been tackling these challenges head-on through our work towards developing topological qubits, classical information processing devices for quantum control, new quantum algorithms, and simulations.

At the start of this year, Daniel Newman, principal analyst and founding partner at Futurum Research, predicted that 2020 will be a big year for investors and Silicon Valley to invest in quantum computing companies. He said, It will be incredibly impactful over the next decade, and 2020 should be a big year for advancement and investment.

Quantum computing is still in the development phase, and the lack of suppliers and skilled researchers might be one of the influential factors in its establishment. However, if tech giants, and researchers continue to collaborate on a large scale, quantum technology can turbocharge innovation at a large scale.

What are your thoughts on the progress of quantum computing? Comment below or let us know on LinkedIn, Twitter, or Facebook. Wed love to hear from you!

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The Quantum Dream: Are We There Yet? - Toolbox

Atos helps researchers and students to experiment with quantum algorithms by offering free, universal access to myQLM – Stockhouse

Paris, September 3, 2020 Atos, a global leader in digital transformation, now provides free, universal access to myQLM, its program providing researchers, students and developers with quantum programming tools. Launched in 2019 and initially reserved to Atos Quantum Learning Machine (Atos QLM) users, myQLM aims to democratize access to quantum simulation and encourage innovation in quantum computing. By allowing all researchers, students and developers worldwide to download and use myQLM, Atos moves one step further forward in its commitment to empower the quantum computing community.

Quantum computing has the potential to change the world as we know it by spurring breakthroughs in healthcare, environmental sustainability, industrial processes or finance. The current race to develop a commercially viable quantum computer has been instrumental in increasing awareness of the field worldwide but the quantum revolution requires more than just hardware. Training of students, professors, engineers and researchers needs to be boosted to pave the way for the emergence of the new programming languages, algorithms and tools all essentials in harnessing the true power of quantum computing.

Using myQLM, anyone can explore the capabilities of quantum computing, from experimenting with quantum programming to launching simulations of up to 20 qubits directly on their own computer or even larger simulations on the Atos QLM.

”The shortage of skilled experts is one of the next greatest challenges to the development of quantum technologies. By opening up the access to our quantum programming environment myQLM, we hope to help train the next generation of computer scientists and researchers and foster an active community that will shape the future of quantum computing. We invite everyone to download myQLM today and join us in this life-changing adventure”, said Agns Boudot, Senior Vice President, Head of HPC & Quantum at Atos.

myQLM comes with a complete set of tools:

Atos, a pioneer in quantum solutions

Atos’ ambitious program to anticipate the future of quantum computing the Atos Quantum’ program was launched in November 2016. As a result of this initiative, Atos was the first organization to offer a quantum noisy simulation module within its Atos QLM offer. Launched in 2017, Atos QLM is being used in numerous countries worldwide including Austria, Finland, France, Germany, India, Italy, Japan, the Netherlands, Senegal, UK and the United States, empowering major research programs in various sectors like industry or energy. Recently, Atos extended its portfolio of quantum solutions with Atos QLM Enhanced (Atos QLM E), a new GPU-accelerated range of Atos QLM.

Learn more about myQLM and join our community by visiting the dedicated website: https://atos.net/en/lp/myqlm

***

About Atos

Atos is a global leader in digital transformation with 110,000 employees in 73 countries and annual revenue of 12 billion. European number one in Cloud, Cybersecurity and High-Performance Computing, the Group provides end-to-end Orchestrated Hybrid Cloud, Big Data, Business Applications and Digital Workplace solutions. The Group is the Worldwide Information Technology Partner for the Olympic & Paralympic Games and operates under the brands Atos, Atos|Syntel, and Unify. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index.

The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Press contact Marion Delmas | marion.delmas@atos.net | +33 6 37 63 91 99

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Atos helps researchers and students to experiment with quantum algorithms by offering free, universal access to myQLM - Stockhouse

How Amazon Quietly Powers The Internet – Forbes

Amazon (AMZN)

What was the last thing you heard about Amazon (AMZN)?

Let me guess. Its battle with Walmart WMT ? Or was it the FAAs approval of Amazons delivery drones? Most of this news about Amazons store is just noise that distracts investors from Amazons real force.

As Ill show, Amazon is running an operating system that powers some of todays most important technologies such as virtual reality, machine learning, and even quantum computing. Behind the scenes, it is utilized by over a million companiesincluding tech giants Apple AAPL , Netflix NFLX , and Facebook FB .

This is Amazons key and ever-growing moneymaker that has been driving Amazon stock to the moon. But before I pull the curtains, lets step back for a moment.

