SparkCognition Partners with Informatica to Enable Customers to Operationalize Artificial Intelligence and Solve Problems at Scale – PRNewswire

AUSTIN, Texas, Feb. 19, 2020 /PRNewswire/ --SparkCognition, a leading AI company, announced a partnership with enterprise cloud data management company, Informatica, to transform the data science process for companies. By combining Informatica's data management capabilities with SparkCognition's AI-powered data science automation platform, Darwin, users will benefit from an integrated end-to-end environment where they can gather and manage their data, create a custom and highly-accurate model based off of that data, and deploy the model to inform business decisions.

"There has never been a more critical time to leverage the power of data and today's leading businesses recognize that data not only enables them to stay afloat, but provides them with the competitive edge necessary to innovate within their industries," said Ronen Schwartz, EVP, global technical and ecosystem strategy and operations at Informatica. "Together with SparkCognition, we are helping users tackle some of the most labor and time-intensive aspects of data science in a user-friendly fashion that allows users of all skill levels to quickly solve their toughest business problems."

Informatica is the leading data integration and data management company, which offers users the ability to collect their data from even the most fragmented sources across hybrid enterprises, discover data, then clean and prepare datasets to create and expand data model features. SparkCognition is the world's leading industrial artificial intelligence company, and its Darwin data science automation platform accelerates the creation of end-to-end AI solutions to deliver business-wide outcomes. The partnership will allow users to seamlessly discover data, pull their data from virtually anywhere using Informatica's data ingestion capabilities, then input the data into the Darwin platform. Through the new integration, users will streamline workflows and speed up the model building process to provide value to their business faster.

"At SparkCognition, we're strong believers that this new decade will be dominated by model-driven enterprisescompanies who have embraced and operationalized artificial intelligence," said Dana Wright, Global Vice President of Sales at SparkCognition. "We recognize this shared mission with Informatica and are excited to announce our partnership to help companies solve their toughest business problems using artificial intelligence."

To learn more about Darwin, visit sparkcognition.com/product/darwin/

About SparkCognition:

With award-winning machine learning technology, a multinational footprint, and expert teams focused on defense, IIoT, and finance, SparkCognition builds artificial intelligence systems to advance the most important interests of society. Our customers are trusted with protecting and advancing lives, infrastructure, and financial systems across the globe. They turn to SparkCognition to help them analyze complex data, empower decision-making, and transform human and industrial productivity. SparkCognition offers four main products:DarwinTM, DeepArmor, SparkPredict, and DeepNLPTM. With our leading-edge artificial intelligence platforms, our clients can adapt to a rapidly changing digital landscape and accelerate their business strategies. Learn more about SparkCognition's AI applications and why we've been featured in CNBC's 2017 Disruptor 50, and recognized three years in a row on CB Insights AI 100, by visiting http://www.sparkcognition.com.

For Media Inquiries:

Cara SchwartzkopfSparkCognitioncschwartzkopf@sparkcognition.com512-956-5491

SOURCE SparkCognition

http://sparkcognition.com

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SparkCognition Partners with Informatica to Enable Customers to Operationalize Artificial Intelligence and Solve Problems at Scale - PRNewswire

Implementing artificial intelligence in the insurance industry: Cass breakfast briefing – City, University of London

Cass event addresses implementation, benefits and challenges of AI in insurance

How is artificial intelligence (AI) affecting the insurance industry and what should insurance providers consider before implementing this technology? These were just two points of discussion during the Artificial Intelligence and Insurance: Managing Risks and Igniting Innovation breakfast event held at Cass Business School.

Professor of Strategy and Founding Director of the Digital Leadership Research Centre, Gianvito Lanzolla was joined by technology and insurance professionals to explore the feasibility of digitisation on the industry, as well as looking at how and when AI should be implemented.

Professor Lanzolla presented his joint research (carried out with Cass research student Lei Fang and Reader in Actuarial Science, Dr Andreas Tsanakas) about the impact of digitisation on management attention in the banking and insurance industries highlighting the ambivalent consequences of digitisation. On the one hand there could be scope for increased coordination, but this potentially comes at the expense of increasing group thinking and systemic risk.

Santiago Restrepo, Director at global professional services consultancy BDO UK LLP, then spoke about how businesses should make the case for using AI. This includes assessing market needs, company objectives and potential scalability of the technology.