First, how Amazon makes moneyfor real

For all the online shopping fuss, Amazon doesn't earn much from its store. Yes, Amazon.com AMZN flips hundreds of billions of dollars worth of products every yearand its revenues are on a tear. But Amazon turns only a sliver of that into profits.

In the past year, Amazons store generated a record $282 billion in revenue from Amazon.com. That translated to just $5.6 billion in profitskeep in mind that was Amazon.coms most profitable year ever.

Meanwhile, most of Amazons profits came from the lesser-known side of its business called Amazon Web Services (AWS), as you can see below:

Amazon's profits from AWS vs Amazon.com

Its Amazons cloud arm that is serving over a million companies across the world. You may have heard that AWS has something to do with storing data in the cloud. But its much,muchmore than that.

AWS is the operating system of the internet

To get an idea of how AWS works, take your computer as an example.

Like every other computer, it runs on an operating system such as Windows or MacOS, which comes with a set of programs. This software puts your computer resources to use and helps you carry out daily taskssuch as sending emails or sorting out your files.

Now, think of AWS as an operating system thats running not one, but hundreds of thousands of big computers (in tech lingo: servers). It gives companies nearly unlimited computing power and storageas well as tools to build and run their software on the internet.

The difference is that these big computers sit in Amazons warehouses. And companies work on them remotelyor via the cloud. In other words, AWS is like the operating system of the internet.

Amazons operating system now powers AI, blockchain, and other next-gen technologies

In 2003, when Amazons AWS first started out, it offered only a couple of basic cloud services for storage and mail. Today, this system offers an unmatched set of 175+ tools that help companies build software harnesses todays top technologies.

The list includes blockchain, VR, machine learning (AI), quantum computing, augmented reality (AR), and other technologies that are the building blocks of todays internet.

For example, Netflix is using AWS for more than simply storing and streaming its shows on the internet. Its also employing AWS machine learning technology to recommend movies and shows to you.

Youve also probably heard of Slack (WORK), the most popular messaging app for business. Slack recently announced it will use Amazons media technology to introduce video and audio calls on its app.

And its not just tech companies that are utilizing Amazons AWS tools.

Take GE Power. The worlds energy leader is using AWS analytics technology to store and sift through avalanches of data from its plants. Or Fidelity. Americas mutual fund giant experiments with Amazons VR technology to build VR chat rooms for its clients.

In a picture, Amazons AWS works like this:

How Amazon's AWS powers the internet

Amazons AWS is earning more and more... and more

Amazon is not the only company running a cloud service. Google, Microsoft MSFT , Alibibaba, IBM IBM , and other tech giants are all duking it out for a slice of this lucrative business. But Amazon is the biggest and most feature-rich.

Today, Amazon controls 33% of the market, leaving its closest competitors Microsoft (2nd with 18%) and Google (3rd with 9%) far behind in the dust. That means nearly one third of the internet is running on Amazons AWS.

And it doesnt appear that Amazon will step down from its cloud throne anytime soon. Amazons sales from AWS soared 10X in the past six years. And last year, Amazon reported a bigger sales gain from AWS (dollar-wise) than any other cloud company.

Heres the main takeaway for investors

If you are looking into Amazon stock, dont get caught up in the online shopping fuss.

For years, AWS has been the linchpin of Amazons business. And this invisible side of Amazon is where Amazons largest gears turn.

Problem is, AWS is like a black box. Amazon reports very little on its operations. So if you want to dig deeper, youll have to do your own research.

Youll also have to weigh a couple of risks before putting your money into Amazon stock:

Other than that, Amazon is an outstanding stock, killing it in one of the most lucrative businesses on the planet. And its proven to be resilient to Covid, whose spread could hit the markers again.

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How Amazon Quietly Powers The Internet - Forbes

The big promise of Elon Musks neuralink with extended reality – Livemint

Last week, a healthy, happy pig" named Gertrude attained her 15 seconds of fame. This was courtesy Elon Musk, the serial entrepreneur and now the third-richest man in the world, who demonstrated his latest venture, Neuralink, an ultra-high bandwidth brain-machine interface (BMI) to connect humans and computers. As this column has often gushed about Musk, he thinks new and big, and Neuralink did live up to its billing, certainly from a public relations viewpoint. Reactions to it from the scientific community were mixed, and we will discuss those in a forthcoming column.

But what Neuralink did was to fire a few of my memory neurons and take me back to a programme I attended at Singularity University. In a session by a professor there, Jody Medich, I saw a quote by Satya Nadella: The future of computing will be driven by Quantum, AI and XR". While I understood why he talked about AI (artificial intelligence) and quantum computing, it was his mention of XR in the same breath that threw me. XR or extended reality includes technologies like AR (augmented reality), VR (virtual reality) and MR (mixed reality). I had always considered XR an afterthought to blockbusters like AI, blockchain, Internet of Things, etc. But Nadella was thinking otherwise. I learnt that XR was not just a tool to make Pokmon Go, or to show you a car in different colours, it was something that could make paralyzed war veterans walk, or the sightless see", much like what BMI was promising.

XR is big in enterprise usage, with Statista and the International Data Corp estimating the markets worth at $209 billion by 2022, powered by a shipment of 66 million AR/VR headsets. Applications include training in unsafe areas; retailing by way of virtual apparel, shoes, property, etc.; entertainment via virtual music festivals; and travel where you can see giraffes without going to Kenya (good for covid times). XR has great potential in healthcare. For instance, it could show the veins in your arm for accurate intravenous drug administration. Solar installations use XR with overlays and heads-up displays, increasing efficiency and safety.

While these are great, what makes this technology a superpower is the merging of the digital, physical and biological". Consider the cerebral cortex of our brain, specifically the neo-cortex, which is concerned with sight and hearing. XR explicitly works on one part of this, the primary visual cortex, the part that enables us to see. It is here where XR can work its magic. It can amplify our vision and literally rewire our brain.

One application of this XR-rewiring is pain reduction. VRHealth, an Israeli firm, works on using VR to cure migraine pains, for instance. Our brain is like a CPU75% of that CPU goes to visuals and sound," says founder Eran Orr. When we overload our CPU with an immersive technology like VR, things like pain can get downgraded in the priority list. That is why its amazing for pain management or pain distraction. Once you combine that with actual rehab, its a game-changer." The New York Times has written of Hollie Davis, who owes her current full mobility to trying VR as part of her treatment for a persistent, life-inhibiting pain after a motorcycle accident. She spent 10 or 20 minutes in a dark room while a head-mounted 3-D screen transported her to a very relaxing place, taught her about the nature of pain, how oxygen travels through the body, then how to breathe, focus on her breathing, relax her body and think of nothing else." The device engages multiple senses, essentially flooding the brain with so much input that it cannot register pain signals. When pain messages try to get through, the brain gives a busy signal".

VR can help restore feelings in paraplegics. Recently, researchers worked on eight chronic paraplegics", where the studys participants underwent a year-long training module that used BMIs combined with virtual reality tech. Half the patients were upgraded from chronic" to incomplete paraplegia" as their status classification. One of them, who had suffered from paralysis for 13 years, was able to move her legs without the help of a support harness.

As Medich puts it, XR can be used to provide cognitive ergonomics". While physical ergonomics amplifies manpower, cognitive ergonomics amplifies brain power. XR, combined with Neuralink-like technologies, therefore, will be super powerful. They could help the disabled walk again and let the pain- ridden transcend pain. I am already wondering how cool Gertrude would look in a VR headset.

Jaspreet Bindra is the author of The Tech Whisperer, and founder of Digital Matters

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The big promise of Elon Musks neuralink with extended reality - Livemint

Could Quantum Computing Progress Be Halted by Background Radiation? – Singularity Hub

Doing calculations with a quantum computer is a race against time, thanks to the fragility of the quantum states at their heart. And new research suggests we may soon hit a wall in how long we can hold them together thanks to interference from natural background radiation.

While quantum computing could one day enable us to carry out calculations beyond even the most powerful supercomputer imaginable, were still a long way from that point. And a big reason for that is a phenomenon known as decoherence.

The superpowers of quantum computers rely on holding the qubitsquantum bitsthat make them up in exotic quantum states like superposition and entanglement. Decoherence is the process by which interference from the environment causes them to gradually lose their quantum behavior and any information that was encoded in them.

It can be caused by heat, vibrations, magnetic fluctuations, or any host of environmental factors that are hard to control. Currently we can keep superconducting qubits (the technology favored by the fields leaders like Google and IBM) stable for up to 200 microseconds in the best devices, which is still far too short to do any truly meaningful computations.

But new research from scientists at Massachusetts Institute of Technology (MIT) and Pacific Northwest National Laboratory (PNNL), published last week in Nature, suggests we may struggle to get much further. They found that background radiation from cosmic rays and more prosaic sources like trace elements in concrete walls is enough to put a hard four-millisecond limit on the coherence time of superconducting qubits.

These decoherence mechanisms are like an onion, and weve been peeling back the layers for the past 20 years, but theres another layer that left unabated is going to limit us in a couple years, which is environmental radiation, William Oliver from MIT said in a press release. This is an exciting result, because it motivates us to think of other ways to design qubits to get around this problem.