Founder and CEO of data insights provider Digital Fineprint, Bo-Erik Abrahamsson demonstrated the importance of data, and how raw data mining could be transformed into useful insights for insurance companies.

Paul Willoughby, Head of IT Strategy, Innovation and Architecture at insurance provider Beazley, then stressed the importance of only using AI where it was critically required and would make the boat move faster citing the example of anonymous chat bots as a piece of technology that does not necessarily deliver satisfactory insights or levels of customer service.

The session concluded with a Q&A session from audience members.

Reflecting on the discussion, Professor Lanzolla said:

Artificial Intelligence can have many and clear advantages for industries that are heavily reliant on data, such as insurance, but there are also considerations that need to be made before implementing technology."

Common considerations should include the implications of AI-related black boxing, fault lines between new digital skills and legacy skills, loss of emotional engagement with an organisation and risks for organisational stability when turbocharging some areas of an organisation with AI while leaving others lagging behind.

The event was introduced and chaired by Darren Munday, Partner at Internal Consulting Group (Global) and Visiting Fellow at the Digital Leadership Research Centre.

Find out more about upcoming events at Cass.

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Implementing artificial intelligence in the insurance industry: Cass breakfast briefing - City, University of London

Why Quantum Computing Gets Special Attention In The Trump Administration’s Budget Proposal – KUT

From Texas Standard:

The Trump administration's fiscal year 2021 budget proposal includes significant increases in funding for artificial intelligence and quantum computing, while cutting overall research and development spending. If Congress agrees to it, funding for artificial intelligence, or AI, would nearly double, and quantum computing would receive a 50% boost over last year's budget, doubling in 2022 to $860 million. The administration says these two fields of research are important to U.S. national security, in part, because China also invests heavily in these fields.

Quantum computing uses quantum mechanics to solve highly complex problems more quickly than they can be solved by standard or classical computers. Though fully functional quantum computers don't yet exist, scientists at academic institutions, as well as at IBM, Google and other companies, are working to build such systems.

Scott Aaronson is a professor of computer science and the founding director of the Quantum Information Center at the University of Texas at Austin. He says applications for quantum computing include simulation of chemistry and physics problems. These simulations enable scientists to design new materials, drugs, superconductors and solar cells, among other things.

Aaronson says the government's role is to support basic scientific research the kind needed to build and perfect quantum computers.

"We do not yet know how to build a fully scalable quantum computer. The quantum version of the transistor, if you like, has not been invented yet," Aaronson says.

On the software front, researchers have not yet developed applications that take full advantage of quantum computing's capabilities.

"That's often misrepresented in the popular press, where it's claimed that a quantum computer is just a black box that does everything," Aaronson says.

Competition between the U.S. and China in quantum computing revolves, in part, around the role such a system could play in breaking the encryption that makes things secure on the internet.

Truly useful quantum computing applications could be as much as a decade away, Aaronson says. Initially, these tools would be highly specialized.

"The way I put it is that we're now entering the very, very early, vacuum-tube era of quantum computers," he says.

Written by Shelly Brisbin.

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Why Quantum Computing Gets Special Attention In The Trump Administration's Budget Proposal - KUT

This Breakthrough Just Got Us One Step Closer to a Quantum Internet – Singularity Hub

While quantum computing tends to garner all the headlines, quantum technology also has huge promise for the communication networks of the future. Thats why on top of the roughly $450 million the Trump administration just earmarked for quantum research in their proposed budget, theres $25 million dedicated to building a nationwide quantum internet.

At what point a quantum network becomes the quantum internet is up for debate, but its likely to develop in phases of increasing sophistication, with the ultimate goal being a global network of quantum-connected quantum computers.

The US is well behind China on this front, though. A team led by quantum supremo Jian-Wei Pan have already demonstrated a host of breakthroughs in transmitting quantum signals to satellites, most recently developing a mobile quantum satellite station.

The reason both countries are rushing to develop the technology is that it could provide an ultra-secure communication channel in an era where cyberwarfare is becoming increasingly common.

Its essentially impossible to eavesdrop on a quantum conversation. The strange rules of quantum mechanics mean that measuring a quantum state immediately changes it, so any message encoded in quantum states will be corrupted if someone tries to intercept it.

But quantum states are also intrinsically fragile, which has made it difficult to establish quantum connections over large distances. But a team led by Pan has reported smashing the record for connecting two quantum memories in a paper in Nature.