Superconducting qubits rely on pairs of electrons flowing through a resistance-free circuit. But radiation can knock these pairs out of alignment, causing them to split apart, which is what eventually results in the qubit decohering.

To determine how significant of an impact background levels of radiation could have on qubits, the researchers first tried to work out the relationship between coherence times and radiation levels. They exposed qubits to irradiated copper whose emissions dropped over time in a predictable way, which showed them that coherence times rose as radiation levels fell up to a maximum of four milliseconds, after which background effects kicked in.

To check if this coherence time was really caused by the natural radiation, they built a giant shield out of lead brick that could block background radiation to see what happened when the qubits were isolated. The experiments clearly showed that blocking the background emissions could boost coherence times further.

At the minute, a host of other problems like material impurities and electronic disturbances cause qubits to decohere before these effects kick in, but given the rate at which the technology has been improving, we may hit this new wall in just a few years.

Without mitigation, radiation will limit the coherence time of superconducting qubits to a few milliseconds, which is insufficient for practical quantum computing, Brent VanDevender from PNNL said in a press release.

Potential solutions to the problem include building radiation shielding around quantum computers or locating them underground, where cosmic rays arent able to penetrate so easily. But if you need a few tons of lead or a large cavern in order to install a quantum computer, thats going to make it considerably harder to roll them out widely.

Its important to remember, though, that this problem has only been observed in superconducting qubits so far. In July, researchers showed they could get a spin-orbit qubit implemented in silicon to last for about 10 milliseconds, while trapped ion qubits can stay stable for as long as 10 minutes. And MITs Oliver says theres still plenty of room for building more robust superconducting qubits.

We can think about designing qubits in a way that makes them rad-hard, he said. So its definitely not game-over, its just the next layer of the onion we need to address.

Image Credit: Shutterstock

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Could Quantum Computing Progress Be Halted by Background Radiation? - Singularity Hub

We Just Found Another Obstacle For Quantum Computers to Overcome – And It’s Everywhere – ScienceAlert

Keeping qubits stable those quantum equivalents of classic computing bits will be key to realising the potential of quantum computing. Now scientists have found a new obstacle to this stability: natural radiation.

Natural or background radiation comes from all sorts of sources, both natural and artificial. Cosmic rays contribute to natural radiation, for example, and so do concrete buildings. It's around us all the time, and so this poses something of a problem for future quantum computers.

Through a series of experiments that altered the level of natural radiation around qubits, physicists have been able to establish that this background buzz does indeed nudge qubits off balance in a way that stops them from functioning properly.

"Our study is the first to show clearly that low-level ionising radiation in the environment degrades the performance of superconducting qubits," says physicist John Orrell, from the Pacific Northwest National Laboratory (PNNL).

"These findings suggest that radiation shielding will be necessary to attain long-sought performance in quantum computers of this design."

Natural radiation is by no means the most significant or the only threat to qubit stability, which is technically known as coherence everything from temperature fluctuations to electromagnetic fields can break the qubit 'spell'.

But the scientists say if we're to reach a future where quantum computers are taking care of our most advanced computing needs, then this interference from natural radiation is going to have to be dealt with.

It was after experiencing problems with superconducting qubit decoherence that the team behind the new study decided to investigate the possible problem with natural radiation. They found it breaks up a key quantum binding called a Cooper pair of electrons.

"The radiation breaks apart matched pairs of electrons that typically carry electric current without resistance in a superconductor," says physicist Brent VanDevender, from PNNL. "The resistance of those unpaired electrons destroys the delicately prepared state of a qubit."

Classical computers can be disrupted by the same issues that affect qubits, but quantum states are much more delicate and sensitive. One of the reasons that we don't have genuine full-scale quantum computers today is that no one can keep qubits stable for more than a few milliseconds at a time.

If we can improve on that, the benefits in terms of computing power could be huge: whereas classical computing bits can only be set as 1 or 0, qubits can be set as 1, 0 or both at the same time (known as superposition).

Scientists have been able to get it happening, but only for a very short space of time and in a very tightly controlled environment. The good news is that researchers like those at PNNL are committed to the challenge of figuring out how to make quantum computers a reality and now we know a bit more about what we're up against.

"Practical quantum computing with these devices will not be possible unless we address the radiation issue," says VanDevender. "Without mitigation, radiation will limit the coherence time of superconducting qubits to a few milliseconds, which is insufficient for practical quantum computing."

The research has been published in Nature.