Making a quantum connection relies on a phenomenon known as entanglement. If the states of two quantum objects are entangled, manipulating or measuring the state of one will be mirrored in the other. In theory this allows you to transmit quantum information instantaneously over very large distances.

So far most research has been done on entangled photonsincluding Pans work on quantum satellitesbut single particles can only carry limited information. Quantum memories, which are made up of clouds of millions of rubidium atoms, can store more, but the biggest distance theyd previously been entangled over was 1.3 kilometers.

Pans team came up with a clever workaround, as John Timmer explains in Ars Technica. Each quantum memory is set by shooting a photon at it, which causes the memory to emit another photon that is entangled with the state of the memory. This photon is then converted to an infrared wavelength so it can be transmitted over fiber optic cable.

The photons from each memory meet at a halfway point where they are measured in such a way that they become entangled. Because each was already entangled with their respective memories, these both become entangled as well, setting up the quantum connection.

The researchers carried out two experiments, one where they transmitted photons over 22 kilometers of cable buried underground between two separate facilities and one where they sent the particles around a 50-kilometer spool of optical cable in their lab.

The authors say those kinds of distances make it feasible to connect cities on a quantum internet and could be used to create quantum repeaters, a series of nodes that help boost the signal over longer distances.

But theres still some way to go. The process of converting the photons into a form that can travel along the fiber optic loses about 30 percent of the photons. The complex process involved in entangling the two photons also leads to further inefficiencies, which means theyre only able to successfully entangle photons roughly twice a second.

Thats a problem, because the memories only hold their state for 70 microseconds. The researchers admit they likely need to both boost the lifetime of the memories and the rate of entanglement for this approach to work in practice.

Its early, but the research is a significant step towards a quantum internet. If the US wants to play any part in its development, its going to have to play catch-up.

Image Credit: Garik Barseghyan from Pixabay

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Correcting the jitters in quantum devices – MIT News

Labs around the world are racing to develop new computing and sensing devices that operate on the principles of quantum mechanics and could offer dramatic advantages over their classical counterparts. But these technologies still face several challenges, and one of the most significant is how to deal with noise random fluctuations that can eradicate the data stored in such devices.

A new approach developed by researchers at MIT could provide a significant step forward in quantum error correction. The method involves fine-tuning the system to address the kinds of noise that are the most likely, rather than casting a broad net to try to catch all possible sources of disturbance.

The analysis is described in the journal Physical Review Letters, in a paper by MIT graduate student David Layden, postdoc Mo Chen, and professor of nuclear science and engineering Paola Cappellaro.

The main issues we now face in developing quantum technologies are that current systems are small and noisy, says Layden. Noise, meaning unwanted disturbance of any kind, is especially vexing because many quantum systems are inherently highly sensitive, a feature underlying some of their potential applications.

And theres another issue, Layden says, which is that quantum systems are affected by any observation. So, while one can detect that a classical system is drifting and apply a correction to nudge it back, things are more complicated in the quantum world. What's really tricky about quantum systems is that when you look at them, you tend to collapse them, he says.

Classical error correction schemes are based on redundancy. For example, in a communication system subject to noise, instead of sending a single bit (1 or 0), one might send three copies of each (111 or 000). Then, if the three bits dont match, that shows there was an error. The more copies of each bit get sent, the more effective the error correction can be.

The same essential principle could be applied to adding redundancy in quantum bits, or qubits. But, Layden says, If I want to have a high degree of protection, I need to devote a large part of my system to doing these sorts of checks. And this is a nonstarter right now because we have fairly small systems; we just dont have the resources to do particularly useful quantum error correction in the usual way. So instead, the researchers found a way to target the error correction very narrowly at the specific kinds of noise that were most prevalent.

The quantum system theyre working with consists of carbon nuclei near a particular kind of defect in a diamond crystal called a nitrogen vacancy center. These defects behave like single, isolated electrons, and their presence enables the control of the nearby carbon nuclei.

But the team found that the overwhelming majority of the noise affecting these nuclei came from one single source: random fluctuations in the nearby defects themselves. This noise source can be accurately modeled, and suppressing its effects could have a major impact, as other sources of noise are relatively insignificant.

We actually understand quite well the main source of noise in these systems, Layden says. So we don't have to cast a wide net to catch every hypothetical type of noise.