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We Just Found Another Obstacle For Quantum Computers to Overcome - And It's Everywhere - ScienceAlert

Atos helps researchers and students to experiment with quantum algorithms by offering free, universal access to myQLM – GlobeNewswire

Paris, September 3, 2020 Atos, a global leader in digital transformation, now provides free, universal access to myQLM, its program providing researchers, students and developers with quantum programming tools. Launched in 2019 and initially reserved to Atos Quantum Learning Machine (Atos QLM) users, myQLM aims to democratize access to quantum simulation and encourage innovation in quantum computing. By allowing all researchers, students and developers worldwide to download and use myQLM, Atos moves one step further forward in its commitment to empower the quantum computing community.

Quantum computing has the potential to change the world as we know it by spurring breakthroughs in healthcare, environmental sustainability, industrial processes or finance. The current race to develop a commercially viable quantum computer has been instrumental in increasing awareness of the field worldwide but the quantum revolution requires more than just hardware. Training of students, professors, engineers and researchers needs to be boosted to pave the way for the emergence of the new programming languages, algorithms and tools all essentials in harnessing the true power of quantum computing.

Using myQLM, anyone can explore the capabilities of quantum computing, from experimenting with quantum programming to launching simulations of up to 20 qubits directly on their own computer or even larger simulations on the Atos QLM.

The shortage of skilled experts is one of the next greatest challenges to the development of quantum technologies. By opening up the access to our quantum programming environment myQLM, we hope to help train the next generation of computer scientists and researchers and foster an active community that will shape the future of quantum computing. We invite everyone to download myQLM today and join us in this life-changing adventure, said Agns Boudot, Senior Vice President, Head of HPC & Quantum at Atos.

myQLM comes with a complete set of tools:

Atos, a pioneer in quantum solutions

Atos ambitious program to anticipate the future of quantum computing the Atos Quantum program was launched in November 2016. As a result of this initiative,Atos was the first organization to offer a quantum noisy simulation module within its Atos QLM offer. Launched in 2017, Atos QLM is being used in numerous countries worldwide includingAustria, Finland, France,Germany, India, Italy, Japan, the Netherlands, Senegal,UKand theUnited States, empowering major research programs in various sectors like industry or energy. Recently, Atos extended its portfolio of quantum solutions with Atos QLM Enhanced (Atos QLM E), a new GPU-accelerated range of Atos QLM.

Learn more about myQLM and join our community by visiting the dedicated website: https://atos.net/en/lp/myqlm

***

About Atos

Atos is a global leader in digital transformation with 110,000 employees in 73 countries and annual revenue of 12 billion. European number one in Cloud, Cybersecurity and High-Performance Computing, the Group provides end-to-end Orchestrated Hybrid Cloud, Big Data, Business Applications and Digital Workplace solutions. The Group is the Worldwide Information Technology Partner for the Olympic & Paralympic Games and operates under the brands Atos, Atos|Syntel, and Unify. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index.

The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Press contact Marion Delmas | marion.delmas@atos.net | +33 6 37 63 91 99

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Atos helps researchers and students to experiment with quantum algorithms by offering free, universal access to myQLM - GlobeNewswire

Intel ups the ante on quantum computing research – IT-Online

Intel is one of the US quantum technology companies included in Q-Next, one of five national quantum research centres established by the White House Office of Science and Technology Policy (OSTP) and the US Department of Energy (DOE).

Q-Next, National Quantum Information Science Research Centre, is led by Argonne National Laboratory and brings together researchers from national laboratories, universities and technology companies.

Advancing quantum practicality will be a team sport across the ecosystem, and our partnership with Argonne National Laboratory on Q-Next will enable us to bring our unique areas of expertise to this cross-industry effort to drive meaningful progress in the field, says James Clarke, director of quantum hardware at Intel.

At Intel, we are taking a broad view of quantum research that spans hardware and software with a singular focus on getting quantum out of labs and into the real world, where it can solve real problems.

Quantum computing has the potential to tackle problems beyond the capabilities of conventional systems today by leveraging a phenomenon of quantum physics that exponentially expands computational power.

This could dramatically speed complex problem-solving in a variety of fields such as pharmaceuticals, telecommunications and materials science, accelerating what today could take years to complete in only a matter of minutes.

To speed the discovery and development in this promising emerging field of computing, the DOE and the OSTP have created five new quantum information science research centers across the country, with Q-Next being one of them.

The Q-Next facility will create two national foundries for quantum materials and devices, and leverage the strength of private-public partnership to focus on the advancements of three core quantum technologies:

* Quantum networks: Development of communications networks and interconnects for the transmission of quantum information across long distances, including quantum repeaters that enable the establishment of unhackable networks for information transfer.

* Quantum-enabled sensing: Development of sensor technologies that can leverage the exponential power of quantum computing to achieve unprecedented sensitivities for data capture, which would have transformational applications in physics, materials and life sciences.