The team came up with a different error correction strategy, tailored to counter this particular, dominant source of noise. As Layden describes it, the noise comes from this one central defect, or this one central electron, which has a tendency to hop around at random. It jitters.

That jitter, in turn, is felt by all those nearby nuclei, in a predictable way that can be corrected.

The upshot of our approach is that were able to get a fixed level of protection using far fewer resources than would otherwise be needed, he says. We can use a much smaller system with this targeted approach.

The work so far is theoretical, and the team is actively working on a lab demonstration of this principle in action. If it works as expected, this could make up an important component of future quantum-based technologies of various kinds, the researchers say, including quantum computers that could potentially solve previously unsolvable problems, or quantum communications systems that could be immune to snooping, or highly sensitive sensor systems.

This is a component that could be used in a number of ways, Layden says. Its as though were developing a key part of an engine. Were still a ways from building a full car, but weve made progress on a critical part.

"Quantum error correction is the next challenge for the field," says Alexandre Blais, a professor of physics at the University of Sherbrooke, in Canada, who was not associated with this work. "The complexity of current quantum error correcting codes is, however, daunting as they require a very large number of qubits to robustly encode quantum information."

Blais adds, "We have now come to realize that exploiting our understanding of the devices in which quantum error correction is to be implemented can be very advantageous.This work makes an important contribution in this direction by showing that a common type of error can be corrected for in a much more efficient manner than expected. For quantum computers to become practical we need more ideas like this."

The research was supported by the U.S. Army Research Office and the National Science Foundation.

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Correcting the jitters in quantum devices - MIT News

Alex Garlands new show wants you to be scared of tech again – Engadget

Devs, a limited series that premieres March 5th on Hulu, tells the story of fictional quantum computing company Amaya. It's a pretty typical tech giant, complete with shuttle buses taking employees to a campus deep in the woods. Lily Chan (Sonoya Mizuno) works in encryption, while her boyfriend Sergei (Karl Glusman) specializes in life simulations. Katie (Alison Pill), Stewart (Stephen McKinley Henderson) and Lyndon (Cailee Spaeny) all work in the secretive "Devs" division, whose exact nature is revealed to us over the course of eight episodes. And then there's Forest (Nick Offerman), the soft-spoken CEO, whose grief over a lost child is so great he not only named the company after her, but he built a giant statue of her in the middle of the corporate campus.

Devs doesn't frame any of these people as being particularly remarkable. We're never treated to a montage of the staff working all-nighters fueled by nachos and Red Bull. They don't walk up to a chalkboard full of equations and write down an answer others have been seeking for months. Our young prodigy, Lyndon, isn't even that young he's 19, and we're never given some exposition about how he was recruited as a child or some other clichd nonsense. Even Forest escapes any kind of hagiography, with his origins in tech and the rise of the company kept completely out of the narrative. The past doesn't matter; nothing really matters except what they do now.

And everything they're doing now revolves around the quantum computer and the predictive code that runs on it.

The system is hidden inside a bunker situated in the middle of a forest. To reach the office you must cross a gold-lined vacuum chamber inside an electromagnetically-supported clear cube. The quantum computer is a delicate structure of metal fittings and wires inside a glass case, reminiscent of an old pendulum clock underneath a glass dome. The characters are often shown pondering it in silence. The camera occasionally approaches it as if it's a character itself, implying the sense of something happening.

The techno thrillers of the '90s (I once saw them referred to as "techsploitation" movies, which seemed apt) leaned on how little we knew about the internet back then. We lacked the knowledge to question what they showed us, and fear of the unknown is an easy well for filmmakers to draw upon. Now we all carry supercomputers in our pockets. Plus, many of us know someone who works in IT or CS, so it's less mysterious now. It's just so ordinary these days. We're not scared of tech anymore.

A show like Black Mirror can scream "technology is bad" all it wants, but in most episodes, the problem isn't the tech itself. It's more how it's used and how it affects people. A mother monitors her daughter's every action via a cranial implant. Two heterosexual men discover mutual attraction through VR. A woman becomes obsessed with her social standing, expressed in a literal score. As best evidenced by the happy ending of 'San Junipero,' it's not the technology itself that is good or evil, but what you choose to do with it.

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Alex Garlands new show wants you to be scared of tech again - Engadget

QUANTUM COMPUTING TECHNOLOGIES Market: Comprehensive study explores Huge Growth in Future | D-Wave Systems Inc., IBM Corporation, Lockheed Martin…

The QUANTUM COMPUTING TECHNOLOGIES market research report added by Report Ocean, is an in-depth analysis of the latest trends, market size, status, upcoming technologies, industry drivers, challenges, regulatory policies, with key company profiles and strategies of players. The research study provides market introduction, QUANTUM COMPUTING TECHNOLOGIES market definition, regional market scope, sales and revenue by region, manufacturing cost analysis, Industrial Chain, market effect factors analysis, QUANTUM COMPUTING TECHNOLOGIES market size forecast, 100+ market data, Tables, Pie Chart, Graphs and Figures, and many more for business intelligence.

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In the QUANTUM COMPUTING TECHNOLOGIES Market, some of the major companies are:

D-Wave Systems Inc.IBM CorporationLockheed Martin CorporationIntel CorporationAnyon Systems Inc.Cambridge Quantum Computing Limited

The report consists of various chapters and company profiling is a major among them. Company profiling garners business intelligence and track key elements of a business, such as:

QUANTUM COMPUTING TECHNOLOGIES Market: Insights

Global Quantum Computing Technologies Market valued approximately USD 75.0 million in 2018 is anticipated to grow with a healthy growth rate of more than 24.0% over the forecast period 2019-2026. The Quantum Computing Technologies Market is continuously growing in the global scenario at significant pace. As it is recognized as a computer technology based on the principles of quantum theory, which explains the nature and behavior of energy and matter on the quantum level. A Quantum computer follows the laws of quantum physics through which it can gain enormous power, have the ability to be in multiple states and perform tasks using all possible permutations simultaneously. Surging implementation of machine learning by quantum computer, escalating application in cryptography and capability in simulating intricate systems are the substantial driving factors of the market during the forecast period. Moreover, rising adoption & utility in cyber security is the factors that likely to create numerous opportunity in the near future. However, lack of skilled professionals is one of the major factors that restraining the growth of the market during the forecast period.

The regional analysis of Global Quantum Computing Technologies Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the leading/significant region across the world in terms of market share due to increasing usage of quantum computers by government agencies and aerospace & defense for machine learning in the region. Europe is estimated to grow at second largest region in the global Quantum Computing Technologies market over the upcoming years. Further, Asia-Pacific is anticipated to exhibit higher growth rate / CAGR over the forecast period 2019-2026 due to rising adoption of quantum computers by BFSI sectors in the region.

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The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players.

The Global QUANTUM COMPUTING TECHNOLOGIES Market is segmented into various sub-groups to understand the market scenario in detail, the market segmentation are as follows:

By Application:OptimizationMachine LearningSimulation

By Vertical:BFSIIT and TelecommunicationHealthcareTransportationGovernmentAerospace & DefenseOthers

Other Report Highlights Competitive Landscape Sales, Market Share, Geographical Presence, Business Segments Product Benchmarking. Market Dynamics Drivers and Restraints. Market Trends. Porter Five Forces Analysis. SWOT Analysis.

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

Historical year 2013-2017

Base year 2018

Forecast period** 2019 to 2025 [** unless otherwise stated]

Regional split of the Global QUANTUM COMPUTING TECHNOLOGIES Market research report is as follows:

The market research study offers in-depth regional analysis along with the current market scenarios. The major regions analyzed in the study are:

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Questions answered in the QUANTUM COMPUTING TECHNOLOGIES market research report:

Key highlights and important features of the Report:

Overview and highlights of product and application segments of the global QUANTUM COMPUTING TECHNOLOGIES Market are provided. Highlights of the segmentation study include price, revenue, sales, sales growth rate, and market share by product.

Explore about Sales data of key players of the global QUANTUM COMPUTING TECHNOLOGIES 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 QUANTUM COMPUTING TECHNOLOGIES Market.

Explore about gross margin, sales, revenue, production, market share, CAGR, and market size by region.

Describe QUANTUM COMPUTING TECHNOLOGIES Market Findings and Conclusion, Appendix, methodology and data source;

Research Methodology:

We identify the major drivers and restraints for every region (North America, Latin America, Europe, Asia Pacific, & Middle East) of any particular market with a weightage value of how it is impacting the market. For each driver and restraint, we provide weightage in short term, medium term, and long term. Here the driver acts as a pull factor and restraint as a push factor.