* Quantum test beds: Ongoing research utilising quantum test environments, including both quantum simulators and future full-stack universal quantum computers, with applications in quantum simulations, cryptanalysis and logistics optimisation.

We are excited to have Intels expertise and partnership, along with numerous technology leaders, as part of the new Q-Next centre. Intel will help us to drive discoveries and technical progress in quantum computing that will advance both known and yet-to-be discovered quantum-enabled applications, says David Awschalom, Q-Next director, senior scientist at Argonne, Liew Family professor of Molecular Engineering at the University of Chicago and director of the Chicago Quantum Exchange.

Intels research efforts in quantum span the entire quantum system or full-stack from qubit devices to the hardware and software required to control these devices, to quantum algorithms that will harness the power of quantum technologies.

All of these elements are essential to advancing quantum practicality, the point at which quantum computing moves out of research labs and into real-world practical applications.

The company aims to develop a large-scale quantum computing system, which will require thousands of quantum bits, or qubits, working reliably together with limited error and information loss. It is focused on overcoming the key bottlenecks preventing researchers from moving beyond todays few qubit systems, including qubit operation at slightly higher temperatures, and elegant control systems and interconnects to facilitate the design of quantum systems at scale.

Earlier this year, Intel demonstrated progress in hot qubit performance, leveraging its silicon spin qubit research, and continues to advance its research on customised cryogenic control chips for quantum systems like Horse Ridge.

Featured picture: The inside of a quantum computing refrigerator in Intels Quantum Computing Lab in Hillsboro, Oregon. (Credit: Walden Kirsch/Intel Corporation)

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Intel ups the ante on quantum computing research - IT-Online

Synopsys Appoints Jeannine Sargent to Board of Directors – HPCwire

MOUNTAIN VIEW, Calif.,Sept. 3, 2020Synopsys, Inc. announced the appointment of Jeannine Sargentto its board of directors, effective today. Ms. Sargent is an experienced corporate executive and board member, with a background in global business and product strategy, engineering, operations, and sales and marketing. Prior to her current investment advisory roles with a focus on industries ranging from artificial intelligence to energy and sustainability, she served as president of Innovation and New Ventures at Flex, where she was responsible for worldwide innovation, global design and engineering, new product businesses and corporate venture investments. Before joining Flex, Ms.Sargent was CEO of Oerlikon Solar, a leading provider of end-to-end thin film solar photovoltaic solutions, and of Voyan Technology, whichsupplied software and silicon solutions for the broadband communication and semiconductor equipment industries.

Jeannine is an accomplished business leader and advisor with a compelling breadth of experience and impact, saidAart de Geus, chairman and co-CEO of Synopsys. Her demonstrated expertise in leading-edge technology and business development, operations, complex ecosystems and global markets will be of high value as a complement to the strong board we have at Synopsys.

Ms. Sargent is currently a member of the boards of Fortive, a diversified industrial technology company, and Proterra, a privately held leader in commercial electric vehicle technology. At Fortive, she is chair of the Audit committee and serves on the Compensation and Nominating & Governance committees. Ms. Sargent was also a director at Cypress Semiconductor, where she served on the Compensation and Nominating & Governance committees.

Im excited about the opportunities that Synopsys has in EDA and semiconductor IP, in light of todays hyperscalers and the dawn of quantum computing, and in the Software Integrity business, as the need for security testing continues to accelerate, Sargent said. Im honored to join such a capable and committed team.

She graduated magna cum laude fromNortheastern Universitywith a Bachelor of Science degree in chemical engineering and holds certificates from the executive development programs at theMIT Sloan School of Management,Harvard University, andStanford University.

About Synopsys

Synopsys, Inc. is the Silicon to Softwarepartner for innovative companies developing the electronic products and software applications we rely on every day. As the worlds 15thlargest software company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and is also growing its leadership in software security and quality solutions. Whether youre a system-on-chip (SoC) designer creating advanced semiconductors, or a software developer writing applications that require the highest security and quality, Synopsys has the solutions needed to deliver innovative, high-quality, secure products. Learn more atwww.synopsys.com.

Source: Synopsys

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Synopsys Appoints Jeannine Sargent to Board of Directors - HPCwire

Editorial: Five Birdies That Signal Good Work | Opinion | thepilot.com – Southern Pines Pilot

Birdie, by Moore County Schools, for choosing transparency when it comes to how its handling the coronavirus in its schools.

Going back into schools for the first time since Gov. Roy Cooper closed them in March, it was a given that COVID-19 positive cases would turn up among students, teachers and staff at some point.