Primary ResearchKey players in the market are identified through review of secondary sources such as industry whitepapers, annual reports, published reports by credible agencies, financial reports and published interviews of Key Opinion Leaders (KOLs) from leading companies. During the primary interviews, KOLs also suggested some producers that are included under the initial scope of the study. We further refined company profile section by adding suggested producers by KOLs. KOLs include Chief Executive Officer (CEO), general managers, vice presidents, sales directors, market executives, R&D directors, product managers, procurement managers, export managers etc. During the research process, all the major stakeholders across the value chain are contacted for conducting primary interviews.

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There are 15 Chapters to display the Global QUANTUM COMPUTING TECHNOLOGIES Market:

Chapter 1, to describe Definition, Specifications and Classification of Global QUANTUM COMPUTING TECHNOLOGIES, Applications of, Market Segment by Regions;Chapter 2, to analyze the Manufacturing Cost Structure, Raw Material and Suppliers, Manufacturing Process, Industry Chain Structure;Chapter 3, to display the Technical Data and Manufacturing Plants Analysis of , Capacity and Commercial Production Date, Manufacturing Plants Distribution, Export & Import, R&D Status and Technology Source, Raw Materials Sources Analysis;Chapter 4, to show the Overall Market Analysis, Capacity Analysis (Company Segment), Sales Analysis (Company Segment), Sales Price Analysis (Company Segment);Chapter 5 and 6, to show the Regional Market Analysis that includes United States, EU, Japan, China, India & Southeast Asia, Segment Market Analysis (by Type);Chapter 7 and 8, to explore the Market Analysis by Application Major Manufacturers Analysis;Chapter 9, Market Trend Analysis, Regional Market Trend, Market Trend by Product Type, Market Trend by Application;Chapter 10, Regional Marketing Type Analysis, International Trade Type Analysis, Supply Chain Analysis;Chapter 11, to analyze the Consumers Analysis of Global QUANTUM COMPUTING TECHNOLOGIES by region, type and application;Chapter 12, to describe QUANTUM COMPUTING TECHNOLOGIES Research Findings and Conclusion, Appendix, methodology and data source;Chapter 13, 14 and 15, to describe QUANTUM COMPUTING TECHNOLOGIES sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source.

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Quantum Computing Market Analysis With Key Players, Applications, Trends and Forecast To 2026 – Instant Tech News

Quantum Computing Market Overview:

Verified Market Research adds new research report Quantum Computing Market Development Overview 2020, The report includes an in-depth analysis of the toggle switch market, taking into account market dynamics, segmentation, geographic expansion, competitive landscape and some other key issues. The market analysts who prepared the report have thoroughly examined the toggle switch market and provided reliable and accurate data. They understand the needs of the industry and customers, which makes it easier for them to focus on the problems that end users have been looking for. The research report provides an analysis of an assessment of existing and future trends in which players can invest. It also includes an assessment of the players financial perspectives and the nature of the competition.

Global Quantum Computing Market was valued at USD 89.35 million in 2016 and is projected to reach USD 948.82 million by 2025, growing at a CAGR of 30.02% from 2017 to 2025.

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Top 10 Companies in the Quantum Computing Market Research Report:

Competitive Landscape

The competitive landscape is a must-have information for the marketplayersto withstand the competition present in theglobal Quantum Computing market. This further helps the market participants to develop effective strategies to optimize their market positions. Moreover, the competitive analysis helps them to determine potential advantages as well as barriers within the global Quantum Computing market. This way, they can monitor how their competitors are implementing various strategies including pricing, marketing, and distribution.

The report analyses thecurrent trends, growth opportunities, competitive pricing, restraining factors, and boosters that may have an impact on the overall dynamics of the global Quantum Computing market. The report analytically studies the microeconomic and macroeconomic factors affecting the global Quantum Computing market growth. New and emerging technologies that may influence the global Quantum Computing market growth are also being studied in the report.

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 evaluation of the volatility of the political scenarios and amends likely to be made to the regulatory structures. This assessment gives an accurate analysis of the regional-wise growth of the global Quantum Computing market.

Regions Covered by the global market for Quantum Computing :

Middle East and Africa (GCC countries and Egypt)North America (USA, Mexico and Canada)South America (Brazil, etc.)Europe (Turkey, Germany, Russia, Great Britain, Italy, France etc.)Asia Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia and Australia)

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The study objectives are:

Important Questions Answered in this Report:-

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Verified market research partners with clients to provide insight into strategic and growth analytics; data that help achieve business goals and targets. Our core values include trust, integrity, and authenticity for our clients.

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TAGS: Quantum Computing Market Size, Quantum Computing Market Growth, Quantum Computing Market Forecast, Quantum Computing Market Analysis, Quantum Computing Market Trends, Quantum Computing Market

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Quantum Computing Market Analysis With Key Players, Applications, Trends and Forecast To 2026 - Instant Tech News

Quantum Computing Market Size Outlook 2026: Prime Firms, Trends, Growth Factors Details by Regions, Sorts and Applications – Instant Tech News

The report titled on Quantum Computing Market report offers in-intensity analysis of the worldwide market size (Production, Value and Consumption), splits the breakdown (data status 2014-2019 and 6 Forces forecast 2020 to 2026), by manufacturers, region, type and application. Quantum Computing market competitive landscape provides details by topmost manufactures like (D-Wave Systems, Google, IBM, Intel, Microsoft, 1QB Information Technologies, Anyon Systems, Cambridge Quantum Computing, ID Quantique, IonQ, QbitLogic, QC Ware, Quantum Circuits, Qubitekk, QxBranch, Rigetti Computing), including Company Overview, Company Total Revenue (Financials), Market Potential, Presence, Quantum Computing Sales and Revenue Generated, Market Share, Price, Production Sites And Facilities, SWOT Analysis, Product Launch. In the end, there are 4 key segments covered in this Quantum Computing market report: Competitor Segment, Product Type Segment, End Use/Application Segment and Quantum Computing industry geography segment.

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Quantum Computing Market Report Offers Comprehensive Assessment of:

1) Executive Summary, 2) Quantum Computing Market Overview, 3) Key Market Trends, 4) Key Success Factors, 5) Market Demand/Consumption (Value or Size in US$ Mn) Analysis, 6) Quantum Computing Market Background, 7) Quantum Computing industry Analysis & Forecast 20202026 by Type, Application and Region, 8) Quantum Computing Market Structure Analysis, 9) Competition Landscape, 10) Company Share and Company Profiles, 11) Assumptions and Acronyms and, 12) Research Methodology etc.

Scope of Quantum Computing Market:Quantum computing is a technology that applies the laws of quantum mechanics to computational ability. It includes three states, namely 1, 0 as well as the superposition of 1 and 0. Superposition indicates that two states exist at the same time. These bits are known as quantum bits or qubits. The global quantum computing market consists of the hardware that is required to develop quantum computers and its peripherals.

North America accounted for the largest share of the overall quantum computing market in 2017. On the other hand, Asia Pacific (APAC) would be the fastest growing region for quantum computing during the forecast period. This growth can be attributed to the increasing demand for quantum technology to solve the most tedious and complex problems in the defense and banking & finance industry.

On the basis of product type, this report displays the shipments, revenue (Million USD), price, and market share and growth rate of each type.

Hardware Software Services

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Please check your data: A self-driving car dataset failed to label hundreds of pedestrians, thousands of vehicles – The Register

Roundup It's a long weekend in the US, though sadly not in Blighty. So, for those of you starting your week, here's some bite-sized machine-learning news, beyond what we've recently covered, if that's your jam.

Check your training data: A popular dataset for training self-driving vehicles, including an open-source autonomous car system, failed to correctly label hundreds of pedestrians and thousands of vehicles.

Brad Dwyer, founder of Roboflow, a startup focused on building data science tools, discovered the errors when he started digging into the dataset compiled by Udacity, an online education platform.

I first noticed images that were missing annotations, Dwyer told The Register. That led me to dig in deeper and check some of the other images. I found so many errors I ended up going through all 15,000 images because I didnt want to re-share a dataset that had such obvious errors.

After flicking through each image, he found that 33 per cent of them contained mistakes. Thousands of vehicles, hundreds of pedestrians, and dozens of cyclists were not labelled. Some of the bounding boxes around objects were duplicated or needlessly oversized too.

Training an autonomous car on such an incomplete dataset could potentially be dangerous. The collection was pulled together to make it easier for engineers to collaborate and build a self-driving car. Thankfully, a project to develop such a system using this information seems to have died down since it launched more than three years ago.

Udacity created this dataset years ago as a tool purely for educational purposes, back when self-driving car datasets were very hard to come by, and those learning the skills needed to develop a career in this field lacked adequate training resources, a Udacity spokesperson told El Reg.