Rather than leave it to parents spreading stories on social media about cases at their respective schools, the district last week began publishing with daily updates a school-by-school spreadsheet of positive coronavirus cases. The spreadsheet is published on the school systems website, ncmcs.org, for all to see and compare.

Moore County is in the minority of school districts that have chosen to have some form of in-person attendance, so naturally everyone has been nervous about how that would go with the virus. So far, the system seems to be holding its integrity, and being open and transparent with the public about cases is a strong component of building faith.

Birdie, by the Moore County Health Department, for hosting a second Facebook Live discussion and question-and-answer session.

Between department Director Robert Wittmann and health educator Miriam King, the 40-minute session accomplished something that had been sorely lacking in the departments response: face-to-face communication.

The personal touch is important during this pandemic. Gov. Roy Cooper and health officials in several other counties have adopted that approach with regular in-person briefings, even when theres not a whole lot to share. Its a way for leaders to show themselves, speak for their actions, demonstrate to the public that they have a handle on matters.

This birdie could quickly become an eagle if the Health Department builds from here and increases the number of presentations and adds more opportunities for Wittmann and staff to address the public.

Birdie, by Karen Pence, Vice President Mike Pences wife, for her finger point last week at the Republican National Convention of Southern Pines own R. Riveter. Pence visited the company two years ago to highlight its mission to bring meaningful work to military spouses.

While traveling throughout our nation to educate military spouses about policy solutions President Trump has promoted, involving real, tangible progress in military spouse employment, I have been inspired to meet heroes like Lisa Bradley and Cameron Cruse, she said.

These military spouses decided to start their own business, R. Riveter, named after the Rosie the Riveter campaign used to recruit women workers during World War II. R. Riveter makes beautiful handbags designed and manufactured exclusively by military spouses. Many of those spouses live all over the country. They prepare and send their section of the bags to the company located in North Carolina, where the final product is assembled.

When you can be remembered two years later by someone like the Second Lady, you know youre doing something special.

Birdie, by Vito Gironda and all his extended family, for 40 years of serving this community. Vito and his brothers opened Vitos pizza on South East Broad Street in 1980 as their attempt at achieving the American dream. Theyve grown that business over the years to the point where they are virtually synonymous with Italian food in Southern Pines.

The restaurant business can be a fleeting one, so its rare when you find one still in business after 40 years. Thats a testament to the Girondas faith in the community and the flavorful food, not to mention Vitos massive annual summer garden.

Birdie, by David Sinclair, The Pilots recently departed managing editor. Sinclair spent the past 20 years at The Pilot, but his career covering Moore County for various news organizations stretches to 38 years. Yes, he started in high school.

The Moore County Board of Commissioners, who Sinclair covered for years, recently passed a resolution honoring him. You are better known in this community than we are, teased Board Chairman Frank Quis.

Sinclair approached every assignment with good humor, grace and integrity, and his Pinehurst sunset pictures are local legend.

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Editorial: Five Birdies That Signal Good Work | Opinion | thepilot.com - Southern Pines Pilot

Army looks to machine learning to predict, prevent injuries – GCN.com

Army looks to machine learning to predict, prevent injuries

The Army is harnessing a sensor and machine learning platform currently used by professional and collegiate sports teams to analyze individual soldiers biomechanics and predict and prevent physical injuries.

According to a March 2020 paper in Military Medicine, noncombat injuries are the leading cause of outpatient medical visits among active Army service members, accounting for nearly 60% of soldiers limited duty days and 65% of soldiers who cannot deploy for medical reasons. Besides decreasing the number of soldiers available to deploy, these injuries are expensive to treat and can lead to service-connected disability compensation.

The Armys Mission and Installation Contracting Command will be using Sparta Sciences Sparta Trac system to collect data on movements used in heavy physical training regimes. The system uses force plates, similar to large bathroom scales that are equipped with sensors that assess an athletes core and lower extremity strength. As athletes do various balance, jumping and plank exercises, the system collects and analyzes the data to create a movement signature and show the risk level for musculoskeletal injuries. It also designs customized workouts so soldiers can strengthen weak areas and avoid injuries. The diagnostic test takes five minutes, company officials wrote in an Aug. 18 column for Stars and Stripes.

Force plate technology was singled out for study by the military in the 2021 National Defense Authorization Act. The NDAA encouraged development of a tool that will check warfighters physical fitness to determine combat readiness. Force plate technology and machine learning capabilities are an important part of that tool, according to the NDAA.

Although force plate systems are already used across the military, the NDAA tasked the Secretary of Defense to report on how many military units are using the systems, as well as whether the technology could be scaled to develop individual fitness programs for at-home and deployed warfighters.

About the Author

Mark Rockwell is a senior staff writer at FCW, whose beat focuses on acquisition, the Department of Homeland Security and the Department of Energy.