At the time it was helpful to the researchers and engineers who were transitioning into the autonomous vehicle community. In the intervening years, companies like Waymo, nuTonomy, and Voyage have published newer, better datasets intended for real-world scenarios. As a result, our project hasn't been active for three years.

We make no representations that the dataset is fully labeled or complete. Any attempts to show this educational data set as an actual dataset are both misleading and unhelpful. Udacity's self-driving car currently operates for educational purposes only on a closed test track. Our car has not operated on public streets for several years, so our car poses no risk to the public.

Roboflow has since corrected the errors on the dataset, and issued an improved version.

Standing up to patent trolls works: Mycroft AI, a startup building an open-source voice-controlled assistant for Linux-based devices, was sued for allegedly infringing a couple of patents, as we reported earlier this month.

Mycrofts CEO Joshua Montgomery spoke to The Register about his strong suspicions that he was being targeted by a so-called patent troll. His biz was told by a lawyer representing the patents' owner to cough up a license fee, and when Montgomery ignored the request, a patent-infringement lawsuit was filed against his company.

The mysterious patent owner, Voice Tech Corp, turned out to a brand new company in Texas, USA, and its address was someones bungalow, according to court filings. All of that fueled the growing speculation that, yes, Voice Tech Corp, was probably a patent troll.

Now, after facing sufficient resistance from Mycroft, Voice Tech Corp has dropped its case. Montgomery threatened to fight the lawsuit all the way to get Voice Tech Corps patents invalidated so that no other startup would have to face the same problem.

More Clearview drama: The controversial facial-recognition outfit that admitted to harvesting more than three billion publicly shared photos from social media sites is back in the news again.

The American Civil Liberties Union (ACLU) revealed it is trying to get Clearview to remove the claim from its marketing that its facial recognition code was verified using a methodology used by the ACLU. The rights warriors said they had no involvement in the product and do not endorse it. In fact, the union is pretty much against everything Clearview is doing.

Clearview boasts that its technology is 99 per cent accurate following numerous tests. Buzzfeed News, however, reckons it is nowhere near that good. The upstart previously said its algorithms helped police in New York City catch a terrorist planning to plant fake bombs on the subway. NYPD denied using Clearviews software.

Google, YouTube, Twitter, and Facebook have sent Clearview cease-and-desist letters demanding the startup stop scraping images of their platforms, and to delete those in its database. In a bizarre interview, Clearviews CEO fought back and said he believed that since all the photos were public, his stateside company, therefore, had a First Amendment right to public information." Er, yeah right.

Public funding for AI, 5G: President Donald Trump has vowed to spend more of US taxpayers' money on the research and development of emergent technologies, such as AI, quantum computing, and 5G, than traditional sciences.

The Budget prioritizes accelerating AI solutions, according to a proposal, subject to congressional approval, published this week. Along with quantum information sciences, advanced manufacturing, biotechnology, and 5G research and development (R&D), these technologies will be at the forefront of shaping future economies.

The Budget proposes large increases for key industries, including doubling AI and quantum information sciences R&D by 2022 as part of an all-of-Government approach to ensure the United States leads the world in these areas well into the future.

Trump pledged to spend $142.2bn in R&D for the next fiscal year, nine per cent less than this year. While AI and quantum computing are favored, there's less federal funding for general research and development for the other sciences.

The Department of Energy, the National Science Foundation, the National Institutes of Health, and others, will see cuts. The DOEs Advanced Research Projects Agency-Energy (ARPA-E) will be particularly hard hit: not only does the proposed budget effectively eliminate the agency, it must pay back $311m to the treasury.

You can read more about the proposed budget for the fiscal year of 2021, here.

CEO of AI startup steps down over allegations: The CEO of Clinc, a small artificial-intelligence outfit spun out of the University of Michigan, has resigned following claims he sexually harassed employees and customers.

Jason Mars, an assistant professor of computer science at the university, was accused of physically accosting clients, making lewd comments about female employees and interns, and hiring a prostitute during a work trip.

In an email to employees at Clinc, first reported by The Verge, Mars said the allegations against him were rife with embellishments and fabrications. He did, however, admit to drinking too much and partying with staff in a way thats not becoming of a CEO.

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Please check your data: A self-driving car dataset failed to label hundreds of pedestrians, thousands of vehicles - The Register