Before joining FCW, Rockwell was Washington correspondent for Government Security News, where he covered all aspects of homeland security from IT to detection dogs and border security. Over the last 25 years in Washington as a reporter, editor and correspondent, he has covered an increasingly wide array of high-tech issues for publications like Communications Week, Internet Week, Fiber Optics News, tele.com magazine and Wireless Week.

Rockwell received a Jesse H. Neal Award for his work covering telecommunications issues, and is a graduate of James Madison University.

Click here for previous articles by Rockwell. Contact him at [emailprotected] or follow him on Twitter at @MRockwell4.

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Army looks to machine learning to predict, prevent injuries - GCN.com

Toward a machine learning model that can reason about everyday actions – MIT News

The ability to reason abstractly about events as they unfold is a defining feature of human intelligence. We know instinctively that crying and writing are means of communicating, and that a panda falling from a tree and a plane landing are variations on descending.

Organizing the world into abstract categories does not come easily to computers, but in recent years researchers have inched closer by training machine learning models on words and images infused with structural information about the world, and how objects, animals, and actions relate. In a new study at the European Conference on Computer Vision this month, researchers unveiled a hybrid language-vision model that can compare and contrast a set of dynamic events captured on video to tease out the high-level concepts connecting them.

Their model did as well as or better than humans at two types of visual reasoning tasks picking the video that conceptually best completes the set, and picking the video that doesnt fit. Shown videos of a dog barking and a man howling beside his dog, for example, the model completed the set by picking the crying baby from a set of five videos. Researchers replicated their results on two datasets for training AI systems in action recognition: MITs Multi-Moments in Time and DeepMinds Kinetics.

We show that you can build abstraction into an AI system to perform ordinary visual reasoning tasks close to a human level, says the studys senior author Aude Oliva, a senior research scientist at MIT, co-director of the MIT Quest for Intelligence, and MIT director of the MIT-IBM Watson AI Lab. A model that can recognize abstract events will give more accurate, logical predictions and be more useful for decision-making.

As deep neural networks become expert at recognizing objects and actions in photos and video, researchers have set their sights on the next milestone: abstraction, and training models to reason about what they see. In one approach, researchers have merged the pattern-matching power of deep nets with the logic of symbolic programs to teach a model to interpret complex object relationships in a scene. Here, in another approach, researchers capitalize on the relationships embedded in the meanings of words to give their model visual reasoning power.

Language representations allow us to integrate contextual information learned from text databases into our visual models, says study co-author Mathew Monfort, a research scientist at MITs Computer Science and Artificial Intelligence Laboratory (CSAIL). Words like running, lifting, and boxing share some common characteristics that make them more closely related to the concept exercising, for example, than driving.

Using WordNet, a database of word meanings, the researchers mapped the relation of each action-class label in Moments and Kinetics to the other labels in both datasets. Words like sculpting, carving, and cutting, for example, were connected to higher-level concepts like crafting, making art, and cooking. Now when the model recognizes an activity like sculpting, it can pick out conceptually similar activities in the dataset.

This relational graph of abstract classes is used to train the model to perform two basic tasks. Given a set of videos, the model creates a numerical representation for each video that aligns with the word representations of the actions shown in the video. An abstraction module then combines the representations generated for each video in the set to create a new set representation that is used to identify the abstraction shared by all the videos in the set.

To see how the model would do compared to humans, the researchers asked human subjects to perform the same set of visual reasoning tasks online. To their surprise, the model performed as well as humans in many scenarios, sometimes with unexpected results. In a variation on the set completion task, after watching a video of someone wrapping a gift and covering an item in tape, the model suggested a video of someone at the beach burying someone else in the sand.

Its effectively covering, but very different from the visual features of the other clips, says Camilo Fosco, a PhD student at MIT who is co-first author of the study with PhD student Alex Andonian. Conceptually it fits, but I had to think about it.

Limitations of the model include a tendency to overemphasize some features. In one case, it suggested completing a set of sports videos with a video of a baby and a ball, apparently associating balls with exercise and competition.

A deep learning model that can be trained to think more abstractly may be capable of learning with fewer data, say researchers. Abstraction also paves the way toward higher-level, more human-like reasoning.

One hallmark of human cognition is our ability to describe something in relation to something else to compare and to contrast, says Oliva. Its a rich and efficient way to learn that could eventually lead to machine learning models that can understand analogies and are that much closer to communicating intelligently with us.

Other authors of the study are Allen Lee from MIT, Rogerio Feris from IBM, and Carl Vondrick from Columbia University.

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Toward a machine learning model that can reason about everyday actions - MIT News